code: def testAssignSession(self, batch_size):
      if tf.executing_eagerly():
          self.skipTest(
              "b/123770140: Handling sessions with eager mode is buggy"
          )
  
      policy = py_tf_policy.PyTFPolicy(self._tf_policy)
      policy.session = tf.compat.v1.Session()
      expected_initial_state = np.zeros(
          [batch_size or 1, 1], dtype=np.float32
      )
      self.assertTrue(
          np.array_equal(
              policy.get_initial_state(batch_size),
              expected_initial_state,
          )
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import flags
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.networks import network
  from tf_agents.policies import actor_policy
  from tf_agents.policies import ou_noise_policy
  from tf_agents.policies import py_tf_policy
  from tf_agents.policies import q_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 4 for calling the PyTFPolicyTest obj's underlying member method code with example usage: obj.testAssignSession(batch_size) without return types