code: def get_ptb_words():
      """Gets the Penn Tree Bank dataset as long word sequences.
  
      `Penn Tree Bank <https://catalog.ldc.upenn.edu/LDC99T42>`_
      is originally a corpus of English sentences with linguistic structure
      annotations. This function uses a variant distributed at
      `https://github.com/wojzaremba/lstm <https://github.com/wojzaremba/lstm>`_,
      which omits the annotation and splits the dataset into three parts:
      training, validation, and test.
  
      This function returns the training, validation, and test sets, each of
      which is represented as a long array of word IDs. All sentences in the
      dataset are concatenated by End-of-Sentence mark '<eos>', which is treated
      as one of the vocabulary.
  
      Returns:
          tuple of numpy.ndarray: Int32 vectors of word IDs.
  
      .. Seealso::
         Use :func:`get_ptb_words_vocabulary` to get the mapping between the
         words and word IDs.
  
      """
      train = _retrieve_ptb_words("train.npz", _train_url)
      valid = _retrieve_ptb_words("valid.npz", _valid_url)
      test = _retrieve_ptb_words("test.npz", _test_url)
      return train, valid, test
  
file_path: chainer/chainer/datasets/ptb.py
imports: import os
  import numpy
  from chainer.dataset import download
label_desc: Use image node_id 1 for calling a global function with example usage: get_ptb_words() and returns: train,  valid,  test