code: def _task(self):
      # Do a single task in the prefetch thread.
      # Returns a bool indicating whether the loop should continue running.
  
      status, prefetch_state, reset_count = self._comm.check()
      if status == _Communicator.STATUS_RESET:
          self.prefetch_state = prefetch_state
      elif status == _Communicator.STATUS_TERMINATE:
          return False  # stop loop
  
      (
          self.prefetch_state,
          indices,
      ) = _statemachine.iterator_statemachine(
          self.prefetch_state,
          self.batch_size,
          self.repeat,
          self.order_sampler,
          len(self.dataset),
      )
      if indices is None:  # stop iteration
          batch = None
      else:
          future = self._pool.map_async(_fetch_run, enumerate(indices))
          while True:
              try:
                  data_all = future.get(_response_time)
              except multiprocessing.TimeoutError:
                  if self._comm.is_terminated:
                      return False
              else:
                  break
          batch = [_unpack(data, self.mem_bulk) for data in data_all]
  
      self._comm.put(batch, self.prefetch_state, reset_count)
      return True
  
imports: from __future__ import division
  import datetime
  import multiprocessing
  from multiprocessing import sharedctypes
  import signal
  import sys
  import threading
  import warnings
  import numpy
  import six
  from chainer.dataset import iterator
  from chainer.iterators import _statemachine
  from chainer.iterators.order_samplers import ShuffleOrderSampler
label_desc: Use image node_id 9 for calling the _PrefetchLoop obj's underlying member method code with example usage: obj._task() and returns: True, False, False