docstr: Args:
      gpus (list[int]): the gpus used to run inference
docstr_tok: ["Args",":","gpus","(","list","[","int","]",")",":","the","gpus","used","to","run","inference"]
code: def __init__(self, pipe_c2s, pipe_s2c, gpus):
      """
      Args:
          gpus (list[int]): the gpus used to run inference
      """
      super(MySimulatorMaster, self).__init__(pipe_c2s, pipe_s2c)
      self.queue = queue.Queue(maxsize=BATCH_SIZE * 8 * 2)
      self._gpus = gpus
  
imports: import argparse
  import cv2
  import gym
  import multiprocessing
  import numpy
  import os
  import sys
  import uuid
  import tensorflow
  from six.moves import queue
  from concurrent import futures
  from tensorpack import *
  from tensorpack.tfutils.gradproc import MapGradient, SummaryGradient
  from tensorpack.utils.concurrency import ensure_proc_terminate, start_proc_mask_signal
  from tensorpack.utils.gpu import get_num_gpu
  from tensorpack.utils.serialize import dumps
  from atari_wrapper import FireResetEnv, FrameStack, LimitLength, MapState
  from common import Evaluator, eval_model_multithread, play_n_episodes
  from simulator import SimulatorMaster, SimulatorProcess, TransitionExperience
label_desc: Use image node_id 1 to create a new MySimulatorMaster object from inherited base classes: SimulatorMaster, Callback with example: obj = MySimulatorMaster(pipe_c2s, pipe_s2c, gpus)