code: def wrap_deepmind(
      env,
      dim=84,
      framestack=True,
      obs_format="NHWC",
      test=False,
      test_episodes=3,
  ):
      """Configure environment for DeepMind-style Atari.
  
      Args:
          dim (int): Dimension to resize observations to (dim x dim).
          framestack (bool): Whether to framestack observations.
          obs_format (str): observation output format
          test (bool): whether this is a test env
          test_episodes (int): when test, number of episodes for each evaluation
      """
      env = CompatWrapper(env)
      env = MonitorEnv(env)
      env = NoopResetEnv(env, noop_max=30)
      if "NoFrameskip" in env.spec.id:
          env = MaxAndSkipEnv(env, skip=4)
      env = EpisodicLifeEnv(env)
      if "FIRE" in env.unwrapped.get_action_meanings():
          env = FireResetEnv(env)
      env = WarpFrame(env, dim)
      env = ClipRewardEnv(env)
      if framestack:
          env = FrameStack(env, 4, obs_format)
      if test:
          env = TestEnv(env, test_episodes)
      return env
  
imports: import time
  import numpy
  from collections import deque
  import gym
  from gym import spaces
  from parl.env.compat_wrappers import CompatWrapper, is_gym_version_ge, V_NPRANDOM_CHANGED
  import cv2
label_desc: Use image node_id 2 for calling a global function with example usage: wrap_deepmind(env, dim, framestack, obs_format, test, test_episodes) and returns: env