0df03347b9e26ef6153d1a1bed49991b51b09a9d,snips_nlu/tests/test_intent_classifier_featurizer.py,CooccurrenceVectorizerTest,test_limit_vocabulary,#CooccurrenceVectorizerTest#,929

Before Change

        // Given
        config = CooccurrenceVectorizerConfig(filter_stop_words=False)
        vectorizer = CooccurrenceVectorizer(config=config)
        train_data = [
            ("a b", [], []),
            ("a c", [], []),
            ("a d", [], []),
            ("a e", [], []),
        ]
        data = [
            ("a c e", [], []),
            ("a d e", [], []),
        ]

After Change

            text_to_utterance(t) for t in ("a b", "a c", "a d", "a e")]

        data = [text_to_utterance(t) for t in ("a c e", "a d e")]
        vectorizer.fit(train_data, get_empty_dataset("en"))
        x_0 = vectorizer.transform(data)
        pairs = {
            ("a", "b"): 0,

Instances