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66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
# Copyright 2019 Deepmind Technologies Limited.
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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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"""Trains a graph-based network to predict particle mobilities in glasses."""
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import os
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from absl import app
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from absl import flags
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from glassy_dynamics import train as train_using_tf
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from glassy_dynamics import train_using_jax
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FLAGS = flags.FLAGS
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flags.DEFINE_string(
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'data_directory',
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'',
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'Directory which contains the train and test datasets.')
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flags.DEFINE_integer(
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'time_index',
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9,
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'The time index of the target mobilities.')
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flags.DEFINE_integer(
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'max_files_to_load',
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None,
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'The maximum number of files to load from the train and test datasets.')
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flags.DEFINE_string(
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'checkpoint_path',
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None,
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'Path used to store a checkpoint of the best model.')
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flags.DEFINE_boolean(
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'use_jax',
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False,
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'Uses jax to train model.')
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def main(argv):
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if len(argv) > 1:
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raise app.UsageError('Too many command-line arguments.')
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train_file_pattern = os.path.join(FLAGS.data_directory, 'train/aggregated*')
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test_file_pattern = os.path.join(FLAGS.data_directory, 'test/aggregated*')
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train = train_using_jax if FLAGS.use_jax else train_using_tf
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train.train_model(
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train_file_pattern=train_file_pattern,
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test_file_pattern=test_file_pattern,
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max_files_to_load=FLAGS.max_files_to_load,
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time_index=FLAGS.time_index,
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checkpoint_path=FLAGS.checkpoint_path)
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if __name__ == '__main__':
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app.run(main)
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