b08a142edf180325b63441ec1b71119c393c4a64,tf_agents/metrics/tf_metrics_test.py,TFMetricsTest,testMetric,#TFMetricsTest#Any#Any#Any#Any#,149

Before Change

    with run_mode():
      trajectories = self._create_trajectories()
      metric = metric_class()
      deps = []
      self.evaluate(metric.init_variables())
      for i in range(num_trajectories):
        with tf.control_dependencies(deps):
          traj = metric(trajectories[i])
          deps = tf.nest.flatten(traj)
      with tf.control_dependencies(deps):
        result = metric.result()
      result_ = self.evaluate(result)
      self.assertEqual(result_, expected_result)

After Change

                 expected_result):
    with run_mode():
      trajectories = self._create_trajectories()
      if metric_class in [tf_metrics.AverageReturnMetric,
                          tf_metrics.AverageEpisodeLengthMetric]:
        metric = metric_class(batch_size=2)
      else:
        metric = metric_class()
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(metric.init_variables())
      for i in range(num_trajectories):
        self.evaluate(metric(trajectories[i]))

Instances