9a3e9d21273da7ae40da9f70cb6df1b077b08105,tf_agents/networks/actor_distribution_network_test.py,ActorDistributionNetworkTest,testDropoutFCLayersWithConv,#ActorDistributionNetworkTest#Any#,117

Before Change

    mode2 = action_distributions2.mode()

    self.evaluate(tf.compat.v1.global_variables_initializer())
    mode1, mode2 = self.evaluate([mode1, mode2])

    if training:
      self.assertGreater(np.linalg.norm(mode1 - mode2), 0)
    else:

After Change

    modes = []
    num_modes = 10
    for _ in range(num_modes):
      action_distributions, _ = net(
          time_step.observation, time_step.step_type, (), training=training)
      modes.append(action_distributions.mode())

    self.evaluate(tf.compat.v1.global_variables_initializer())
    modes = self.evaluate(modes)

    modes_differ = False

Instances