class_docstr: Same as DataLoader except it uses torch-based shuffling buffers which enable batched buffering
  (significantly faster for small data).
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 BatchedDataLoader obj's underlying member method code with example usage: obj.__enter__() and returns: self