class_docstr: SNIPS dataset class
  
  Args:
          path (str): dataset path
          sentence_length (int, optional): max sentence length
          word_length (int, optional): max word length
class_docstr_tok: ["SNIPS","dataset","class","Args",":","path","(","str",")",":","dataset","path","sentence_length","(","int",",","optional",")",":","max","sentence","length","word_length","(","int",",","optional",")",":","max","word","length"]
code: def _create_tags(tag, length):
      labels = ["B-" + tag]
      if length > 1:
          for _ in range(length - 1):
              labels.append("I-" + tag)
      return labels
  
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 5 for calling the SNIPS obj's underlying member method code with example usage: obj._create_tags(tag, length) and returns: labels