code: def __init__(self, cfg, result_queue=None):
      num_workers = cfg.NUM_GPUS
  
      self.task_queue = mp.Queue()
      self.result_queue = (
          mp.Queue() if result_queue is None else result_queue
      )
  
      self.get_idx = -1
      self.put_idx = -1
      self.procs = []
      cfg = cfg.clone()
      cfg.defrost()
      cfg.NUM_GPUS = 1
      for gpu_id in range(num_workers):
          self.procs.append(
              AsycnActionPredictor._Predictor(
                  cfg, self.task_queue, self.result_queue, gpu_id
              )
          )
  
      self.result_data = {}
      for p in self.procs:
          p.start()
      atexit.register(self.shutdown)
  
imports: import atexit
  import numpy
  import queue
  import torch
  import torch.multiprocessing
  import slowfast.utils.logging
  from slowfast.datasets import cv2_transform
  from slowfast.visualization.predictor import Predictor
label_desc: Use image node_id 1 to create a new AsycnActionPredictor object  with example: obj = AsycnActionPredictor(cfg, result_queue)