code: def testAgentAndEnvironmentRuns(self, environment_name, agent_name):
      batch_size = 8
      training_loops = 3
      steps_per_loop = 2
      (
          environment,
          optimal_reward_fn,
          optimal_action_fn,
      ) = trainer_test_utils.get_environment_and_optimal_functions_by_name(
          environment_name, batch_size
      )
  
      agent = trainer_test_utils.get_agent_by_name(
          agent_name,
          environment.time_step_spec(),
          environment.action_spec(),
      )
  
      regret_metric = tf_bandit_metrics.RegretMetric(optimal_reward_fn)
      suboptimal_arms_metric = tf_bandit_metrics.SuboptimalArmsMetric(
          optimal_action_fn
      )
      with mock.patch.object(
          export_utils, "logging", new_callable=MockLog
      ) as mock_logging:
          trainer.train(
              root_dir=tempfile.mkdtemp(dir=os.getenv("TEST_TMPDIR")),
              agent=agent,
              environment=environment,
              training_loops=training_loops,
              steps_per_loop=steps_per_loop,
              additional_metrics=[
                  regret_metric,
                  suboptimal_arms_metric,
              ],
          )
      logged = mock_logging.as_string()
      self.assertEqual(logged.count("RegretMetric"), training_loops)
      self.assertEqual(
          logged.count("SuboptimalArmsMetric"), training_loops
      )
      self.assertEqual(logged.count("loss"), training_loops)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import os
  import tempfile
  from unittest import mock
  from absl import logging
  from absl.testing import parameterized
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.agents import exp3_agent
  from tf_agents.bandits.agents.examples.v2 import trainer
  from tf_agents.bandits.agents.examples.v2 import trainer_test_utils
  from tf_agents.bandits.environments import environment_utilities
  from tf_agents.bandits.environments import random_bandit_environment
  from tf_agents.bandits.environments import stationary_stochastic_py_environment
  from tf_agents.bandits.environments import wheel_py_environment
  from tf_agents.bandits.metrics import tf_metrics
  from tf_agents.environments import tf_py_environment
  from tf_agents.metrics import export_utils
  from tf_agents.specs import tensor_spec
label_desc: Use image node_id 2 for calling the TrainerTest obj's underlying member method code with example usage: obj.testAgentAndEnvironmentRuns(environment_name, agent_name) without return types