code: def testTrainAgentWithMask(self):
      time_step_spec = ts.time_step_spec(
          (
              tensor_spec.TensorSpec([], tf.float32),
              tensor_spec.TensorSpec([3], tf.int32),
          )
      )
      agent = bern_ts_agent.BernoulliThompsonSamplingAgent(
          time_step_spec, self._action_spec, batch_size=2
      )
      observations = (
          np.array([1, 1], dtype=np.float32),
          np.array([[0, 0, 1], [0, 0, 1]], dtype=np.int32),
      )
      actions = np.array([0, 1], dtype=np.int32)
      rewards = np.array([1.0, 0.0], dtype=np.float32)
      (
          initial_step,
          final_step,
      ) = _get_initial_and_final_steps_with_action_mask(
          observations, rewards
      )
      action_step = _get_action_step(actions)
      experience = _get_experience(
          initial_step, action_step, final_step
      )
      loss, _ = agent.train(experience, None)
      self.evaluate(tf.compat.v1.initialize_all_variables())
      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 6 for calling the AgentTest obj's underlying member method code with example usage: obj.testTrainAgentWithMask() without return types