code: def process_images_in_process_pool(
      images_to_check, number_of_cpus, model, upsample
  ):
      if number_of_cpus == -1:
          processes = None
      else:
          processes = number_of_cpus
  
      # macOS will crash due to a bug in libdispatch if you don't use 'forkserver'
      context = multiprocessing
      if "forkserver" in multiprocessing.get_all_start_methods():
          context = multiprocessing.get_context("forkserver")
  
      pool = context.Pool(processes=processes)
  
      function_parameters = zip(
          images_to_check,
          itertools.repeat(model),
          itertools.repeat(upsample),
      )
  
      pool.starmap(test_image, function_parameters)
  
file_path: face_recognition/face_recognition/face_detection_cli.py
imports: from __future__ import print_function
  import click
  import os
  import re
  import face_recognition.api
  import multiprocessing
  import sys
  import itertools
label_desc: Use image node_id 4 for calling a global function with example usage: process_images_in_process_pool(images_to_check, number_of_cpus, model, upsample) without return types