class_docstr: This class loads in the Facebook bAbI dataset and vectorizes them into stories,
  questions, and answers as described in:
  "Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks"
  http://arxiv.org/abs/1502.05698.
class_docstr_tok: ["This","class","loads","in","the","Facebook","bAbI","dataset","and","vectorizes","them","into","stories",",","questions",",","and","answers","as","described","in",":","''","Towards","AI-Complete","Question","Answering",":","A","Set","of","Prerequisite","Toy","Tasks","''","http",":","\/\/arxiv.org\/abs\/1502.05698","."]
docstr: Convert a list of words into vector form.
  
  Arguments:
      words (list) : List of words.
  
  Returns:
      list : Vectorized list of words.
docstr_tok: ["Convert","a","list","of","words","into","vector","form",".","Arguments",":","words","(","list",")",":","List","of","words",".","Returns",":","list",":","Vectorized","list","of","words","."]
code: def words_to_vector(self, words):
      """
      Convert a list of words into vector form.
  
      Arguments:
          words (list) : List of words.
  
      Returns:
          list : Vectorized list of words.
      """
      return [
          self.word_to_index[w]
          if w in self.word_to_index
          else self.vocab_size - 1
          for w in words
      ]
  
imports: from builtins import map
  import numpy
  import os
  import re
  import tarfile
  from neon import logger
  from neon.data.dataiterator import NervanaDataIterator
  from neon.data.datasets import Dataset
  from neon.data.text_preprocessing import pad_sentences
  from functools import reduce
label_desc: Use image node_id 7 for calling the BABI obj's underlying member method code with example usage: obj.words_to_vector(words) and returns: unknown