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Enable all attention operators to work with MultiHeadAttention #383

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May 6, 2024
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Enable all attention operators to work with MultiHeadAttention #383

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5 changes: 4 additions & 1 deletion pypots/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -285,7 +285,10 @@ def save(
f"‼️ File {saving_path} exists. Argument `overwrite` is True. Overwriting now..."
)
else:
logger.error(f"❌ File {saving_path} exists. Saving operation aborted.")
logger.error(
f"❌ File {saving_path} exists. Saving operation aborted. "
f"Use the arg `overwrite=True` to force overwrite."
)

try:
create_dir_if_not_exist(saving_dir)
Expand Down
4 changes: 2 additions & 2 deletions pypots/classification/raindrop/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,8 +21,8 @@ def __init__(
n_features,
n_layers,
d_model,
d_ffn,
n_heads,
d_ffn,
n_classes,
dropout=0.3,
max_len=215,
Expand All @@ -41,8 +41,8 @@ def __init__(
n_features,
n_layers,
d_model,
d_ffn,
n_heads,
d_ffn,
n_classes,
dropout,
max_len,
Expand Down
10 changes: 5 additions & 5 deletions pypots/classification/raindrop/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,12 +43,12 @@ class Raindrop(BaseNNClassifier):
The dimension of the Transformer encoder backbone.
It is the input dimension of the multi-head self-attention layers.

d_ffn :
The dimension of the layer in the Feed-Forward Networks (FFN).

n_heads :
The number of heads in the multi-head self-attention mechanism.

d_ffn :
The dimension of the layer in the Feed-Forward Networks (FFN).

dropout :
The dropout rate for all fully-connected layers in the model.

Expand Down Expand Up @@ -112,8 +112,8 @@ def __init__(
n_classes,
n_layers,
d_model,
d_ffn,
n_heads,
d_ffn,
dropout,
d_static=0,
aggregation="mean",
Expand Down Expand Up @@ -147,8 +147,8 @@ def __init__(
n_features,
n_layers,
d_model,
d_ffn,
n_heads,
d_ffn,
n_classes,
dropout,
n_steps,
Expand Down
36 changes: 11 additions & 25 deletions pypots/imputation/autoformer/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,13 +8,7 @@

import torch.nn as nn

from ...nn.modules.autoformer import (
SeasonalLayerNorm,
AutoformerEncoderLayer,
AutoCorrelation,
AutoCorrelationLayer,
)
from ...nn.modules.informer import InformerEncoder
from ...nn.modules.autoformer import AutoformerEncoder
from ...nn.modules.saits import SaitsLoss, SaitsEmbedding


Expand All @@ -24,8 +18,8 @@ def __init__(
n_steps,
n_features,
n_layers,
n_heads,
d_model,
n_heads,
d_ffn,
factor,
moving_avg_window_size,
Expand All @@ -44,23 +38,15 @@ def __init__(
with_pos=False,
dropout=dropout,
)
self.encoder = InformerEncoder(
[
AutoformerEncoderLayer(
AutoCorrelationLayer(
AutoCorrelation(factor, dropout),
d_model,
n_heads,
),
d_model,
d_ffn,
moving_avg_window_size,
dropout,
activation,
)
for _ in range(n_layers)
],
norm_layer=SeasonalLayerNorm(d_model),
self.encoder = AutoformerEncoder(
n_layers,
d_model,
n_heads,
d_ffn,
factor,
moving_avg_window_size,
dropout,
activation,
)

# for the imputation task, the output dim is the same as input dim
Expand Down
10 changes: 5 additions & 5 deletions pypots/imputation/autoformer/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,12 +37,12 @@ class Autoformer(BaseNNImputer):
n_layers :
The number of layers in the Autoformer model.

n_heads :
The number of heads in each layer of Autoformer.

d_model :
The dimension of the model.

n_heads :
The number of heads in each layer of Autoformer.

d_ffn :
The dimension of the feed-forward network.

Expand Down Expand Up @@ -107,8 +107,8 @@ def __init__(
n_steps: int,
n_features: int,
n_layers: int,
n_heads: int,
d_model: int,
n_heads: int,
d_ffn: int,
factor: int,
moving_avg_window_size: int,
Expand Down Expand Up @@ -152,8 +152,8 @@ def __init__(
self.n_steps,
self.n_features,
self.n_layers,
self.n_heads,
self.d_model,
self.n_heads,
self.d_ffn,
self.factor,
self.moving_avg_window_size,
Expand Down
2 changes: 1 addition & 1 deletion pypots/imputation/crossformer/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,8 +23,8 @@ def __init__(
n_steps,
n_features,
n_layers,
n_heads,
d_model,
n_heads,
d_ffn,
factor,
seg_len,
Expand Down
10 changes: 5 additions & 5 deletions pypots/imputation/crossformer/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,12 +37,12 @@ class Crossformer(BaseNNImputer):
n_layers :
The number of layers in the 1st and 2nd DMSA blocks in the SAITS model.

n_heads:
The number of heads in the multi-head attention mechanism.

d_model :
The dimension of the model.

n_heads:
The number of heads in the multi-head attention mechanism.

d_ffn :
The dimension of the feed-forward network.

