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https://github.com/google-deepmind/deepmind-research.git
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Nimrod Gileadi
89 lines
2.8 KiB
Python
89 lines
2.8 KiB
Python
# Copyright 2020 DeepMind Technologies Limited.
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#
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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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# https://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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"""Checkpointing functionality."""
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import os
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from typing import Any, Mapping, Optional
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from absl import logging
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import dill
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import jax
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import jax.numpy as jnp
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class Checkpointer:
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"""A checkpoint saving and loading class."""
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def __init__(self, checkpoint_dir: str, filename: str):
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"""Class initializer.
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Args:
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checkpoint_dir: Checkpoint directory.
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filename: Filename of checkpoint in checkpoint directory.
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"""
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self._checkpoint_dir = checkpoint_dir
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if not os.path.isdir(self._checkpoint_dir):
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os.mkdir(self._checkpoint_dir)
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self._checkpoint_path = os.path.join(self._checkpoint_dir, filename)
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def save_checkpoint(
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self,
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experiment_state: Mapping[str, jnp.ndarray],
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opt_state: Mapping[str, jnp.ndarray],
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step: int,
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extra_checkpoint_info: Optional[Mapping[str, Any]] = None) -> None:
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"""Save checkpoint with experiment state and step information.
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Args:
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experiment_state: Experiment params to be stored.
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opt_state: Optimizer state to be stored.
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step: Training iteration step.
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extra_checkpoint_info: Extra information to be stored.
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"""
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if jax.host_id() != 0:
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return
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checkpoint_data = dict(
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experiment_state=jax.tree_map(jax.device_get, experiment_state),
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opt_state=jax.tree_map(jax.device_get, opt_state),
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step=step)
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if extra_checkpoint_info is not None:
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for key in extra_checkpoint_info:
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checkpoint_data[key] = extra_checkpoint_info[key]
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with open(self._checkpoint_path, 'wb') as checkpoint_file:
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dill.dump(checkpoint_data, checkpoint_file, protocol=2)
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def load_checkpoint(
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self) -> Optional[Mapping[str, Mapping[str, jnp.ndarray]]]:
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"""Load and return checkpoint data.
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Returns:
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Loaded checkpoint if it exists else returns None.
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"""
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if os.path.exists(self._checkpoint_path):
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with open(self._checkpoint_path, 'rb') as checkpoint_file:
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checkpoint_data = dill.load(checkpoint_file)
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logging.info('Loading checkpoint from %s, saved at step %d',
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self._checkpoint_path, checkpoint_data['step'])
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return checkpoint_data
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else:
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logging.warning('No pre-saved checkpoint found at %s',
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self._checkpoint_path)
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return None
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