chore: import upstream snapshot with attribution
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# Copyright (c) Microsoft Corporation.
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# SPDX-License-Identifier: Apache-2.0
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# DeepSpeed Team
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import torch
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from deepspeed.runtime.checkpoint_engine.checkpoint_engine import \
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CheckpointEngine, CheckpointCommitInfo
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from deepspeed.runtime.model_checkpointing import (
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CHECKPOINT_WRITER,
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CHECKPOINT_SERIALIZATION,
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CheckpointWriterFactory,
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)
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class FastCheckpointEngine(CheckpointEngine):
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def __init__(self, config_params, dp_writer_config, optimize_dp_state):
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super().__init__(config_params)
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self.name = 'FastCheckpointEngine'
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self.serialization_enabled = config_params.checkpoint_config[CHECKPOINT_SERIALIZATION]
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self.optimize_dp_state = optimize_dp_state
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if dp_writer_config is None:
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self._writer = None
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else:
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self._writer = CheckpointWriterFactory(writer_config=config_params.checkpoint_config[CHECKPOINT_WRITER],
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aio_config=config_params.aio_config,
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dp_writer_config=dp_writer_config)
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def create(self, info: CheckpointCommitInfo):
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pass
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def save(self, state_dict, path: str):
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if self._writer is None:
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return
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torch.save(obj=state_dict,
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f=self._writer.create_writer(path, self.optimize_dp_state),
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_use_new_zipfile_serialization=self.serialization_enabled)
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self._writer.release_writer()
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def load(self, path: str, map_location=None):
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sd = torch.load(path, map_location=map_location)
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return sd
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def commit(self, info: CheckpointCommitInfo):
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return True
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def is_data_parallel_writer(self, dp_rank):
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return self._writer is not None
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