code: def _create_test_agent(self, sess):
      stack_size = self.stack_size
  
      class MockDQNNetwork(tf.keras.Model):
          """The Keras network used in tests."""
  
          def __init__(self, num_actions, **kwargs):
              # This weights_initializer gives action 0 a higher weight, ensuring
              # that it gets picked by the argmax.
              super(MockDQNNetwork, self).__init__(**kwargs)
              weights_initializer = np.tile(
                  np.arange(num_actions, 0, -1), (stack_size, 1)
              )
              self.layer = tf.keras.layers.Dense(
                  num_actions,
                  kernel_initializer=tf.constant_initializer(
                      weights_initializer
                  ),
                  bias_initializer=tf.ones_initializer(),
              )
  
          def call(self, state):
              inputs = tf.constant(
                  np.zeros((state.shape[0], stack_size)),
                  dtype=tf.float32,
              )
              return atari_lib.DQNNetworkType(self.layer((inputs)))
  
      agent = dopamine_connector.BatchDQNAgent(
          network=MockDQNNetwork,
          replay_capacity=100,
          buffer_batch_size=8,
          generates_trainable_dones=True,
          sess=sess,
          env_batch_size=self.env_batch_size,
          num_actions=self.num_actions,
          min_replay_history=self.min_replay_history,
          epsilon_fn=lambda w, x, y, z: 0.0,  # No exploration.
          update_period=self.update_period,
          target_update_period=self.target_update_period,
          epsilon_eval=0.0,
      )  # No exploration during evaluation.
      # This ensures non-random action choices (since epsilon_eval = 0.0) and
      # skips the train_step.
      agent.eval_mode = True
      sess.run(tf.global_variables_initializer())
      return agent
  
file_path: tensor2tensor/tensor2tensor/rl/batch_dqn_agent_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import shutil
  from absl import flags
  from dopamine.agents.dqn import dqn_agent
  from dopamine.discrete_domains import atari_lib
  import numpy
  from tensor2tensor.rl import dopamine_connector
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the BatchDQNAgentTest obj's underlying member method code with example usage: obj._create_test_agent(sess) and returns: agent, atari_lib