code: def __init__(
      self,
      data_loader,
      transform,
      num_processes,
      num_cached_per_queue=2,
      timeout=10,
      wait_time=0.2,
  ):
      self.data_loader = data_loader
      self.transform = transform
      self.num_processes = num_processes
      self.num_cached_per_queue = num_cached_per_queue
      self.queue_maxsize = num_cached_per_queue * num_processes
      self.timeout = timeout
      self.wait_time = wait_time
      self._queue = None
      self._processes = None
      self.is_initialized = False
  
file_path: PaddleSeg/contrib/MedicalSeg/nnunet/transforms/multi_threaded_augmenter.py
imports: import sys
  import paddle
  import traceback
  from multiprocessing import Event, Queue, Process
  from time import sleep
  from threadpoolctl import threadpool_limits
label_desc: Use image node_id 1 to create a new MultiThreadedAugmenter object  with example: obj = MultiThreadedAugmenter(data_loader, transform, num_processes, num_cached_per_queue, timeout, wait_time)