code: def test_training_should_be_reproducible(self):
      # Given
      dataset_stream = io.StringIO(
          """
  ---
  type: intent
  name: MakeTea
  utterances:
  - make me a [beverage_temperature:Temperature](hot) cup of tea
  - make me [number_of_cups:snips/number](five) tea cups
  
  ---
  type: intent
  name: MakeCoffee
  utterances:
  - make me [number_of_cups:snips/number](one) cup of coffee please
  - brew [number_of_cups] cups of coffee"""
      )
      dataset = Dataset.from_yaml_files("en", [dataset_stream]).json
      x = [text_to_utterance("please make me two hots cups of tea")]
      shared = self.get_shared_data(dataset)
      shared["random_state"] = 42
  
      # When
      vectorizer1 = CooccurrenceVectorizer(**shared)
      vectorizer1.fit(x, dataset)
  
      vectorizer2 = CooccurrenceVectorizer(**shared)
      vectorizer2.fit(x, dataset)
  
      # Then
      with temp_dir() as tmp_dir:
          dir_vectorizer1 = tmp_dir / "vectorizer1"
          dir_vectorizer2 = tmp_dir / "vectorizer2"
          vectorizer1.persist(dir_vectorizer1)
          vectorizer2.persist(dir_vectorizer2)
          hash1 = dirhash(str(dir_vectorizer1), "sha256")
          hash2 = dirhash(str(dir_vectorizer2), "sha256")
          self.assertEqual(hash1, hash2)
  
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 11 for calling the CooccurrenceVectorizerTest obj's underlying member method code with example usage: obj.test_training_should_be_reproducible() without return types