class_docstr: Intent extraction dataset base class
  
  Args:
      sentence_length (int): max sentence length
class_docstr_tok: ["Intent","extraction","dataset","base","class","Args",":","sentence_length","(","int",")",":","max","sentence","length"]
docstr: :obj:`tuple` of :obj:`numpy.ndarray`: train set
docstr_tok: [":","obj",":","`","tuple","`","of",":","obj",":","`","numpy.ndarray","`",":","train","set"]
code: def train_set(self):
      """:obj:`tuple` of :obj:`numpy.ndarray`: train set"""
      return self.vecs["train"]
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import json
  import os
  import sys
  import numpy
  from nlp_architect.utils.generic import pad_sentences
  from nlp_architect.utils.text import SpacyInstance, Vocabulary, character_vector_generator, word_vector_generator
label_desc: Use image node_id 11 for calling the IntentDataset obj's underlying member method code with example usage: obj.train_set() and returns: self