code: def testPolicy(self):
      agent = categorical_dqn_agent.CategoricalDqnAgent(
          self._time_step_spec,
          self._action_spec,
          self._categorical_net,
          self._optimizer,
      )
  
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_steps = ts.restart(observations, batch_size=2)
      actions, _, _ = agent.policy.action(time_steps)
      self.assertEqual(actions.shape, [2])
      self.evaluate(tf.compat.v1.global_variables_initializer())
      actions_ = self.evaluate(actions)
      self.assertTrue(all(actions_ <= self._action_spec.maximum))
      self.assertTrue(all(actions_ >= self._action_spec.minimum))
  
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 10 for calling the CategoricalDqnAgentTest obj's underlying member method code with example usage: obj.testPolicy() without return types