def METHOD_NAME(generator_helper, data_helper):
    # Given
    input_data = data_helper.generate_datetime_as_object_feature_advanced().to_frame(name="datetime_as_object")
    generator = DatetimeFeatureGenerator()
    expected_feature_metadata_in_full = {
        ("object", ("datetime_as_object",)): ["datetime_as_object"],
    }
    expected_feature_metadata_full = {
        ("int", ("datetime_as_int",)): [
            "datetime_as_object",
            "datetime_as_object.year",
            "datetime_as_object.month",
            "datetime_as_object.day",
            "datetime_as_object.dayofweek",
        ]
    }
    expected_output_data_feat_datetime = [
        1533140820000000000,
        1600067037034500096,
        1600067037034500096,
        1628543228659000000,
        1628543295541000000,
        1610040803938000000,
    ]
    # When
    output_data = generator_helper.fit_transform_assert(
        input_data=input_data,
        generator=generator,
        expected_feature_metadata_in_full=expected_feature_metadata_in_full,
        expected_feature_metadata_full=expected_feature_metadata_full,
    )
    assert expected_output_data_feat_datetime == list(output_data["datetime_as_object"].values)