Expand Down Expand Up @@ -110,8 +110,8 @@ def __init__(
n_steps: int,
n_features: int,
n_layers: int,
n_heads: int,
d_model: int,
n_heads: int,
d_ffn: int,
factor: int,
seg_len: int,
Expand Down Expand Up @@ -157,8 +157,8 @@ def __init__(
self.n_steps,
self.n_features,
self.n_layers,
self.n_heads,
self.d_model,
self.n_heads,
self.d_ffn,
self.factor,
self.seg_len,
Expand Down
4 changes: 2 additions & 2 deletions pypots/imputation/etsformer/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,8 +24,8 @@ def __init__(
n_features,
n_e_layers,
n_d_layers,
n_heads,
d_model,
n_heads,
d_ffn,
dropout,
top_k,
Expand Down Expand Up @@ -53,7 +53,7 @@ def __init__(
n_steps,
n_steps,
top_k,
dim_feedforward=d_ffn,
d_ffn=d_ffn,
dropout=dropout,
activation=activation,
)
Expand Down
10 changes: 5 additions & 5 deletions pypots/imputation/etsformer/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,12 +40,12 @@ class ETSformer(BaseNNImputer):
n_d_layers :
The number of layers in the ETSformer decoder.

n_heads :
The number of heads in each layer of ETSformer.

d_model :
The dimension of the model.

n_heads :
The number of heads in each layer of ETSformer.

d_ffn :
The dimension of the feed-forward network.

Expand Down Expand Up @@ -108,8 +108,8 @@ def __init__(
n_features,
n_e_layers,
n_d_layers,
n_heads,
d_model,
n_heads,
d_ffn,
top_k,
dropout: float = 0,
Expand Down Expand Up @@ -153,8 +153,8 @@ def __init__(
self.n_features,
self.n_e_layers,
self.n_d_layers,
self.n_heads,
self.d_model,
self.n_heads,
self.d_ffn,
self.dropout,
self.top_k,
Expand Down
4 changes: 2 additions & 2 deletions pypots/imputation/fedformer/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,8 +18,8 @@ def __init__(
n_steps,
n_features,
n_layers,
n_heads,
d_model,
n_heads,
d_ffn,
moving_avg_window_size,
dropout,
Expand All @@ -43,8 +43,8 @@ def __init__(
self.encoder = FEDformerEncoder(
n_steps,
n_layers,
n_heads,
d_model,
n_heads,
d_ffn,
moving_avg_window_size,
dropout,
Expand Down
4 changes: 2 additions & 2 deletions pypots/imputation/fedformer/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,8 +115,8 @@ def __init__(
n_steps,
n_features,
n_layers,
n_heads,
d_model,
n_heads,
d_ffn,
moving_avg_window_size,
dropout: float = 0,
Expand Down Expand Up @@ -164,8 +164,8 @@ def __init__(
self.n_steps,
self.n_features,
self.n_layers,
self.n_heads,
self.d_model,
self.n_heads,
self.d_ffn,
self.moving_avg_window_size,
self.dropout,
Expand Down
6 changes: 3 additions & 3 deletions pypots/imputation/informer/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,8 +24,8 @@ def __init__(
n_steps,
n_features,
n_layers,
n_heads,
d_model,
n_heads,
d_ffn,
factor,
dropout,
Expand All @@ -47,11 +47,11 @@ def __init__(
[
InformerEncoderLayer(
MultiHeadAttention(
n_heads,
ProbAttention(False, factor, dropout),
d_model,
n_heads,
d_model // n_heads,
d_model // n_heads,
ProbAttention(False, factor, dropout),
),
d_model,
d_ffn,
Expand Down
10 changes: 5 additions & 5 deletions pypots/imputation/informer/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,12 +37,12 @@ class Informer(BaseNNImputer):
n_layers :
The number of layers in the Informer model.

n_heads :
The number of heads in each layer of Informer.

d_model :
The dimension of the model.

n_heads :
The number of heads in each layer of Informer.

d_ffn :
The dimension of the feed-forward network.

Expand Down Expand Up @@ -104,8 +104,8 @@ def __init__(
n_steps: int,
n_features: int,
n_layers: int,
n_heads: int,
d_model: int,
n_heads: int,
d_ffn: int,
factor: int,
dropout: float = 0,
Expand Down Expand Up @@ -147,8 +147,8 @@ def __init__(
self.n_steps,
self.n_features,
self.n_layers,
self.n_heads,
self.d_model,
self.n_heads,
self.d_ffn,
self.factor,
self.dropout,
Expand Down
4 changes: 2 additions & 2 deletions pypots/imputation/itransformer/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,10 +20,10 @@ def __init__(
n_features: int,
n_layers: int,
d_model: int,
d_ffn: int,
n_heads: int,
d_k: int,
d_v: int,
d_ffn: int,
dropout: float,
attn_dropout: float,
ORT_weight: float = 1,
Expand All @@ -41,10 +41,10 @@ def __init__(
self.encoder = TransformerEncoder(
n_layers,
d_model,
d_ffn,
n_heads,
d_k,
d_v,
d_ffn,
dropout,
attn_dropout,
)
Expand Down
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