code: def testGetInitialPolicyState(self, stateful):
      if tf.test.is_built_with_gpu_support():  # b/237573967
          self.skipTest("Test is only applicable on GPU")
      agent = reinforce_agent.ReinforceAgent(
          self._time_step_spec,
          self._action_spec,
          actor_network=DummyActorNet(
              self._obs_spec,
              self._action_spec,
              unbounded_actions=False,
              stateful=stateful,
          ),
          optimizer=None,
      )
      observations = tf.constant([[1, 2]], dtype=tf.float32)
      time_steps = ts.restart(observations, batch_size=3)
      initial_state = reinforce_agent._get_initial_policy_state(
          agent.collect_policy, time_steps
      )
      if stateful:
          self.assertAllEqual(
              self.evaluate(initial_state),
              self.evaluate(tf.zeros((3, 2), dtype=tf.float32)),
          )
      else:
          self.assertEqual(initial_state, ())
  
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 20 for calling the ReinforceAgentTest obj's underlying member method code with example usage: obj.testGetInitialPolicyState(stateful) without return types