code: def testAlphaLoss(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,
          target_entropy=3.0,
          initial_log_alpha=4.0,
          actor_policy_ctor=DummyActorPolicy,
      )
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_steps = ts.restart(observations, batch_size=2)
  
      expected_loss = 4.0 * (-10 - 3)
      loss = agent.alpha_loss(time_steps)
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      loss_ = self.evaluate(loss)
      self.assertAllClose(loss_, expected_loss)
  
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 8 for calling the SacAgentTest obj's underlying member method code with example usage: obj.testAlphaLoss() without return types