code: def testUpdate(self):
      tf.compat.v1.set_random_seed(1)
      actor_network = DummyActionNet(self._obs_spec, self._action_spec)
      policy = actor_policy.ActorPolicy(
          self._time_step_spec,
          self._action_spec,
          actor_network=actor_network,
      )
      self.assertLen(policy.variables(), 2)
      new_policy = actor_policy.ActorPolicy(
          self._time_step_spec,
          self._action_spec,
          actor_network=actor_network,
      )
  
      action_step = policy.action(self._time_step_batch)
      self.assertLen(policy.variables(), 2)
      new_action_step = new_policy.action(self._time_step_batch)
      self.assertLen(new_policy.variables(), 2)
  
      self.assertEqual(
          action_step.action.shape, new_action_step.action.shape
      )
      self.assertEqual(
          action_step.action.dtype, new_action_step.action.dtype
      )
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(new_policy.update(policy))
      actions_, new_actions_ = self.evaluate(
          [action_step.action, new_action_step.action]
      )
      self.assertAllEqual(actions_, new_actions_)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import network
  from tf_agents.policies import actor_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 6 for calling the ActorPolicyTest obj's underlying member method code with example usage: obj.testUpdate() without return types