class_docstr: Shuffling implements a shuffling algorithm. Items can be added to the shuffling buffer and removed in a
  different order as defined by the concrete shuffling algorithm. A shuffling buffer is intended to be used from
  a single thread, hence, not thread safe.
  Functionality is similar to ShufflingBufferBase except operations are batched and based on PyTorch.
code: def add_many(self, items):
      items = [torch.as_tensor(v) for v in items]
  
      return self._add_many(items)
  
imports: import abc
  import six
  import torch
label_desc: Use image node_id 2 for calling the BatchedShufflingBufferBase obj's underlying member method code with example usage: obj.add_many(items) and returns: self