code: def testPolicy(self, agent_class):
      q_net = DummyNet(self._observation_spec, self._action_spec)
      agent = agent_class(
          self._time_step_spec,
          self._action_spec,
          q_network=q_net,
          optimizer=None,
      )
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_steps = ts.restart(observations, batch_size=2)
      policy = agent.policy
      action_step = policy.action(time_steps)
      # Batch size 2.
      self.assertAllEqual(
          action_step.action.shape,
          [2] + self._action_spec.shape.as_list(),
      )
      self.evaluate(tf.compat.v1.global_variables_initializer())
      actions_ = self.evaluate(action_step.action)
      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
  from absl.testing import parameterized
  import tensorflow
  from tf_agents.agents.dqn import dqn_agent
  from tf_agents.networks import network
  from tf_agents.networks import q_network
  from tf_agents.networks import sequential
  from tf_agents.networks import test_utils
  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
  from tf_agents.utils import test_utils
label_desc: Use image node_id 15 for calling the DqnAgentTest obj's underlying member method code with example usage: obj.testPolicy(agent_class) without return types