code: def test_fit_with_no_utterance_should_raise(self):
      # Given
      utterances = []
      classes = []
      dataset = get_empty_dataset("en")
  
      # When/Then
      with self.assertRaises(_EmptyDatasetUtterancesError) as ctx:
          Featurizer().fit_transform(dataset, utterances, classes, None)
  
      self.assertEqual(
          "Tokenized utterances are empty", str(ctx.exception)
      )
  
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 6 for calling the TestIntentClassifierFeaturizer obj's underlying member method code with example usage: obj.test_fit_with_no_utterance_should_raise() without return types