dcp checkpointer - ensure no distributed collectives while checkpoint…

… is ongoing (#870)

Summary: Pull Request resolved: #870

Reviewed By: saumishr, diego-urgell

Differential Revision: D60174864

fbshipit-source-id: 69d15c0c889b766aae540c8dfeb5642d7e3ea339

torchtnt/framework/callbacks/base_checkpointer.py

@@ -9,7 +9,7 @@
 import abc
 import logging
 from datetime import timedelta
-from typing import Any, cast, Iterable, Literal, Optional, Union
+from typing import Any, cast, Dict, Iterable, Literal, Optional, Union
 
 import torch.distributed as dist
 from pyre_extensions import none_throws
@@ -170,7 +170,7 @@ def _generate_checkpoint_and_upkeep(
                 value=metric_value,
             )
 
-        checkpoint_path = self._checkpoint_manager.generate_checkpoint_path(
+        checkpoint_path = self._generate_checkpoint_path(
             epoch,
             step_mapping,
             metric_data,
@@ -225,6 +225,20 @@ def _does_checkpoint_exist(
             checkpoint_path, process_group
         )
 
+    def _generate_checkpoint_path(
+        self,
+        epoch: int,
+        step_mapping: Union[int, Dict[Phase, int]],
+        metric_data: Optional[MetricData] = None,
+        process_group: Optional[dist.ProcessGroup] = None,
+    ) -> CheckpointPath:
+        return self._checkpoint_manager.generate_checkpoint_path(
+            epoch,
+            step_mapping,
+            metric_data,
+            process_group=process_group,
+        )
+
     def _get_tracked_metric_value(
         self, unit: Union[TTrainUnit, TEvalUnit]
     ) -> Optional[float]:

torchtnt/framework/callbacks/dcp_saver.py

@@ -38,7 +38,12 @@
     TTrainUnit,
 )
 from torchtnt.framework.utils import get_timing_context
-from torchtnt.utils.checkpoint import BestCheckpointConfig, CheckpointPath
+from torchtnt.utils.checkpoint import (
+    BestCheckpointConfig,
+    CheckpointPath,
+    MetricData,
+    Phase,
+)
 from torchtnt.utils.optimizer import init_optim_state
 from torchtnt.utils.rank_zero_log import rank_zero_info, rank_zero_warn
 from torchtnt.utils.stateful import MultiStateful, Stateful
@@ -385,6 +390,24 @@ def _does_checkpoint_exist(
             checkpoint_path=checkpoint_path, process_group=process_group
         )
 
+    def _generate_checkpoint_path(
+        self,
+        epoch: int,
+        step_mapping: Union[int, Dict[Phase, int]],
+        metric_data: Optional[MetricData] = None,
+        process_group: Optional[dist.ProcessGroup] = None,
+    ) -> CheckpointPath:
+        # if we are still checkpointing, this might cause a collective hang.
+        # so wait here instead
+        self._wait()
+
+        return super()._generate_checkpoint_path(
+            epoch=epoch,
+            step_mapping=step_mapping,
+            metric_data=metric_data,
+            process_group=process_group,
+        )
+
     @property
     def default_writer_options(self) -> Dict[str, Any]:
         # defaults are picked to to match TSS defaults