code: def fake_atari_wrapped(
      episode_length: int = 10, oar_wrapper: bool = False
  ) -> dm_env.Environment:
      """Builds fake version of the environment to be used by tests.
  
      Args:
        episode_length: The length of episodes produced by this environment.
        oar_wrapper: Should ObservationActionRewardWrapper be applied.
  
      Returns:
        Fake version of the environment equivalent to the one returned by
        env_loader.load_atari_wrapped
      """
      env = DiscreteEnvironment(
          num_actions=18,
          num_observations=2,
          obs_shape=(84, 84, 4),
          obs_dtype=np.float32,
          episode_length=episode_length,
      )
  
      if oar_wrapper:
          env = wrappers.ObservationActionRewardWrapper(env)
      return env
  
imports: import threading
  from typing import List, Mapping, Optional, Sequence, Callable, Iterator
  from acme import core
  from acme import specs
  from acme import types
  from acme import wrappers
  import dm_env
  import numpy
  import reverb
  from rlds import rlds_types
  import tensorflow
  import tree
label_desc: Use image node_id 8 for calling a global function with example usage: fake_atari_wrapped(episode_length, oar_wrapper) and returns: env