code: def get_contexts_iterator(dataset, intent_name, random_state):
      shuffled_utterances = random_state.permutation(
          dataset[INTENTS][intent_name][UTTERANCES]
      )
      return cycle(shuffled_utterances)
  
file_path: snips-nlu/snips_nlu/data_augmentation.py
imports: from __future__ import unicode_literals
  from builtins import next
  from copy import deepcopy
  from itertools import cycle
  from future.utils import iteritems
  from snips_nlu.constants import CAPITALIZE, DATA, ENTITIES, ENTITY, INTENTS, TEXT, UTTERANCES
  from snips_nlu.entity_parser.builtin_entity_parser import is_builtin_entity
  from snips_nlu.languages import get_default_sep
  from snips_nlu.preprocessing import tokenize_light
  from snips_nlu.resources import get_stop_words
label_desc: Use image node_id 4 for calling a global function with example usage: get_contexts_iterator(dataset, intent_name, random_state) and returns: cycle