docstr: Create iterator objects for splits of the WikiText-103 dataset.
  
  This is the simplest way to use the dataset, and assumes common
  defaults for field, vocabulary, and iterator parameters.
  
  Args:
      batch_size: Batch size.
      bptt_len: Length of sequences for backpropagation through time.
      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 wikitext-2
          subdirectory the data files will be stored.
      vectors: One of either the available pretrained vectors
          or custom pretrained vectors (see Vocab.load_vectors);
          or a list of aforementioned vectors
      kwargs: Passed to the splits method.
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code: def iters(
      cls,
      batch_size=32,
      bptt_len=35,
      device=0,
      root=".data",
      vectors=None,
      **kwargs,
  ):
      """Create iterator objects for splits of the WikiText-103 dataset.
  
      This is the simplest way to use the dataset, and assumes common
      defaults for field, vocabulary, and iterator parameters.
  
      Args:
          batch_size: Batch size.
          bptt_len: Length of sequences for backpropagation through time.
          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 wikitext-2
              subdirectory the data files will be stored.
          vectors: One of either the available pretrained vectors
              or custom pretrained vectors (see Vocab.load_vectors);
              or a list of aforementioned vectors
          kwargs: Passed to the splits method.
      """
      TEXT = data.Field()
  
      train, val, test = cls.splits(TEXT, root=root, **kwargs)
  
      TEXT.build_vocab(train, vectors=vectors)
  
      return data.BPTTIterator.splits(
          (train, val, test),
          batch_size=batch_size,
          bptt_len=bptt_len,
          device=device,
      )
  
file_path: pytext/pytext/legacy/datasets/language_modeling.py
imports: import io
  from ..None import data
label_desc: Use image node_id 2 for calling the WikiText103 obj's underlying member method code with example usage: obj.iters(cls, batch_size, bptt_len, device, root, vectors) and returns: data