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

    Draw samples from the standard exponential distribution.

    `standard_exponential` is identical to the exponential distribution
    with a scale parameter of 1.

    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
    -------
    out : float or ndarray
        Drawn samples.

    See Also
    --------
    numpy.random.standard_exponential

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

    standard_exponential(size=None)

    Draw samples from the standard exponential distribution.

    `standard_exponential` is identical to the exponential distribution
    with a scale parameter of 1.

    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
    -------
    out : float or ndarray
        Drawn samples.

    See Also
    --------
    numpy.random.standard_exponential

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