code: def _worker_loop(
      predictor_path: Path,
      input_queue: mp.Queue,
      output_queue: mp.Queue,
      worker_id,
      **kwargs,
  ):
      """
      Worker loop for multiprocessing Predictor.
  
      Loads the predictor serialized in predictor_path reads inputs from
      input_queue and writes forecasts to output_queue
      """
  
      predictor = Predictor.deserialize(predictor_path)
      while True:
          idx, data_chunk = input_queue.get()
          if idx is None:
              output_queue.put((None, None, None))
              break
          try:
              result = list(predictor.predict(data_chunk, **kwargs))
          except Exception:
              we = WorkerError(
                  "".join(traceback.format_exception(*sys.exc_info()))
              )
              output_queue.put((we, None, None))
              break
          output_queue.put((idx, worker_id, result))
  
imports: import itertools
  import json
  import logging
  import multiprocessing
  import sys
  import traceback
  from pathlib import Path
  from pydoc import locate
  from tempfile import TemporaryDirectory
  from typing import TYPE_CHECKING, Callable, Iterator, Optional, Dict, Any
  import numpy
  import gluonts
  from gluonts.core import fqname_for
  from gluonts.core.component import equals, from_hyperparameters
  from gluonts.core.serde import dump_json, load_json
  from gluonts.dataset.common import DataEntry, Dataset
  from gluonts.model.forecast import Forecast
label_desc: Use image node_id 1 for calling a global function with example usage: _worker_loop(predictor_path, input_queue, output_queue, worker_id) without return types