class_docstr: Base class for predict worker that runs offline in multiprocess
class_docstr_tok: ["Base","class","for","predict","worker","that","runs","offline","in","multiprocess"]
docstr: Args:
      idx (int): index of the worker. the 0th worker will print log.
      config (PredictConfig): the config to use.
docstr_tok: ["Args",":","idx","(","int",")",":","index","of","the","worker",".","the","0th","worker","will","print","log",".","config","(","PredictConfig",")",":","the","config","to","use","."]
code: def __init__(self, idx, config):
      """
      Args:
          idx (int): index of the worker. the 0th worker will print log.
          config (PredictConfig): the config to use.
      """
      super(MultiProcessPredictWorker, self).__init__()
      self.name = "MultiProcessPredictWorker-{}".format(idx)
      self.idx = idx
      self.config = config
  
imports: import multiprocessing
  import numpy
  from concurrent.futures import Future
  import tensorflow
  from six.moves import queue, range
  from ..compat import tfv1
  from ..tfutils.model_utils import describe_trainable_vars
  from ..utils import logger
  from ..utils.concurrency import DIE, ShareSessionThread, StoppableThread
  from .base import AsyncPredictorBase, OfflinePredictor, OnlinePredictor
label_desc: Use image node_id 1 to create a new MultiProcessPredictWorker object from inherited base classes: multiprocessing with example: obj = MultiProcessPredictWorker(idx, config)