code: def testLoss(self):
      cloning_net = get_dummy_net(self._action_spec)
      agent = behavioral_cloning_agent.BehavioralCloningAgent(
          self._time_step_spec,
          self._action_spec,
          cloning_network=cloning_net,
          optimizer=tf.compat.v1.train.AdamOptimizer(
              learning_rate=0.001
          ),
      )
  
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      actions = tf.constant([0, 1], dtype=tf.int32)
      rewards = tf.constant([10, 20], dtype=tf.float32)
      discounts = tf.constant([0.9, 0.9], dtype=tf.float32)
  
      experience = trajectory.first(
          observation=observations,
          action=actions,
          policy_info=(),
          reward=rewards,
          discount=discounts,
      )
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
  
      expected_loss = tf.reduce_mean(
          input_tensor=tf.nn.sparse_softmax_cross_entropy_with_logits(
              labels=actions, logits=cloning_net(observations)[0]
          )
      )
  
      loss_info = agent.train(experience)
      total_loss = self.evaluate(loss_info.loss)
  
      self.assertAllClose(total_loss, expected_loss)
  
      test_util.test_loss_and_train_output(
          test=self,
          expect_equal_loss_values=True,
          agent=agent,
          experience=experience,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.agents import test_util
  from tf_agents.agents.behavioral_cloning import behavioral_cloning_agent
  from tf_agents.keras_layers import inner_reshape
  from tf_agents.networks import expand_dims_layer
  from tf_agents.networks import q_network
  from tf_agents.networks import q_rnn_network
  from tf_agents.networks import sequential
  from tf_agents.specs import tensor_spec
  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 7 for calling the BehavioralCloningAgentTest obj's underlying member method code with example usage: obj.testLoss() without return types