code: def test_fit_transform(self, mocked_preprocess):
      t = "a b c d e f"
      u = text_to_utterance(t)
      builtin_ents = [
          {
              "value": "e",
              "resolved_value": "e",
              "range": {"start": 8, "end": 9},
              "entity_kind": "the_snips_e_entity",
          }
      ]
      custom_ents = [
          {
              "value": "c",
              "resolved_value": "c",
              "range": {"start": 4, "end": 5},
              "entity_kind": "the_c_entity",
          }
      ]
      mocked_preprocess.return_value = (
          [u],
          [builtin_ents],
          [custom_ents],
      )
  
      config = CooccurrenceVectorizerConfig(
          window_size=3,
          unknown_words_replacement_string="b",
          filter_stop_words=False,
      )
  
      dataset = get_empty_dataset("en")
  
      builtin_parser = EntityParserMock({t: builtin_ents})
      custom_parser = EntityParserMock({t: custom_ents})
      resources = {STOP_WORDS: set()}
      vectorizer1 = CooccurrenceVectorizer(
          config,
          builtin_entity_parser=builtin_parser,
          custom_entity_parser=custom_parser,
          resources=resources,
      )
      vectorizer2 = CooccurrenceVectorizer(
          config,
          builtin_entity_parser=builtin_parser,
          custom_entity_parser=custom_parser,
          resources=resources,
      )
  
      # When
      x = [u]
      x_0 = vectorizer1.fit(x, dataset).transform(x).todense().tolist()
      x_1 = vectorizer2.fit_transform(x, dataset).todense().tolist()
  
      # Then
      self.assertListEqual(x_0, x_1)
  
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 CooccurrenceVectorizerTest obj's underlying member method code with example usage: obj.test_fit_transform(mocked_preprocess) without return types