code: def testSharedLayer(self):
      input_spec = (self._obs_spec, self._action_spec)
  
      shared_layer = tf.keras.layers.Dense(
          2,
          kernel_initializer=tf.constant_initializer([0]),
          bias_initializer=tf.constant_initializer([0]),
          name="shared",
      )
  
      critic_net_1 = DummyCriticNetwork(
          input_spec, shared_layer=shared_layer
      )
      critic_net_2 = DummyCriticNetwork(
          input_spec, shared_layer=shared_layer
      )
  
      bounded_actor_net = DummyActorNetwork(
          self._obs_spec,
          self._action_spec,
          shared_layer=shared_layer,
          unbounded_actions=False,
      )
  
      target_shared_layer = tf.keras.layers.Dense(
          2,
          kernel_initializer=tf.constant_initializer([0]),
          bias_initializer=tf.constant_initializer([0]),
          name="shared",
      )
  
      target_critic_net_1 = DummyCriticNetwork(
          input_spec, shared_layer=target_shared_layer
      )
      target_critic_net_2 = DummyCriticNetwork(
          input_spec, shared_layer=target_shared_layer
      )
      target_bounded_actor_net = DummyActorNetwork(
          self._obs_spec,
          self._action_spec,
          shared_layer=target_shared_layer,
          unbounded_actions=False,
      )
  
      agent = td3_agent.Td3Agent(
          self._time_step_spec,
          self._action_spec,
          actor_network=bounded_actor_net,
          critic_network=critic_net_1,
          critic_network_2=critic_net_2,
          target_actor_network=target_bounded_actor_net,
          target_critic_network=target_critic_net_1,
          target_critic_network_2=target_critic_net_2,
          actor_optimizer=None,
          critic_optimizer=None,
          target_update_tau=0.5,
      )
  
      self.evaluate(
          [
              tf.compat.v1.global_variables_initializer(),
              tf.compat.v1.local_variables_initializer(),
          ]
      )
  
      self.evaluate(agent.initialize())
  
      for v in shared_layer.variables:
          self.evaluate(v.assign(v * 0 + 1))
  
      self.evaluate(agent._update_target())
  
      self.assertEqual(
          1.0, self.evaluate(shared_layer.variables[0][0][0])
      )
      self.assertEqual(
          0.5, self.evaluate(target_shared_layer.variables[0][0][0])
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tf_agents.agents.td3 import td3_agent
  from tf_agents.networks import network
  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 TD3AgentTest obj's underlying member method code with example usage: obj.testSharedLayer() without return types