code: def test_feature_index_to_feature_name(self):
      # Given
      config = FeaturizerConfig(added_cooccurrence_feature_ratio=0.75)
      featurizer = Featurizer(config=config)
  
      # When
      mocked_cooccurrence_vectorizer = MagicMock()
      mocked_cooccurrence_vectorizer.word_pairs = {("a", "b"): 0}
  
      mocked_tfidf_vectorizer = MagicMock()
      mocked_tfidf_vectorizer.vocabulary = {"a": 0}
  
      featurizer.cooccurrence_vectorizer = (
          mocked_cooccurrence_vectorizer
      )
      featurizer.tfidf_vectorizer = mocked_tfidf_vectorizer
  
      # Then
      expected = {0: "ngram:a", 1: "pair:a+b"}
      self.assertDictEqual(
          expected, featurizer.feature_index_to_feature_name
      )
  
imports: from __future__ import unicode_literals
  import io
  from builtins import str, zip, range
  import numpy
  from checksumdir import dirhash
  from mock import patch, MagicMock
  from snips_nlu.common.io_utils import temp_dir
  from snips_nlu.common.utils import json_string
  from snips_nlu.constants import LANGUAGE_EN, STEMS, WORD_CLUSTERS, STOP_WORDS
  from snips_nlu.dataset import Dataset
  from snips_nlu.entity_parser import BuiltinEntityParser, CustomEntityParser
  from snips_nlu.entity_parser.custom_entity_parser_usage import CustomEntityParserUsage
  from snips_nlu.exceptions import _EmptyDatasetUtterancesError
  from snips_nlu.intent_classifier.featurizer import CooccurrenceVectorizer, Featurizer, TfidfVectorizer
  from snips_nlu.intent_classifier.log_reg_classifier_utils import text_to_utterance
  from snips_nlu.pipeline.configs import FeaturizerConfig
  from snips_nlu.pipeline.configs.intent_classifier import CooccurrenceVectorizerConfig, TfidfVectorizerConfig
  from snips_nlu.tests.utils import FixtureTest, get_empty_dataset, EntityParserMock
label_desc: Use image node_id 7 for calling the TestIntentClassifierFeaturizer obj's underlying member method code with example usage: obj.test_feature_index_to_feature_name() without return types