mlp_mnist_main.py revision aaac4ac3e9d1d8c48db9e4010459a417a07553d2 
1# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7#     http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ==============================================================================
15r"""Train an MLP on MNIST using K-FAC.
16
17See mlp.py for details.
18"""
19
20from __future__ import absolute_import
21from __future__ import division
22from __future__ import print_function
23
24import argparse
25import sys
26
27import tensorflow as tf
28
29from tensorflow.contrib.kfac.examples import mlp
30
31FLAGS = None
32
33
34def main(argv):
35  _ = argv
36  if FLAGS.use_estimator:
37    if FLAGS.num_towers != 1:
38      raise ValueError("Only 1 device supported in tf.estimator example.")
39    mlp.train_mnist_estimator(FLAGS.data_dir, num_epochs=200)
40  elif FLAGS.num_towers > 1:
41    mlp.train_mnist_multitower(
42        FLAGS.data_dir, num_epochs=200, num_towers=FLAGS.num_towers)
43  else:
44    mlp.train_mnist(FLAGS.data_dir, num_epochs=200)
45
46
47if __name__ == "__main__":
48  parser = argparse.ArgumentParser()
49  parser.add_argument(
50      "--data_dir",
51      type=str,
52      default="/tmp/mnist",
53      help="Directory to store dataset in.")
54  parser.add_argument(
55      "--num_towers",
56      type=int,
57      default=1,
58      help="Number of CPUs to split minibatch across.")
59  parser.add_argument(
60      "--use_estimator",
61      action="store_true",
62      help="Use tf.estimator API to train.")
63  FLAGS, unparsed = parser.parse_known_args()
64  tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
65