def standard_cauchy(
    size: NdShapeLike | None = None,
    dtype: npt.DTypeLike = np.float64,
) -> ndarray:
    """
    standard_cauchy(size=None)

    Draw samples from a standard Cauchy distribution with mode = 0.

    Also known as the Lorentz distribution.

    Parameters
    ----------
    size : int or tuple of ints, optional
        Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
        ``m * n * k`` samples are drawn.  Default is None, in which case a
        single value is returned.

    Returns
    -------
    samples : ndarray or scalar
        The drawn samples.

    See Also
    --------
    numpy.random.standard_cauchy

    Availability
    --------
    Multiple GPUs, Multiple CPUs
    """
    return get_static_generator().standard_cauchy(size, dtype)

    standard_cauchy(size=None)

    Draw samples from a standard Cauchy distribution with mode = 0.

    Also known as the Lorentz distribution.

    Parameters
    ----------
    size : int or tuple of ints, optional
        Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
        ``m * n * k`` samples are drawn.  Default is None, in which case a
        single value is returned.

    Returns
    -------
    samples : ndarray or scalar
        The drawn samples.

    See Also
    --------
    numpy.random.standard_cauchy

    Availability
    --------
    Multiple GPUs, Multiple CPUs
    
cupynumeric/random/_random.py