code: def testPolicyGradientLossMultipleEpisodes(self):
      agent = reinforce_agent.ReinforceAgent(
          self._time_step_spec,
          self._action_spec,
          actor_network=DummyActorNet(
              self._obs_spec, self._action_spec, unbounded_actions=True
          ),
          optimizer=None,
      )
  
      step_type = tf.constant(
          [
              ts.StepType.FIRST,
              ts.StepType.LAST,
              ts.StepType.FIRST,
              ts.StepType.LAST,
          ]
      )
      reward = tf.constant([0, 0, 0, 0], dtype=tf.float32)
      discount = tf.constant([1, 1, 1, 1], dtype=tf.float32)
      observations = tf.constant(
          [[1, 2], [1, 2], [1, 2], [1, 2]], dtype=tf.float32
      )
      time_steps = ts.TimeStep(
          step_type, reward, discount, observations
      )
  
      actions = tf.constant([[0], [1], [2], [3]], dtype=tf.float32)
      actions_distribution = agent.collect_policy.distribution(
          time_steps
      ).action
      returns = tf.constant([1.9, 1.9, 1.0, 1.0], dtype=tf.float32)
  
      expected_loss = 5.140229225158691
      loss = agent.policy_gradient_loss(
          actions_distribution,
          actions,
          time_steps.is_last(),
          returns,
          2,
      )
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      loss_ = self.evaluate(loss)
      self.assertAllClose(loss_, expected_loss)
  
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 5 for calling the ReinforceAgentTest obj's underlying member method code with example usage: obj.testPolicyGradientLossMultipleEpisodes() without return types