code: def test_get_initial_state(self, multithreading, num_policies):
      policy = self._make_batched_py_policy(
          multithreading, num_policies=num_policies
      )
      policy_state = policy.get_initial_state()
      # Expect policy_state.shape[0] to be batch_size aka num_policies.
      # The remaining dimensions should match the policy_state_spec.
      correct_shape = (num_policies,) + self.policy_state_spec.shape
      self.assertEqual(correct_shape, policy_state.shape)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.policies import batched_py_policy
  from tf_agents.policies import py_policy
  from tf_agents.specs import array_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
label_desc: Use image node_id 7 for calling the BatchedPyPolicyTest obj's underlying member method code with example usage: obj.test_get_initial_state(multithreading, num_policies) without return types