docs: def iters(cls, batch_size=32, device=0, root='.data', vectors=None, **kwargs):
          """Create iterator objects for splits of the SST dataset.
  
          Arguments:
              batch_size: Batch_size
              device: Device to create batches on. Use - 1 for CPU and None for
                  the currently active GPU device.
              root: The root directory that the dataset's zip archive will be
                  expanded into; therefore the directory in whose trees
                  subdirectory the data files will be stored.
              vectors: one of the available pretrained vectors or a list with each
                  element one of the available pretrained vectors (see Vocab.load_vectors)
              Remaining keyword arguments: Passed to the splits method.
          """
          TEXT = data.Field()
          LABEL = data.Field(sequential=False)
  
          train, val, test = cls.splits(TEXT, LABEL, root=root, **kwargs)
  
          TEXT.build_vocab(train, vectors=vectors)
          LABEL.build_vocab(train)
  
          return data.BucketIterator.splits(
              (train, val, test), batch_size=batch_size, device=device)