code: def __init__(self, dataloader, transform_fn, num_prefetch=0):
      self._data_queue = queue.Queue(maxsize=num_prefetch)
      self._done_event = threading.Event()
      self._transform_thread = threading.Thread(
          target=transform_loop,
          args=(
              dataloader,
              transform_fn,
              self._data_queue,
              self._done_event,
          ),
      )
      self._transform_thread.start()
  
imports: import queue
  import threading
  from typing import Dict, List, Union
  import torch
  from torch.utils.data._utils import MP_STATUS_CHECK_INTERVAL
  from torchrec import EmbeddingBagConfig, EmbeddingConfig
  from torchrec.distributed.model_parallel import DistributedModelParallel
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
  from .id_transformer_group import IDTransformerGroup
label_desc: Use image node_id 1 to create a new DataLoaderIter object  with example: obj = DataLoaderIter(dataloader, transform_fn, num_prefetch)