Files
deepmind-research/glassy_dynamics/train_binary.py
Thomas Keck d78eee81f9 Adds JAX version of glassy dynamics training pipeline.
PiperOrigin-RevId: 348791013
2021-01-05 12:02:49 +00:00

66 lines
1.9 KiB
Python

# Copyright 2019 Deepmind Technologies Limited.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Trains a graph-based network to predict particle mobilities in glasses."""
import os
from absl import app
from absl import flags
from glassy_dynamics import train as train_using_tf
from glassy_dynamics import train_using_jax
FLAGS = flags.FLAGS
flags.DEFINE_string(
'data_directory',
'',
'Directory which contains the train and test datasets.')
flags.DEFINE_integer(
'time_index',
9,
'The time index of the target mobilities.')
flags.DEFINE_integer(
'max_files_to_load',
None,
'The maximum number of files to load from the train and test datasets.')
flags.DEFINE_string(
'checkpoint_path',
None,
'Path used to store a checkpoint of the best model.')
flags.DEFINE_boolean(
'use_jax',
False,
'Uses jax to train model.')
def main(argv):
if len(argv) > 1:
raise app.UsageError('Too many command-line arguments.')
train_file_pattern = os.path.join(FLAGS.data_directory, 'train/aggregated*')
test_file_pattern = os.path.join(FLAGS.data_directory, 'test/aggregated*')
train = train_using_jax if FLAGS.use_jax else train_using_tf
train.train_model(
train_file_pattern=train_file_pattern,
test_file_pattern=test_file_pattern,
max_files_to_load=FLAGS.max_files_to_load,
time_index=FLAGS.time_index,
checkpoint_path=FLAGS.checkpoint_path)
if __name__ == '__main__':
app.run(main)