Function fall_back_tuple

monai/utils/misc.py:260–303

Refine `user_provided` according to the `default`, and returns as a validated tuple. The validation is done for each element in `user_provided` using `func`. If `func(user_provided[idx])` returns False, the corresponding `default[idx]` will be used as the fallback. Typically u

(
    user_provided: Any, default: Sequence | NdarrayTensor, func: Callable = lambda x: x and x > 0
)

def fall_back_tuple(
    user_provided: Any, default: Sequence | NdarrayTensor, func: Callable = lambda x: x and x > 0
) -> tuple[Any, ...]:
    """
    Refine `user_provided` according to the `default`, and returns as a validated tuple.

    The validation is done for each element in `user_provided` using `func`.
    If `func(user_provided[idx])` returns False, the corresponding `default[idx]` will be used
    as the fallback.

    Typically used when `user_provided` is a tuple of window size provided by the user,
    `default` is defined by data, this function returns an updated `user_provided` with its non-positive
    components replaced by the corresponding components from `default`.

    Args:
        user_provided: item to be validated.
        default: a sequence used to provided the fallbacks.
        func: a Callable to validate every components of `user_provided`.

    Examples::

        >>> fall_back_tuple((1, 2), (32, 32))
        (1, 2)
        >>> fall_back_tuple(None, (32, 32))
        (32, 32)
        >>> fall_back_tuple((-1, 10), (32, 32))
        (32, 10)
        >>> fall_back_tuple((-1, None), (32, 32))
        (32, 32)
        >>> fall_back_tuple((1, None), (32, 32))
        (1, 32)
        >>> fall_back_tuple(0, (32, 32))
        (32, 32)
        >>> fall_back_tuple(range(3), (32, 64, 48))
        (32, 1, 2)
        >>> fall_back_tuple([0], (32, 32))
        ValueError: Sequence must have length 2, got length 1.

    """
    ndim = len(default)
    user = ensure_tuple_rep(user_provided, ndim)
    return tuple(  # use the default values if user provided is not valid
        user_c if func(user_c) else default_c for default_c, user_c in zip(default, user)
    )


def is_scalar_tensor(val: Any) -> bool: