Remove support for deprecated DCP APIs in DCPSaver callback (#890)

Summary: Pull Request resolved: #890

Reviewed By: anshulverma, JKSenthil

Differential Revision: D61887203

fbshipit-source-id: 17bd899a9b88033feb0285f3a395be6edbf82d5a

Author: diego-urgell

tests/framework/callbacks/test_dcp_saver.py

@@ -7,18 +7,11 @@
 
 # pyre-strict
 
-import unittest
-
-from torchtnt.framework.callbacks.dcp_saver import _LATEST_DCP_AVAIL
-from torchtnt.framework.state import State
-
-if not _LATEST_DCP_AVAIL:
-    raise unittest.SkipTest("Latest Pytorch is required to run DCP tests")
-
 import math
 import os
 import shutil
 import tempfile
+import unittest
 from typing import Any, Dict, Iterator, List, Optional
 from unittest import mock
 from unittest.mock import MagicMock, patch
@@ -40,6 +33,8 @@
 )
 from torchtnt.framework.callbacks.checkpointer_types import KnobOptions, RestoreOptions
 from torchtnt.framework.callbacks.dcp_saver import DistributedCheckpointSaver
+
+from torchtnt.framework.state import State
 from torchtnt.framework.train import train
 from torchtnt.utils.distributed import get_global_rank, spawn_multi_process
 from torchtnt.utils.env import seed

torchtnt/framework/callbacks/dcp_saver.py

@@ -16,6 +16,11 @@
 import torch.distributed as dist
 from pyre_extensions import none_throws
 from torch.distributed import checkpoint as dcp
+
+from torch.distributed.checkpoint._fsspec_filesystem import (
+    FsspecReader as Reader,
+    FsspecWriter as Writer,
+)
 from torch.distributed.checkpoint.default_planner import (
     DefaultLoadPlanner,
     DefaultSavePlanner,
@@ -45,25 +50,8 @@
 from torchtnt.utils.rank_zero_log import rank_zero_info, rank_zero_warn
 from torchtnt.utils.stateful import MultiStateful, Stateful
 
-
 logger: logging.Logger = logging.getLogger(__name__)
 
-_LATEST_DCP_AVAIL: bool = True
-try:
-    from torch.distributed.checkpoint._fsspec_filesystem import (
-        FsspecReader as Reader,
-        FsspecWriter as Writer,
-    )
-except ModuleNotFoundError:
-    logger.warn(
-        "To use FsspecReader / FsspecWriter, please install latest pytorch version"
-    )
-    _LATEST_DCP_AVAIL = False
-    from torch.distributed.checkpoint import (
-        FileSystemReader as Reader,
-        FileSystemWriter as Writer,
-    )
-
 
 class DistributedCheckpointSaver(BaseCheckpointer):
     """
@@ -248,24 +236,13 @@ def _save(
         if storage_writer is None:
             storage_writer = Writer(checkpoint_id, **self.default_writer_options)
 
-        try:
-            dcp.save(
-                state_dict={"app_state": MultiStateful(app_state)},
-                checkpoint_id=checkpoint_id,
-                process_group=self._process_group,
-                storage_writer=storage_writer,
-                planner=planner,
-            )
-        except AttributeError as ex:
-            logger.warning(
-                f"Unable to save checkpoint (will retry saving using deprecated API). Error: {ex}"
-            )
-            dcp.save_state_dict(
-                state_dict={"app_state": MultiStateful(app_state)},
-                process_group=self._process_group,
-                storage_writer=storage_writer,
-                planner=planner,
-            )
+        dcp.save(
+            state_dict={"app_state": MultiStateful(app_state)},
+            checkpoint_id=checkpoint_id,
+            process_group=self._process_group,
+            storage_writer=storage_writer,
+            planner=planner,
+        )
 
         return True
 
@@ -397,21 +374,14 @@ def restore_with_id(
             if isinstance(optimizer, torch.optim.Optimizer):
                 init_optim_state(optimizer)
 
-        try:
-            dcp.load(
-                {"app_state": MultiStateful(app_state)},
-                checkpoint_id=checkpoint_id,
-                storage_reader=storage_reader,
-                planner=planner,
-                process_group=process_group,
-            )
-        except AttributeError:
-            dcp.load_state_dict(
-                {"app_state": MultiStateful(app_state)},
-                storage_reader=storage_reader,
-                process_group=process_group,
-                planner=planner,
-            )
+        dcp.load(
+            {"app_state": MultiStateful(app_state)},
+            checkpoint_id=checkpoint_id,
+            storage_reader=storage_reader,
+            planner=planner,
+            process_group=process_group,
+        )
+
         rank_zero_info(
             f"Restored snapshot for checkpoint_id: {checkpoint_id}", logger=logger
         )