91 lines
3.7 KiB
Python
91 lines
3.7 KiB
Python
#
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# Copyright (c) 2018, The Board of Trustees of the Leland Stanford Junior University
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# * Redistributions of source code must retain the above copyright notice, this
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# list of conditions and the following disclaimer.
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#
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# * Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# * Neither the name of the copyright holder nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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'''
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Created on Mar 3, 2019
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@author: gcampagn
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'''
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import torch
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import ujson as json
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import os
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import logging
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logger = logging.getLogger(__name__)
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class Saver(object):
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'''
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Wrap pytorch's save functionality into an interface similar to tensorflow.train.Saver
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In particular, this class takes care of automatically cleaning up old checkpoints,
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and creating checkpoint files to keep track of which saves are valid and which are not.
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'''
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def __init__(self, savedir, max_to_keep=5):
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self._savedir = savedir
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self._max_to_keep = max_to_keep
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assert max_to_keep >= 1
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self._loaded_last_checkpoints = False
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self._latest_checkpoint = None
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self._all_checkpoints = None
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def _maybe_load_last_checkpoints(self):
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if self._loaded_last_checkpoints:
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return
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try:
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with open(os.path.join(self._savedir, 'checkpoint.json')) as fp:
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data = json.load(fp)
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self._loaded_last_checkpoints = True
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self._all_checkpoints = data['all']
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self._latest_checkpoint = data['latest']
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except FileNotFoundError:
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self._loaded_last_checkpoints = True
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self._all_checkpoints = []
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self._latest_checkpoint = None
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def save(self, save_dict, global_step):
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self._maybe_load_last_checkpoints()
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filename = 'iteration_' + str(global_step) + '.pth'
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abspath = os.path.join(self._savedir, filename)
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self._latest_checkpoint = filename
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self._all_checkpoints.append(filename)
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if len(self._all_checkpoints) > self._max_to_keep:
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try:
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todelete = self._all_checkpoints.pop(0)
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os.unlink(os.path.join(self._savedir, todelete))
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except (OSError, IOError) as e:
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logging.warn('Failed to delete old checkpoint: %s', e)
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torch.save(save_dict, abspath)
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with open(os.path.join(self._savedir, 'checkpoint.json'), 'w') as fp:
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json.dump(dict(all=self._all_checkpoints, latest=self._latest_checkpoint), fp)
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