63 lines
2.3 KiB
Python
63 lines
2.3 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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from abc import ABC, abstractmethod
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from typing import Any, Dict, Optional
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from pytorch_lightning.utilities.types import _PATH
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class CheckpointIO(ABC):
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"""Interface to save/load checkpoints as they are saved through the ``TrainingTypePlugin``.
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Typically most plugins either use the Torch based IO Plugin; ``TorchCheckpointIO`` but may
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require particular handling depending on the plugin.
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In addition, you can pass a custom ``CheckpointIO`` by extending this class and passing it
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to the Trainer, i.e ``Trainer(plugins=[MyCustomCheckpointIO()])``.
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.. note::
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For some plugins, it is not possible to use a custom checkpoint plugin as checkpointing logic is not
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modifiable.
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"""
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@abstractmethod
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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: Optional parameters when saving the model/training states.
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"""
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@abstractmethod
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def load_checkpoint(self, path: _PATH, storage_options: Optional[Any] = None) -> Dict[str, Any]:
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"""Load checkpoint from a path when resuming or loading ckpt for test/validate/predict stages.
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Args:
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path: Path to checkpoint
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storage_options: Optional parameters when loading the model/training states.
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Returns: The loaded checkpoint.
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"""
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@abstractmethod
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def remove_checkpoint(self, path: _PATH) -> None:
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"""Remove checkpoint file from the filesystem.
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Args:
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path: Path to checkpoint
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"""
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