def METHOD_NAME(pair, mask=None):
    """specialized test since checklists have more than one feature ious """
    default = Label(data=ImageData(uid="ckppihxc10005aeyjen11h7jh"))
    prediction = next(NDJsonConverter.deserialize(pair.predictions), default)
    label = next(LBV1Converter.deserialize([pair.labels]))
    if mask:
        for annotation in [*prediction.annotations, *label.annotations]:
            if isinstance(annotation.value, Mask):
                annotation.value.mask.arr = np.frombuffer(
                    base64.b64decode(annotation.value.mask.url.encode('utf-8')),
                    dtype=np.uint8).reshape((32, 32, 3))
    assert math.isclose(data_row_miou(label, prediction),
                        pair.data_row_expected)
    assert math.isclose(
        miou_metric(label.annotations, prediction.annotations)[0].value,
        pair.data_row_expected)
    feature_ious = feature_miou_metric(label.annotations,
                                       prediction.annotations)
    mapping = {}
    for iou in feature_ious:
        if not mapping.get(iou.value, None):
            mapping[iou.value] = 0
        mapping[iou.value] += 1
    assert mapping == pair.expected