norms.py 文件源码

def slogdet(a):
    """Returns sign and logarithm of the determinat of an array.

    It calculates the natural logarithm of the deteminant of a given value.

    Args:
        a (cupy.ndarray): The input matrix with dimension ``(..., N, N)``.

    Returns:
        tuple of :class:`~cupy.ndarray`:
            It returns a tuple ``(sign, logdet)``. ``sign`` represents each
            sign of the deteminant as a real number ``0``, ``1`` or ``-1``.
            'logdet' represents the natural logarithm of the absolute of the
            deteminant.
            If the deteninant is zero, ``sign`` will be ``0`` and ``logdet``
            will be ``-inf``.
            The shapes of both ``sign`` and ``logdet`` are equal to
            ``a.shape[:-2]``.

    .. seealso:: :func:`numpy.linalg.slogdet`
    """
    if not cuda.cusolver_enabled:
        raise RuntimeError('Current cupy only supports cusolver in CUDA 8.0')

    if a.ndim < 2:
        msg = ('%d-dimensional array given. '
               'Array must be at least two-dimensional' % a.ndim)
        raise linalg.LinAlgError(msg)

    dtype = numpy.find_common_type((a.dtype.char, 'f'), ())
    shape = a.shape[:-2]
    sign = cupy.empty(shape, dtype)
    logdet = cupy.empty(shape, dtype)

    a = a.astype(dtype)
    for index in numpy.ndindex(*shape):
        s, l = _slogdet_one(a[index])
        sign[index] = s
        logdet[index] = l
    return sign, logdet