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.
docstr: Selects an batch of items from the buffer and returns the batch to the caller.
  The items are removed from the buffer.
  
  :return: The selected batch.
docstr_tok: ["Selects","an","batch","of","items","from","the","buffer","and","returns","the","batch","to","the","caller",".","The","items","are","removed","from","the","buffer",".",":","return",":","The","selected","batch","."]
code: def retrieve(self):
      """Selects an batch of items from the buffer and returns the batch to the caller.
      The items are removed from the buffer.
  
      :return: The selected batch.
      """
  
imports: import abc
  import six
  import torch
label_desc: Use image node_id 4 for calling the BatchedShufflingBufferBase obj's underlying member method code with example usage: obj.retrieve() without return types