class_docstr: DataLoaderIter class used to more quickly load a batch of indices at once.
class_docstr_tok: ["DataLoaderIter","class","used","to","more","quickly","load","a","batch","of","indices","at","once","."]
code: def __init__(self, dataloader):
      if dataloader.num_workers == 0:
          self.iter = _SingleProcessDataLoaderIter(dataloader)
      else:
          self.iter = _MultiProcessingDataLoaderIter(dataloader)
  
imports: import os
  import pickle
  import sys
  import time
  import numpy
  import scipy.sparse
  from sklearn.datasets import load_svmlight_file
  import torch
  from torch.utils.data import DataLoader, Dataset
  from torch.utils.data.dataloader import _SingleProcessDataLoaderIter, _MultiProcessingDataLoaderIter, _utils
  from .None import constants
  from .None import syssettings
label_desc: Use image node_id 1 to create a new _ChunkDataLoaderIter object  with example: obj = _ChunkDataLoaderIter(dataloader)