class_docstr: A 'no-operation' (noop) implementation of a shuffling buffer. Useful in cases where no shuffling is desired, such
  as test scenarios or iterating over a dataset in a predeterministic order.
code: def can_retrieve(self):
      if not self._done_adding:
          return self._size >= self.batch_size
      else:
          return self._size > 0
  
imports: import abc
  import six
  import torch
label_desc: Use image node_id 4 for calling the BatchedNoopShufflingBuffer obj's underlying member method code with example usage: obj.can_retrieve() and returns: unknown, unknown