code: def testUpdate(self):
      policy = q_policy.QPolicy(
          self._time_step_spec, self._action_spec, q_network=DummyNet()
      )
      new_policy = q_policy.QPolicy(
          self._time_step_spec, self._action_spec, q_network=DummyNet()
      )
      self.assertEqual(len(policy.variables()), 2)
      self.assertEqual(len(new_policy.variables()), 2)
  
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_step = ts.restart(observations, batch_size=2)
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.assertEqual(self.evaluate(new_policy.update(policy)), None)
  
      distribution = policy.distribution(time_step).action.parameters
      new_distribution = new_policy.distribution(
          time_step
      ).action.parameters
      self.assertAllEqual(
          self.evaluate(distribution["logits"]),
          self.evaluate(new_distribution["logits"]),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tf_agents.networks import network
  from tf_agents.networks import q_network
  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 9 for calling the QPolicyTest obj's underlying member method code with example usage: obj.testUpdate() without return types