code: def get_pool_class(use_multiprocessing):
      global _FORCE_THREADPOOL
      if not use_multiprocessing or _FORCE_THREADPOOL:
          return multiprocessing.dummy.Pool  # ThreadPool
      return multiprocessing.Pool
  
imports: import multiprocessing.dummy
  import queue
  import random
  import threading
  import time
  import warnings
  import weakref
  from contextlib import closing
  import numpy
  import tree
  from keras.api_export import keras_export
  from keras.trainers.data_adapters import data_adapter_utils
  from keras.trainers.data_adapters.data_adapter import DataAdapter
label_desc: Use image node_id 1 for calling a global function with example usage: get_pool_class(use_multiprocessing) and returns: multiprocessing, multiprocessing