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f073dcd4f7
First pass at adding a save/load API, as well as definition of Stateful objects. Amongst a couple todo's, we still need to explore adding an `all_gather` & potentially a `barrier` while iterating through state keys. Pull Request resolved: https://github.com/pytorch/pytorch/pull/113867 Approved by: https://github.com/fegin, https://github.com/wz337
44 lines
1.0 KiB
Python
44 lines
1.0 KiB
Python
from typing import Any, Dict, runtime_checkable, TypeVar
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from typing_extensions import Protocol
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__all__ = ["Stateful", "StatefulT"]
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@runtime_checkable
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class Stateful(Protocol):
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"""
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Stateful protocol for objects that can be checkpointed and restored.
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"""
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def state_dict(self) -> Dict[str, Any]:
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"""
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Objects should return their state_dict representation as a dictionary.
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The output of this function will be checkpointed, and later restored in
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`load_state_dict()`.
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.. warning::
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Because of the inplace nature of restoring a checkpoint, this function
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is also called during `torch.distributed.checkpoint.load`.
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Returns:
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Dict: The objects state dict
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"""
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...
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def load_state_dict(self, state_dict: Dict[str, Any]) -> None:
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"""
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Restore the object's state from the provided state_dict.
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Args:
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state_dict: The state dict to restore from
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"""
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...
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StatefulT = TypeVar("StatefulT", bound=Stateful)
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