code: def testTrainAgent(self):
      observations = np.array([[1, 1]], dtype=np.float32)
      actions = np.array([0, 1], dtype=np.int32)
      rewards = np.array([0.0, 1.0], dtype=np.float32)
      initial_step, final_step = _get_initial_and_final_steps(
          observations, rewards
      )
      action_step = _get_action_step(actions)
      experience = _get_experience(
          initial_step, action_step, final_step
      )
  
      agent = bern_ts_agent.BernoulliThompsonSamplingAgent(
          self._time_step_spec, self._action_spec, batch_size=2
      )
      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._train(experience, weights=None)
      self.evaluate(tf.compat.v1.initialize_all_variables())
      # The loss is -sum(rewards).
      self.assertAllClose(self.evaluate(loss), -1.0)
  
imports: import numpy
  import tensorflow
  from tf_agents.bandits.agents import bernoulli_thompson_sampling_agent
  from tf_agents.bandits.drivers import driver_utils
  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 5 for calling the AgentTest obj's underlying member method code with example usage: obj.testTrainAgent() without return types