a0351c62548ebddf5c728ec525ad61a4f7827494,tests/hypermodel/test_preprocessor.py,,test_feature_engineering,#,132

Before Change

def test_feature_engineering():
    data = structured_data()
    dataset = tf.data.Dataset.from_tensor_slices(data)
    feature = preprocessor.FeatureEngineering()
    feature.input_node = ak.StructuredDataInput(column_names=COLUMN_NAMES_FROM_NUMPY,
                                                column_types=COLUMN_TYPES_FROM_NUMPY)
    feature.set_hp(kerastuner.HyperParameters())
    for x in dataset:
        feature.update(x)
    feature.finalize()
    feature.set_config(feature.get_config())
    for a in dataset:
        feature.transform(a)

    def map_func(x):
        return tf.py_function(feature.transform,
                              inp=[x],
                              Tout=(tf.float64,))
    new_dataset = dataset.map(map_func)
    assert isinstance(new_dataset, tf.data.Dataset)


def test_feature_engineering_fix_keyerror():

After Change

def test_feature_engineering():
    dataset = common.generate_structured_data(dtype="dataset")
    feature = preprocessor.FeatureEngineering()
    feature.input_node = ak.StructuredDataInput(
        column_names=common.COLUMN_NAMES_FROM_NUMPY,
        column_types=common.COLUMN_TYPES_FROM_NUMPY)
    new_dataset = run_preprocessor(feature,
                                   dataset,
                                   common.generate_data(dtype="dataset"),
                                   tf.float32)
    assert isinstance(new_dataset, tf.data.Dataset)


def test_feature_engineering_fix_keyerror():

Instances