class_docstr: A data loader adaptor for ``torch.utils.data.DataLoader``.
  
  This class iterates and returns items from the Reader in batches.
  
  This loader can be used as an iterator and will terminate when the reader used in the construction of the class
  runs out of samples.
code: def __enter__(self):
      return self
  
imports: import collections.abc
  import decimal
  import re
  import logging
  import numpy
  from six import PY2
  from torch.utils.data.dataloader import default_collate
  import torch
  from packaging import version
  from petastorm.reader_impl.shuffling_buffer import RandomShufflingBuffer, NoopShufflingBuffer
  from petastorm.reader_impl.pytorch_shuffling_buffer import BatchedRandomShufflingBuffer, BatchedNoopShufflingBuffer
label_desc: Use image node_id 4 for calling the DataLoader obj's underlying member method code with example usage: obj.__enter__() and returns: self