code: def testCriticLoss(self):
      agent = categorical_dqn_agent.CategoricalDqnAgent(
          self._time_step_spec,
          self._action_spec,
          self._dummy_categorical_net,
          self._optimizer,
      )
  
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_steps = ts.restart(observations, batch_size=2)
  
      actions = tf.constant([0, 1], dtype=tf.int32)
      action_steps = policy_step.PolicyStep(actions)
  
      rewards = tf.constant([10, 20], dtype=tf.float32)
      discounts = tf.constant([0.9, 0.9], dtype=tf.float32)
      next_observations = tf.constant(
          [[5, 6], [7, 8]], dtype=tf.float32
      )
      next_time_steps = ts.transition(
          next_observations, rewards, discounts
      )
  
      experience = test_utils.stacked_trajectory_from_transition(
          time_steps, action_steps, next_time_steps
      )
  
      # Due to the constant initialization of the DummyCategoricalNet, we can
      # expect the same loss every time.
      expected_loss = 2.19525
      loss_info = agent._loss(experience)
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      evaluated_loss = self.evaluate(loss_info).loss
      self.assertAllClose(evaluated_loss, expected_loss, atol=1e-4)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tf_agents.agents.categorical_dqn import categorical_dqn_agent
  from tf_agents.networks import categorical_q_network
  from tf_agents.networks import network
  from tf_agents.networks import q_rnn_network
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import test_utils
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
label_desc: Use image node_id 7 for calling the CategoricalDqnAgentTest obj's underlying member method code with example usage: obj.testCriticLoss() without return types