class_docstr: A wrapper for ALE emulator, with configurations to mimic DeepMind DQN settings.
  Info:
      score: the accumulated reward in the current game
      gameOver: True when the current game is Over
class_docstr_tok: ["A","wrapper","for","ALE","emulator",",","with","configurations","to","mimic","DeepMind","DQN","settings",".","Info",":","score",":","the","accumulated","reward","in","the","current","game","gameOver",":","True","when","the","current","game","is","Over"]
docstr: :returns: the current 3-channel image
docstr_tok: [":","returns",":","the","current","3-channel","image"]
code: def _grab_raw_image(self):
      """
      :returns: the current 3-channel image
      """
      m = self.ale.getScreenRGB()
      return m.reshape((self.height, self.width, 3))
  
file_path: PARL/benchmark/fluid/DQN_variant/atari.py
imports: import cv2
  import gym
  import numpy
  import os
  import threading
  from atari_py import ALEInterface
  from gym import spaces
  from gym.envs.atari.atari_env import ACTION_MEANING
label_desc: Use image node_id 3 for calling the AtariPlayer obj's underlying member method code with example usage: obj._grab_raw_image() and returns: m