text: # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
  #
  # 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.
  # ==============================================================================
  r"""Train a ConvNet on MNIST using K-FAC.
  
  See convnet.py for details.
  """
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import argparse
  import sys
  
  import tensorflow as tf
  
  from tensorflow.contrib.kfac.examples import convnet
  
  FLAGS = None
  
  
  def main(argv):
    _ = argv
  
    if FLAGS.num_towers > 1:
      convnet.train_mnist_multitower(
          FLAGS.data_dir, num_epochs=200, num_towers=FLAGS.num_towers)
    else:
      convnet.train_mnist_single_machine(FLAGS.data_dir, num_epochs=200)
  
  
  if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--data_dir",
        type=str,
        default="/tmp/mnist",
        help="Directory to store dataset in.")
    parser.add_argument(
        "--num_towers",
        type=int,
        default=1,
        help="Number of CPUs to split minibatch across.")
    FLAGS, unparsed = parser.parse_known_args()
    tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
  