code: def VerifyVariableAssignAndRestore(self):
      strategy = tf.distribute.get_strategy()
      with strategy.scope():
          # Use BehaviorCloningAgent instead of AWRAgent to test the network.
          q_net = critic_network.CriticNetwork(
              (self._observation_spec, self._action_spec)
          )
          agent = qtopt_agent.QtOptAgent(
              self._time_step_spec,
              self._action_spec,
              q_network=q_net,
              optimizer=None,
              init_mean_cem=self._mean,
              init_var_cem=self._var,
              num_samples_cem=self._num_samples,
              actions_sampler=self._sampler,
          )
      # Assign all vars to 0.
      for var in tf.nest.flatten(agent.variables):
          var.assign(tf.zeros_like(var))
      # Save checkpoint
      ckpt_dir = self.create_tempdir()
      checkpointer = common.Checkpointer(ckpt_dir=ckpt_dir, agent=agent)
      global_step = tf.constant(0)
      checkpointer.save(global_step)
      # Assign all vars to 1.
      for var in tf.nest.flatten(agent.variables):
          var.assign(tf.ones_like(var))
      # Restore to 0.
      checkpointer._checkpoint.restore(
          checkpointer._manager.latest_checkpoint
      )
      for var in tf.nest.flatten(agent.variables):
          value = var.numpy()
          if isinstance(value, np.int64):
              self.assertEqual(value, 0)
          else:
              self.assertAllEqual(
                  value,
                  np.zeros_like(value),
                  msg="{} has var mean {}, expected 0.".format(
                      var.name, value
                  ),
              )
  
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.agents.ddpg import critic_network
  from tf_agents.agents.qtopt import qtopt_agent
  from tf_agents.networks import network
  from tf_agents.policies.samplers import qtopt_cem_actions_sampler_continuous
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import test_utils
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
label_desc: Use image node_id 6 for calling the QtoptAgentTest obj's underlying member method code with example usage: obj.VerifyVariableAssignAndRestore() without return types