code: def _create_test_agent(self, allow_partial_reload=False):
      # This dummy network allows us to deterministically anticipate that
      # action 0 will be selected by an argmax.
      class MockDQNNetwork(nn.Module):
          """The Jax network used in tests."""
  
          num_actions: int
          inputs_preprocessed: bool = False
  
          @nn.compact
          def __call__(self, x):
              # This weights_initializer gives action 0 a higher weight, ensuring
              # that it gets picked by the argmax.
              def custom_init(key, shape, dtype=jnp.float32):
                  del key
                  to_pick_first_action = onp.zeros(shape, dtype)
                  to_pick_first_action[:, 0] = 1
                  return to_pick_first_action
  
              x = x.astype(jnp.float32)
              x = x.reshape((-1))  # flatten
              x = nn.Dense(
                  features=self.num_actions,
                  kernel_init=custom_init,
                  bias_init=nn.initializers.ones,
              )(x)
              return atari_lib.DQNNetworkType(x)
  
      agent = dqn_agent.JaxDQNAgent(
          network=MockDQNNetwork,
          observation_shape=self.observation_shape,
          observation_dtype=self.observation_dtype,
          stack_size=self.stack_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.
          allow_partial_reload=allow_partial_reload,
      )
      # This ensures non-random action choices (since epsilon_eval = 0.0) and
      # skips the train_step.
      agent.eval_mode = True
      return agent
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import shutil
  from absl import flags
  from absl.testing import absltest
  from dopamine.discrete_domains import atari_lib
  from dopamine.jax.agents.dqn import dqn_agent
  from dopamine.utils import test_utils
  from flax import linen
  import gin
  import jax.numpy
  import mock
  import numpy
label_desc: Use image node_id 2 for calling the DQNAgentTest obj's underlying member method code with example usage: obj._create_test_agent(allow_partial_reload) and returns: agent, atari_lib, to_pick_first_action