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"]
code: def reset(self):
      if self.ale.game_over():
          self._restart_episode()
      return self._current_state()
  
file_path: PARL/benchmark/fluid/offline-Q-learning/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 6 for calling the AtariPlayer obj's underlying member method code with example usage: obj.reset() and returns: self