code: def testLoss(self, agent_class, use_num_samples_list):
      reward_net = DummyNet(self._observation_spec, self._action_spec)
      observations = np.array([[1, 2], [3, 4]], dtype=np.float32)
      actions = np.array([0, 1], dtype=np.int32)
      rewards = np.array([0.5, 3.0], dtype=np.float32)
      (
          initial_step,
          final_step,
      ) = _get_initial_and_final_steps_nested_rewards(
          observations, rewards
      )
      action_step = _get_action_step(actions)
      experience = _get_experience(
          initial_step, action_step, final_step
      )
  
      if use_num_samples_list:
          agent_class = functools.partial(
              agent_class, num_samples_list=self._num_samples_list
          )
  
      agent = agent_class(
          self._time_step_spec,
          self._action_spec,
          reward_network=reward_net,
          optimizer=None,
      )
      init_op = agent.initialize()
      if not tf.executing_eagerly():
          with self.cached_session() as sess:
              common.initialize_uninitialized_variables(sess)
              self.assertIsNone(sess.run(init_op))
      loss, _ = agent._loss(experience)
      self.evaluate(tf.compat.v1.initialize_all_variables())
      self.assertAllClose(self.evaluate(loss), 42.25)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.bandits.agents import greedy_reward_prediction_agent
  from tf_agents.bandits.agents import neural_boltzmann_agent
  from tf_agents.bandits.agents import neural_epsilon_greedy_agent
  from tf_agents.bandits.agents import neural_falcon_agent
  from tf_agents.bandits.drivers import driver_utils
  from tf_agents.bandits.networks import global_and_arm_feature_network
  from tf_agents.bandits.policies import constraints
  from tf_agents.bandits.specs import utils
  from tf_agents.networks import network
  from tf_agents.policies import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
label_desc: Use image node_id 4 for calling the AgentTest obj's underlying member method code with example usage: obj.testLoss(agent_class, use_num_samples_list) without return types