code: def test_update_and_wait(self):
      # Create a variable source (emulating the learner).
      np_learner_variables = tf2_utils.to_numpy(
          self._learner_model.variables
      )
      variable_source = fakes.VariableSource(np_learner_variables)
  
      # Create a variable client (emulating the actor).
      variable_client = tf2_variable_utils.VariableClient(
          variable_source, {"policy": self._actor_model.variables}
      )
  
      # Create some random batch of test input:
      x = tf.random.normal(shape=(_BATCH_SIZE, _INPUT_SIZE))
  
      # Before copying variables, the models have different outputs.
      self.assertNotAllClose(
          self._actor_model(x), self._learner_model(x)
      )
  
      # Update the variable client.
      variable_client.update_and_wait()
  
      # After copying variables (by updating the client), the models are the same.
      self.assertAllClose(self._actor_model(x), self._learner_model(x))
  
file_path: acme/acme/tf/variable_utils_test.py
imports: import threading
  from acme.testing import fakes
  from acme.tf import utils
  from acme.tf import variable_utils
  import sonnet
  import tensorflow
label_desc: Use image node_id 2 for calling the VariableClientTest obj's underlying member method code with example usage: obj.test_update_and_wait() without return types