code: def testOneStepUpdatesObservers(self):
      env = tf_py_environment.TFPyEnvironment(
          driver_test_utils.PyEnvironmentMock()
      )
      policy = driver_test_utils.TFPolicyMock(
          env.time_step_spec(), env.action_spec()
      )
      num_episodes_observer = driver_test_utils.NumEpisodesObserver()
      num_steps_observer = driver_test_utils.NumStepsObserver()
      num_steps_transition_observer = (
          driver_test_utils.NumStepsTransitionObserver()
      )
  
      driver = dynamic_episode_driver.DynamicEpisodeDriver(
          env,
          policy,
          observers=[num_episodes_observer, num_steps_observer],
          transition_observers=[num_steps_transition_observer],
      )
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      for _ in range(5):
          self.evaluate(driver.run())
  
      self.assertEqual(
          self.evaluate(num_episodes_observer.num_episodes), 5
      )
      # Two steps per episode.
      self.assertEqual(self.evaluate(num_steps_observer.num_steps), 10)
      self.assertEqual(
          self.evaluate(num_steps_transition_observer.num_steps), 10
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tf_agents.bandits.environments import environment_utilities
  from tf_agents.bandits.environments import stationary_stochastic_py_environment
  from tf_agents.drivers import dynamic_episode_driver
  from tf_agents.drivers import test_utils
  from tf_agents.environments import tf_py_environment
  from tf_agents.policies import random_tf_policy
  from tf_agents.replay_buffers import tf_uniform_replay_buffer
  from tf_agents.utils import test_utils
label_desc: Use image node_id 3 for calling the DynamicEpisodeDriverTest obj's underlying member method code with example usage: obj.testOneStepUpdatesObservers() without return types