def isneginf(x: ndarray, out: ndarray | None = None) -> ndarray:
    """

    Test element-wise for negative infinity, return result as bool array.

    Parameters
    ----------
    x : array_like
        The input array.
    out : array_like, optional
        A location into which the result is stored. If provided, it must have a
        shape that the input broadcasts to. If not provided or None, a
        freshly-allocated boolean array is returned.

    Returns
    -------
    out : ndarray
        A boolean array with the same dimensions as the input.
        If second argument is not supplied then a numpy boolean array is
        returned with values True where the corresponding element of the
        input is negative infinity and values False where the element of
        the input is not negative infinity.

        If a second argument is supplied the result is stored there. If the
        type of that array is a numeric type the result is represented as
        zeros and ones, if the type is boolean then as False and True. The
        return value `out` is then a reference to that array.

    See Also
    --------
    numpy.isneginf

    Availability
    --------
    Multiple GPUs, Multiple CPUs

    """
    x = convert_to_cupynumeric_ndarray(x)
    if out is not None:
        out = convert_to_cupynumeric_ndarray(out, share=True)
    rhs1 = isinf(x)
    rhs2 = signbit(x)
    return logical_and(rhs1, rhs2, out=out)


    Test element-wise for negative infinity, return result as bool array.

    Parameters
    ----------
    x : array_like
        The input array.
    out : array_like, optional
        A location into which the result is stored. If provided, it must have a
        shape that the input broadcasts to. If not provided or None, a
        freshly-allocated boolean array is returned.

    Returns
    -------
    out : ndarray
        A boolean array with the same dimensions as the input.
        If second argument is not supplied then a numpy boolean array is
        returned with values True where the corresponding element of the
        input is negative infinity and values False where the element of
        the input is not negative infinity.

        If a second argument is supplied the result is stored there. If the
        type of that array is a numeric type the result is represented as
        zeros and ones, if the type is boolean then as False and True. The
        return value `out` is then a reference to that array.

    See Also
    --------
    numpy.isneginf

    Availability
    --------
    Multiple GPUs, Multiple CPUs

    
cupynumeric/_module/logic_array_contents.py