[feat] support a context for loading state_dict for FSDP (#1065)

* [fix]: add a context for supporting state_dict from a non-FSDP parent module

* formatting

Co-authored-by: Min Xu <[email protected]>

fairscale/nn/data_parallel/__init__.py

@@ -5,7 +5,13 @@
 
 from typing import List
 
-from .fully_sharded_data_parallel import FullyShardedDataParallel, OffloadConfig, TrainingState, auto_wrap_bn
+from .fully_sharded_data_parallel import (
+    FullyShardedDataParallel,
+    OffloadConfig,
+    TrainingState,
+    auto_wrap_bn,
+    no_pre_load_state_dict_hook,
+)
 from .sharded_ddp import ShardedDataParallel
 
 __all__: List[str] = []

fairscale/nn/data_parallel/fully_sharded_data_parallel.py

@@ -51,7 +51,7 @@
 from fairscale.internal.params import calc_grad_norm, recursive_copy_to_device
 from fairscale.internal.reduce_scatter_bucketer import ReduceScatterBucketer
 from fairscale.internal.state_dict import replace_by_prefix_
-from fairscale.nn.misc import FlattenParamsWrapper
+from fairscale.nn.misc import FlattenParamsWrapper, _enable_pre_load_state_dict_hook
 from fairscale.nn.wrap import auto_wrap, config_auto_wrap_policy, enable_wrap
 
 from . import fsdp_optim_utils as ou
@@ -762,6 +762,7 @@ def _shard_parameters_(self) -> None:
                     self.numel_padded_per_param.append(0)
                     continue
             p._is_sharded = True
+            # TODO (Min): broadcast from rank 0 to avoid each rank need to init with the same seed?
 
             # Replace p.data with the relevant shard.
             orig_data = p.data
@@ -2581,10 +2582,25 @@ def apply_to_tensor(obj: torch.Tensor) -> torch.Tensor:
     return state_dict
 
 
+@contextlib.contextmanager
+def no_pre_load_state_dict_hook() -> Generator:
+    """Disable the pre-load hook.
+
+    This is needed if we are loading a state_dict that was not produced by
+    a root FSDP instance.
+    """
+    global _enable_pre_load_state_dict_hook
+    bak = _enable_pre_load_state_dict_hook
+    _enable_pre_load_state_dict_hook = False
+    yield
+    _enable_pre_load_state_dict_hook = bak
+
+
 def _pre_load_state_dict_hook(
     state_dict: Union[Dict[str, torch.Tensor], "OrderedDict[str, torch.Tensor]"], prefix: str, *args: Any
 ) -> None:
-    replace_by_prefix_(state_dict, prefix, prefix + "_fsdp_wrapped_module.")
+    if _enable_pre_load_state_dict_hook:
+        replace_by_prefix_(state_dict, prefix, prefix + "_fsdp_wrapped_module.")
 
 
 def _clean_path(path: str) -> str:

fairscale/nn/misc/__init__.py

@@ -9,7 +9,7 @@
 # in favor of fairscale.nn.checkpoint.checkpoint_wrapper.
 from fairscale.nn.checkpoint import checkpoint_wrapper
 
-from .flatten_params_wrapper import FlattenParamsWrapper
+from .flatten_params_wrapper import FlattenParamsWrapper, _enable_pre_load_state_dict_hook
 from .param_bucket import GradBucket, ParamBucket
 
 __all__: List[str] = []

fairscale/nn/misc/flatten_params_wrapper.py

@@ -49,6 +49,9 @@
 if TYPE_CHECKING:
     from collections import OrderedDict  # noqa: F401
 
+# See no_pre_load_state_dict_hook context manager function in FSDP for more details.
+_enable_pre_load_state_dict_hook = True
+
 
 class FlatParameter(nn.Parameter):
     """A parameter that is initialized from a list of parameters and can be
@@ -543,6 +546,8 @@ def _post_state_dict_hook(
 def _pre_load_state_dict_hook(
     state_dict: Union[Dict[str, Tensor], "OrderedDict[str, Tensor]"], prefix: str, *args: Any
 ) -> None:
+    if not _enable_pre_load_state_dict_hook:
+        return
     # Push everything down to ._fpw_module level.
     replace_by_prefix_(state_dict, prefix, prefix + "_fpw_module.")
     # The flat_param_* keys actually needs to move one level up.