code: def test_should_be_serializable(self):
      # Given
  
      dataset_stream = io.StringIO(
          """
  ---
  type: intent
  name: dummy_intent
  utterances:
    - this is the number [number:snips/number](one)
  """
      )
      dataset = Dataset.from_yaml_files("en", [dataset_stream]).json
      pvalue_threshold = 0.42
      config = FeaturizerConfig(
          pvalue_threshold=pvalue_threshold,
          added_cooccurrence_feature_ratio=0.2,
      )
      shared = self.get_shared_data(dataset)
      featurizer = Featurizer(config=config, **shared)
      utterances = [
          text_to_utterance("this is the number"),
          text_to_utterance("yo"),
      ]
      classes = np.array([0, 1])
      featurizer.fit(dataset, utterances, classes, max(classes))
  
      # When
      featurizer.persist(self.tmp_file_path)
  
      # Then
      expected_featurizer_dict = {
          "language_code": "en",
          "tfidf_vectorizer": "tfidf_vectorizer",
          "cooccurrence_vectorizer": "cooccurrence_vectorizer",
          "config": config.to_dict(),
      }
      featurizer_dict_path = self.tmp_file_path / "featurizer.json"
      self.assertJsonContent(
          featurizer_dict_path, expected_featurizer_dict
      )
  
      expected_metadata = {"unit_name": "featurizer"}
      metadata_path = self.tmp_file_path / "metadata.json"
      self.assertJsonContent(metadata_path, expected_metadata)
  
      tfidf_vectorizer_path = self.tmp_file_path / "tfidf_vectorizer"
      self.assertTrue(tfidf_vectorizer_path.exists())
  
      cooc_vectorizer_path = (
          self.tmp_file_path / "cooccurrence_vectorizer"
      )
      self.assertTrue(cooc_vectorizer_path.exists())
  
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 1 for calling the TestIntentClassifierFeaturizer obj's underlying member method code with example usage: obj.test_should_be_serializable() without return types