815a9afb26358230fc49704edbfbbeb048f55937,tests/nlu/featurizers/test_count_vectors_featurizer.py,,test_count_vector_featurizer_attribute_featurization,#Any#Any#Any#Any#Any#,106

Before Change

            == response_features
        )
    else:
        assert train_message.get(SPARSE_FEATURE_NAMES[RESPONSE]) is None


@pytest.mark.parametrize(
    "sentence, intent, response, text_features, intent_features, response_features",

After Change

    tk.train(data)
    ftr.train(data)

    intent_vecs = train_message.get_sparse_features(INTENT, [])
    response_vecs = train_message.get_sparse_features(RESPONSE, [])
    if intent_features:
        assert intent_vecs.toarray()[0] == intent_features
    else:

Instances