code: def testLossWithL2Regularization(self, agent_class):
      q_net = DummyNet(
          self._observation_spec,
          self._action_spec,
          l2_regularization_weight=1.0,
      )
      agent = agent_class(
          self._time_step_spec,
          self._action_spec,
          q_network=q_net,
          optimizer=None,
      )
  
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_steps = ts.restart(observations, batch_size=2)
  
      actions = tf.constant([0, 1], dtype=tf.int32)
      action_steps = policy_step.PolicyStep(actions)
  
      rewards = tf.constant([10, 20], dtype=tf.float32)
      discounts = tf.constant([0.9, 0.9], dtype=tf.float32)
      next_observations = tf.constant(
          [[5, 6], [7, 8]], dtype=tf.float32
      )
      next_time_steps = ts.transition(
          next_observations, rewards, discounts
      )
  
      experience = (
          trajectories_test_utils.stacked_trajectory_from_transition(
              time_steps, action_steps, next_time_steps
          )
      )
  
      # See the loss explanation in testLoss above.
      # L2_regularization_loss: 2^2 + 1^2 + 1^2 + 1^2 = 7.0
      # Overall loss: 26.0 (from testLoss) + 7.0 = 33.0
      expected_loss = 33.0
      loss, _ = agent._loss(experience)
  
      self.evaluate(tf.compat.v1.initialize_all_variables())
      self.assertAllClose(self.evaluate(loss), expected_loss)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import tensorflow
  from tf_agents.agents.dqn import dqn_agent
  from tf_agents.networks import network
  from tf_agents.networks import q_network
  from tf_agents.networks import sequential
  from tf_agents.networks import test_utils
  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
  from tf_agents.utils import test_utils
label_desc: Use image node_id 10 for calling the DqnAgentTest obj's underlying member method code with example usage: obj.testLossWithL2Regularization(agent_class) without return types