code: def testPolicy(self):
      agent = sac_agent.SacAgent(
          self._time_step_spec,
          self._action_spec,
          critic_network=DummyCriticNet(),
          actor_network=None,
          actor_optimizer=None,
          critic_optimizer=None,
          alpha_optimizer=None,
          actor_policy_ctor=DummyActorPolicy,
      )
  
      observations = tf.constant([[1, 2]], dtype=tf.float32)
      time_steps = ts.restart(observations)
      action_step = agent.policy.action(time_steps)
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      action_ = self.evaluate(action_step.action)
      self.assertLessEqual(action_, self._action_spec.maximum)
      self.assertGreaterEqual(action_, self._action_spec.minimum)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import mock
  import tensorflow
  from tf_agents.agents import test_util
  from tf_agents.agents.ddpg import critic_rnn_network
  from tf_agents.agents.sac import sac_agent
  from tf_agents.agents.sac import tanh_normal_projection_network
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import actor_distribution_rnn_network
  from tf_agents.networks import nest_map
  from tf_agents.networks import network
  from tf_agents.networks import sequential
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 10 for calling the SacAgentTest obj's underlying member method code with example usage: obj.testPolicy() without return types