Fixes around Strategy.set_world_ranks

src/lightning/fabric/CHANGELOG.md

@@ -24,6 +24,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Allow using iterable-style datasets with TPUs ([#17331](https://github.com/Lightning-AI/lightning/pull/17331))
 
+
+- On XLA, avoid setting the global rank before processes have been launched as this will initialize the PJRT computation client in the main process ([#16966](https://github.com/Lightning-AI/lightning/pull/16966))
+
 ### Deprecated
 
 -
@@ -39,6 +42,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed issue where running on TPUs would select the wrong device index ([#17227](https://github.com/Lightning-AI/lightning/pull/17227))
 
 
+- Fixed issue where Fabric would not initialize the global rank, world size, and rank-zero-only rank after initialization and before launch ([#16966](https://github.com/Lightning-AI/lightning/pull/16966))
+
+
 ## [2.0.1.post0] - 2023-04-11
 
 No changes

src/lightning/fabric/connector.py

@@ -507,8 +507,8 @@ def _lazy_init_strategy(self) -> None:
                 self.strategy.parallel_devices = self._parallel_devices
         if hasattr(self.strategy, "num_nodes"):
             self.strategy._num_nodes = self._num_nodes_flag
-        if hasattr(self.strategy, "set_world_ranks"):
-            self.strategy.set_world_ranks()
+        if hasattr(self.strategy, "_set_world_ranks"):
+            self.strategy._set_world_ranks()
         self.strategy._configure_launcher()
 
         if _IS_INTERACTIVE and self.strategy.launcher and not self.strategy.launcher.is_interactive_compatible:

src/lightning/fabric/plugins/environments/lsf.py

@@ -88,7 +88,7 @@ def world_size(self) -> int:
         if world_size is None:
             raise ValueError(
                 "Cannot determine world size. Environment variable `JSM_NAMESPACE_SIZE` not found."
-                "Make sure you run your executable with `jsrun`."
+                " Make sure you run your executable with `jsrun`."
             )
         return int(world_size)
 
@@ -101,7 +101,7 @@ def global_rank(self) -> int:
         if global_rank is None:
             raise ValueError(
                 "Cannot determine global rank. Environment variable `JSM_NAMESPACE_RANK` not found."
-                "Make sure you run your executable with `jsrun`."
+                " Make sure you run your executable with `jsrun`."
             )
         return int(global_rank)
 
@@ -114,7 +114,7 @@ def local_rank(self) -> int:
         if local_rank is None:
             raise ValueError(
                 "Cannot determine local rank. Environment variable `JSM_NAMESPACE_LOCAL_RANK` not found."
-                "Make sure you run your executable with `jsrun`."
+                " Make sure you run your executable with `jsrun`."
             )
         return int(local_rank)
 

src/lightning/fabric/strategies/ddp.py

@@ -177,7 +177,6 @@ def register_strategies(cls, strategy_registry: Dict) -> None:
 
     def _setup_distributed(self) -> None:
         self._set_world_ranks()
-        rank_zero_only.rank = self.global_rank
         self._process_group_backend = self._get_process_group_backend()
         assert self.cluster_environment is not None
         _init_dist_connection(self.cluster_environment, self._process_group_backend, timeout=self._timeout)
@@ -186,11 +185,12 @@ def _get_process_group_backend(self) -> str:
         return self._process_group_backend or _get_default_process_group_backend_for_device(self.root_device)
 
     def _set_world_ranks(self) -> None:
-        if self.cluster_environment is None:
-            return
-        self.cluster_environment.set_global_rank(self.node_rank * self.num_processes + self.local_rank)
-        self.cluster_environment.set_world_size(self.num_nodes * self.num_processes)
-        rank_zero_only.rank = self.cluster_environment.global_rank()
+        if self.cluster_environment is not None:
+            self.cluster_environment.set_global_rank(self.node_rank * self.num_processes + self.local_rank)
+            self.cluster_environment.set_world_size(self.num_nodes * self.num_processes)
+        # `LightningEnvironment.set_global_rank` will do this too, but we cannot rely on that implementation detail
+        # additionally, for some implementations, the setter is a no-op, so it's safer to access the getter
+        rank_zero_only.rank = self.global_rank
 
     def _determine_ddp_device_ids(self) -> Optional[List[int]]:
         if self.root_device.type == "cpu":

src/lightning/fabric/strategies/deepspeed.py

@@ -33,7 +33,7 @@
 from lightning.fabric.strategies.strategy import _Sharded
 from lightning.fabric.utilities.distributed import log
 from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
-from lightning.fabric.utilities.rank_zero import rank_zero_info, rank_zero_only, rank_zero_warn
+from lightning.fabric.utilities.rank_zero import rank_zero_info, rank_zero_warn
 from lightning.fabric.utilities.seed import reset_seed
 from lightning.fabric.utilities.types import _PATH
 
