code: def testTrainWithRnnTransitions(self):
      actor_net = (
          actor_distribution_rnn_network.ActorDistributionRnnNetwork(
              self._obs_spec,
              self._action_spec,
              input_fc_layer_params=None,
              output_fc_layer_params=None,
              conv_layer_params=None,
              lstm_size=(40,),
          )
      )
  
      counter = common.create_variable("test_train_counter")
      agent = reinforce_agent.ReinforceAgent(
          self._time_step_spec,
          self._action_spec,
          actor_network=actor_net,
          optimizer=tf.compat.v1.train.AdamOptimizer(0.001),
          train_step_counter=counter,
      )
  
      batch_size = 5
      observations = tf.constant(
          [[[1, 2], [3, 4], [5, 6]]] * batch_size, dtype=tf.float32
      )
      time_steps = ts.TimeStep(
          step_type=tf.constant(
              [[1, 1, 1]] * batch_size, dtype=tf.int32
          ),
          reward=tf.constant([[1] * 3] * batch_size, dtype=tf.float32),
          discount=tf.constant(
              [[1] * 3] * batch_size, dtype=tf.float32
          ),
          observation=observations,
      )
      actions = policy_step.PolicyStep(
          tf.constant([[[0], [1], [1]]] * batch_size, dtype=tf.float32)
      )
      next_time_steps = ts.TimeStep(
          step_type=tf.constant(
              [[1, 1, 2]] * batch_size, dtype=tf.int32
          ),
          reward=tf.constant([[1] * 3] * batch_size, dtype=tf.float32),
          discount=tf.constant(
              [[1] * 3] * batch_size, dtype=tf.float32
          ),
          observation=observations,
      )
  
      experience = trajectory.Transition(
          time_steps, actions, next_time_steps
      )
  
      agent.initialize()
      agent.train(experience)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  from absl.testing.absltest import mock
  import tensorflow
  import tensorflow_probability
  from tf_agents.agents.reinforce import reinforce_agent
  from tf_agents.networks import actor_distribution_rnn_network
  from tf_agents.networks import network
  from tf_agents.networks 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.trajectories import trajectory
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 22 for calling the ReinforceAgentTest obj's underlying member method code with example usage: obj.testTrainWithRnnTransitions() without return types