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[API] Add passthrough kwargs for torch.load #13

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merged 3 commits into from
Sep 11, 2024
Merged

[API] Add passthrough kwargs for torch.load #13

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0718126
[ENH] Add handling of passthrough kwargs to torch.load
scottclowe Sep 11, 2024
e52a57e
[API] Change to weights_only=True by default to torch.load
scottclowe Sep 11, 2024
82f3f3a
[DOC] Improve weights_only documentation
scottclowe Sep 11, 2024
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10 changes: 8 additions & 2 deletions wandb_preempt/checkpointer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -176,12 +176,18 @@ def save_checkpoint(self, extra_info: Dict) -> None:
save(data, tmp_savepath)
rename(tmp_savepath, savepath)

def load_latest_checkpoint(self) -> Tuple[int, Dict]:
def load_latest_checkpoint(
self, weights_only: bool = True, **kwargs
) -> Tuple[int, Dict]:
"""Load the latest checkpoint and set random number generator states.

Updates the model, optimizer, lr scheduler, and gradient scaler states
passed at initialization.

Args:
weights_only: Whether to load only the model weights. Default: `True`.
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**kwargs: Additional keyword arguments to pass to the `torch.load` function.

Returns:
The epoch number at which training should resume, and the extra information
that was passed by the user as a dictionary to the :meth:`step` function.
Expand All @@ -193,7 +199,7 @@ def load_latest_checkpoint(self) -> Tuple[int, Dict]:

self.maybe_print(f"Loading checkpoint {loadpath}.")

data = load(loadpath)
data = load(loadpath, weights_only=weights_only, **kwargs)
self.maybe_print("Loading model.")
self.model.load_state_dict(data["model"])
self.maybe_print("Loading optimizer.")
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