text: # coding=utf-8
  # Copyright 2018 The TF-Agents Authors.
  #
  # 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.
  
  """Tests for tf_agents.agents.dqn.examples.v2.train_eval."""
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  from absl import flags
  import tensorflow as tf  # pylint: disable=g-explicit-tensorflow-version-import
  
  from tf_agents.agents.dqn.examples.v2 import train_eval
  
  FLAGS = flags.FLAGS
  
  
  class TrainEval(tf.test.TestCase):
  
    def testDQNCartPole(self):
      if not tf.executing_eagerly():
        self.skipTest('Binary is eager-only.')
  
      root_dir = self.get_temp_dir()
      train_loss = train_eval.train_eval(root_dir,
                                         num_iterations=1,
                                         num_eval_episodes=1,
                                         initial_collect_steps=10)
      self.assertGreater(train_loss.loss, 0.0)
  
    def testRNNDQNMaskedCartPole(self):
      if not tf.executing_eagerly():
        self.skipTest('Binary is eager-only.')
  
      root_dir = self.get_temp_dir()
      train_loss = train_eval.train_eval(
          root_dir,
          env_name='MaskedCartPole-v0',
          train_sequence_length=2,
          initial_collect_steps=10,
          num_eval_episodes=1,
          num_iterations=1)
      self.assertGreater(train_loss.loss, 0.0)
  
  if __name__ == '__main__':
    tf.compat.v1.enable_v2_behavior()
    tf.test.main()
  