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"]
code: def __init__(self, sentence_length=50, word_length=12):
      self.data_dict = {}
      self.vecs = {}
      self.sentence_len = sentence_length
      self.word_len = word_length
  
      self._tokens_vocab = Vocabulary(2)
      self._chars_vocab = Vocabulary(2)
      self._tags_vocab = Vocabulary(1)
      self._intents_vocab = Vocabulary()
  
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 1 to create a new IntentDataset object from inherited base classes: object with example: obj = IntentDataset(sentence_length, word_length)