code: def __init__(
      self,
      data_loader: DataLoader,
      image_extractor: Callable,
      label_extractor: Callable,
  ) -> None:
      if not isinstance(data_loader, DataLoader):
          raise ValueError(
              f"Loader has unsupported type: {type(data_loader)}. Expected type was `torch.utils.data.DataLoader`"
          )
      self.data_loader = data_loader
      self._iterator = iter(data_loader)
      self.image_extractor = image_extractor
      self.label_extractor = label_extractor
  
imports: from __future__ import annotations
  import pickle
  import types
  import warnings
  from functools import partial
  from typing import TYPE_CHECKING, Any, Callable
  import numpy
  import torch
  import torch.nn
  from torch.optim import Optimizer
  from torch.serialization import DEFAULT_PROTOCOL
  from torch.utils.data import DataLoader
  from monai.networks.utils import eval_mode
  from monai.optimizers.lr_scheduler import ExponentialLR, LinearLR
  from monai.utils import StateCacher, copy_to_device, optional_import
label_desc: Use image node_id 1 to create a new DataLoaderIter object  with example: obj = DataLoaderIter(data_loader, image_extractor, label_extractor)