58 lines
2.5 KiB
Python
58 lines
2.5 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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from typing import Any, Dict, Optional
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from pytorch_lightning.plugins.io.torch_plugin import TorchCheckpointIO
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from pytorch_lightning.utilities import _OMEGACONF_AVAILABLE, _TPU_AVAILABLE
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from pytorch_lightning.utilities.apply_func import apply_to_collection
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from pytorch_lightning.utilities.cloud_io import get_filesystem
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from pytorch_lightning.utilities.types import _PATH
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if _TPU_AVAILABLE:
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import torch_xla.core.xla_model as xm
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if _OMEGACONF_AVAILABLE:
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from omegaconf import DictConfig, ListConfig, OmegaConf
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class XLACheckpointIO(TorchCheckpointIO):
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"""CheckpointIO that utilizes :func:`xm.save` to save checkpoints for TPU training strategies."""
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def save_checkpoint(self, checkpoint: Dict[str, Any], path: _PATH, storage_options: Optional[Any] = None) -> None:
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"""Save model/training states as a checkpoint file through state-dump and file-write.
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Args:
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checkpoint: dict containing model and trainer state
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path: write-target path
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storage_options: not used in ``XLACheckpointIO.save_checkpoint``
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Raises:
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TypeError:
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If ``storage_options`` arg is passed in
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"""
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if storage_options is not None:
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raise TypeError(
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"`Trainer.save_checkpoint(..., storage_options=...)` with `storage_options` arg"
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f" is not supported for `{self.__class__.__name__}`. Please implement your custom `CheckpointIO`"
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" to define how you'd like to use `storage_options`."
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)
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fs = get_filesystem(path)
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fs.makedirs(os.path.dirname(path), exist_ok=True)
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# Todo: TypeError: 'mappingproxy' object does not support item assignment
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# Ref: https://github.com/pytorch/xla/issues/2773
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if _OMEGACONF_AVAILABLE:
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checkpoint = apply_to_collection(checkpoint, (DictConfig, ListConfig), OmegaConf.to_container)
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xm.save({k: v for k, v in checkpoint.items() if k != "callbacks"}, path)
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