@@ -580,7 +580,6 @@ def _setup_distributed(self) -> None:
             )
         reset_seed()
         self._set_world_ranks()
-        rank_zero_only.rank = self.global_rank
         self._init_deepspeed_distributed()
         if not self._config_initialized:
             self._format_config()

src/lightning/fabric/strategies/fsdp.py

@@ -320,7 +320,6 @@ def register_strategies(cls, strategy_registry: Dict) -> None:
     def _setup_distributed(self) -> None:
         reset_seed()
         self._set_world_ranks()
-        rank_zero_only.rank = self.global_rank
         self._process_group_backend = self._get_process_group_backend()
         assert self.cluster_environment is not None
         _init_dist_connection(self.cluster_environment, self._process_group_backend, timeout=self._timeout)
@@ -329,11 +328,12 @@ def _get_process_group_backend(self) -> str:
         return self._process_group_backend or _get_default_process_group_backend_for_device(self.root_device)
 
     def _set_world_ranks(self) -> None:
-        if self.cluster_environment is None:
-            return
-        self.cluster_environment.set_global_rank(self.node_rank * self.num_processes + self.local_rank)
-        self.cluster_environment.set_world_size(self.num_nodes * self.num_processes)
-        rank_zero_only.rank = self.cluster_environment.global_rank()
+        if self.cluster_environment is not None:
+            self.cluster_environment.set_global_rank(self.node_rank * self.num_processes + self.local_rank)
+            self.cluster_environment.set_world_size(self.num_nodes * self.num_processes)
+        # `LightningEnvironment.set_global_rank` will do this too, but we cannot rely on that implementation detail
+        # additionally, for some implementations, the setter is a no-op, so it's safer to access the getter
+        rank_zero_only.rank = self.global_rank
 
 
 def _setup_activation_checkpointing(module: "FullyShardedDataParallel", layers: List[Type[Module]]) -> None:

src/lightning/fabric/strategies/xla.py

@@ -93,7 +93,6 @@ def _configure_launcher(self) -> None:
 
     def setup_environment(self) -> None:
         self._launched = True
-        self._set_world_ranks()
         rank_zero_only.rank = self.global_rank
         super().setup_environment()
 
@@ -203,8 +202,3 @@ def remove_checkpoint(self, filepath: _PATH) -> None:
     @classmethod
     def register_strategies(cls, strategy_registry: Dict) -> None:
         strategy_registry.register("xla", cls, description=cls.__class__.__name__)
-
-    def _set_world_ranks(self) -> None:
-        if self.cluster_environment is None:
-            return
-        rank_zero_only.rank = self.cluster_environment.global_rank()

src/lightning/pytorch/CHANGELOG.md

@@ -33,6 +33,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Allow using iterable-style datasets with TPUs ([#17331](https://github.com/Lightning-AI/lightning/pull/17331))
 
+
+- On XLA, avoid setting the global rank before processes have been launched as this will initialize the PJRT computation client in the main process ([#16966](https://github.com/Lightning-AI/lightning/pull/16966))
+
 ### Deprecated
 
 -

src/lightning/pytorch/strategies/ddp.py

@@ -183,7 +183,6 @@ def setup_distributed(self) -> None:
         log.debug(f"{self.__class__.__name__}: setting up distributed...")
         reset_seed()
         self.set_world_ranks()
-        rank_zero_only.rank = self.global_rank
         self._process_group_backend = self._get_process_group_backend()
         assert self.cluster_environment is not None
         _init_dist_connection(self.cluster_environment, self._process_group_backend, timeout=self._timeout)
@@ -192,11 +191,12 @@ def _get_process_group_backend(self) -> str:
         return self._process_group_backend or _get_default_process_group_backend_for_device(self.root_device)
 
     def set_world_ranks(self) -> None:
-        if self.cluster_environment is None:
-            return
-        self.cluster_environment.set_global_rank(self.node_rank * self.num_processes + self.local_rank)
-        self.cluster_environment.set_world_size(self.num_nodes * self.num_processes)
-        rank_zero_only.rank = self.cluster_environment.global_rank()
+        if self.cluster_environment is not None:
+            self.cluster_environment.set_global_rank(self.node_rank * self.num_processes + self.local_rank)
+            self.cluster_environment.set_world_size(self.num_nodes * self.num_processes)
+        # `LightningEnvironment.set_global_rank` will do this too, but we cannot rely on that implementation detail
+        # additionally, for some implementations, the setter is a no-op, so it's safer to access the getter
+        rank_zero_only.rank = self.global_rank
 
     def _register_ddp_hooks(self) -> None:
         log.debug(f"{self.__class__.__name__}: registering ddp hooks")

