def METHOD_NAME():
    env = gym.make("CartPole-v1", render_mode="rgb_array")
    env = gym.wrappers.FlattenObservation(env)
    env = gym.wrappers.TimeAwareObservation(env)
    env = gym.wrappers.NormalizeReward(env, gamma=0.8)
    pickled_env = pickle.loads(pickle.dumps(env))
    obs, info = env.reset(seed=123)
    pickled_obs, pickled_info = pickled_env.reset(seed=123)
    assert data_equivalence(obs, pickled_obs)
    assert data_equivalence(info, pickled_info)
    action = env.action_space.sample()
    obs, reward, terminated, truncated, info = env.step(action)
    (
        pickled_obs,
        pickled_reward,
        pickled_terminated,
        pickled_truncated,
        pickled_info,
    ) = pickled_env.step(action)
    assert data_equivalence(obs, pickled_obs)
    assert data_equivalence(reward, pickled_reward)
    assert data_equivalence(terminated, pickled_terminated)
    assert data_equivalence(truncated, pickled_truncated)
    assert data_equivalence(info, pickled_info)
    env.close()
    pickled_env.close()