src/lightning/pytorch/strategies/deepspeed.py

@@ -43,7 +43,7 @@
 from lightning.pytorch.utilities import GradClipAlgorithmType
 from lightning.pytorch.utilities.exceptions import MisconfigurationException
 from lightning.pytorch.utilities.model_helpers import is_overridden
-from lightning.pytorch.utilities.rank_zero import rank_zero_info, rank_zero_only, rank_zero_warn, WarningCache
+from lightning.pytorch.utilities.rank_zero import rank_zero_info, rank_zero_warn, WarningCache
 from lightning.pytorch.utilities.types import LRSchedulerConfig, STEP_OUTPUT
 
 log = logging.getLogger(__name__)
@@ -326,7 +326,6 @@ def _load_config(self, config: Optional[Union[_PATH, Dict[str, Any]]]) -> Option
     def setup_distributed(self) -> None:
         reset_seed()
         self.set_world_ranks()
-        rank_zero_only.rank = self.global_rank
         self._init_deepspeed_distributed()
         if not self._config_initialized:
             self._format_config()

src/lightning/pytorch/strategies/fsdp.py

@@ -178,9 +178,6 @@ def setup_environment(self) -> None:
         # determine which process we are and world size
         self.set_world_ranks()
 
-        # set warning rank
-        rank_zero_only.rank = self.global_rank
-
         self._process_group_backend = self._get_process_group_backend()
         assert self.cluster_environment is not None
         _init_dist_connection(self.cluster_environment, self._process_group_backend)
@@ -190,11 +187,12 @@ def _get_process_group_backend(self) -> str:
         return self._process_group_backend or _get_default_process_group_backend_for_device(self.root_device)
 
     def set_world_ranks(self) -> None:
-        if self.cluster_environment is None:
-            return
-        self.cluster_environment.set_global_rank(self.node_rank * self.num_processes + self.local_rank)
-        self.cluster_environment.set_world_size(self.num_nodes * self.num_processes)
-        rank_zero_only.rank = self.cluster_environment.global_rank()
+        if self.cluster_environment is not None:
+            self.cluster_environment.set_global_rank(self.node_rank * self.num_processes + self.local_rank)
+            self.cluster_environment.set_world_size(self.num_nodes * self.num_processes)
+        # `LightningEnvironment.set_global_rank` will do this too, but we cannot rely on that implementation detail
+        # additionally, for some implementations, the setter is a no-op, so it's safer to access the getter
+        rank_zero_only.rank = self.global_rank
 
     def _configure_launcher(self) -> None:
         assert self.cluster_environment is not None

src/lightning/pytorch/strategies/xla.py

@@ -201,13 +201,13 @@ def reduce(
 
     def setup_distributed(self) -> None:
         self._launched = True
-        self.set_world_ranks()
         rank_zero_only.rank = self.global_rank
 
     def set_world_ranks(self) -> None:
-        if self.cluster_environment is None:
-            return
-        rank_zero_only.rank = self.cluster_environment.global_rank()
+        # accessing global_rank will initialize the XLA computation client. since this is called outside of the spawned
+        # processes (by the accelerator connector), we cannot run the code that would normally be here.
+        # instead it's done in `setup_distributed`
+        pass
 
     def validation_step(self, *args: Any, **kwargs: Any) -> Optional[STEP_OUTPUT]:
         assert self.model is not None

tests/tests_fabric/test_connector.py

@@ -128,6 +128,8 @@ def creates_processes_externally(self) -> bool:
     assert isinstance(connector.accelerator, CPUAccelerator)
     assert isinstance(connector.strategy, DDPStrategy)
     assert isinstance(connector.strategy.cluster_environment, CustomCluster)
+    # this checks that `strategy._set_world_ranks` was called by the connector
+    assert connector.strategy.world_size == 2
 
 
 @RunIf(mps=False)
@@ -230,10 +232,10 @@ class Strat(DDPStrategy):
 @mock.patch("lightning.fabric.plugins.environments.lsf.LSFEnvironment._get_node_rank", return_value=0)
 def test_fallback_from_ddp_spawn_to_ddp_on_cluster(_, __, env_vars, expected_environment):
     with mock.patch.dict(os.environ, env_vars, clear=True):
-        trainer = _Connector(strategy="ddp_spawn", accelerator="cpu", devices=2)
-    assert isinstance(trainer.accelerator, CPUAccelerator)
-    assert isinstance(trainer.strategy, DDPStrategy)
-    assert isinstance(trainer.strategy.cluster_environment, expected_environment)
+        connector = _Connector(strategy="ddp_spawn", accelerator="cpu", devices=2)
+    assert isinstance(connector.accelerator, CPUAccelerator)
+    assert isinstance(connector.strategy, DDPStrategy)
+    assert isinstance(connector.strategy.cluster_environment, expected_environment)
 
 
 @RunIf(mps=False)