(x_gpu, y_gpu)
return binaryop_2d("/", operator.truediv, False, x_gpu, y_gpu)
Divides two scalars, vectors, or matrices with broadcasting.

    The numpy broadcasting rules apply so this would yield the same result
    as `x_gpu.get()` / `y_gpu.get()` in host code.

    Parameters
    ----------
    x_gpu, y_gpu : pycuda.gpuarray.GPUArray
        The arrays to be divided.

    Returns
    -------
    out : pycuda.gpuarray.GPUArray
        Equivalent to `x_gpu.get()` / `y_gpu.get()`.

    Notes
    -----
    The `out` and `stream` options are not supported because `GPUArray.__div__`
    doesn't provide them.
Divides two scalars, vectors, or matrices with broadcasting.
Divides two scalars vectors or matrices with broadcasting .
def divide(x_gpu, y_gpu):
    """
    Divides two scalars, vectors, or matrices with broadcasting.

    The numpy broadcasting rules apply so this would yield the same result
    as `x_gpu.get()` / `y_gpu.get()` in host code.

    Parameters
    ----------
    x_gpu, y_gpu : pycuda.gpuarray.GPUArray
        The arrays to be divided.

    Returns
    -------
    out : pycuda.gpuarray.GPUArray
        Equivalent to `x_gpu.get()` / `y_gpu.get()`.

    Notes
    -----
    The `out` and `stream` options are not supported because `GPUArray.__div__`
    doesn't provide them.
    """

    return binaryop_2d("/", operator.truediv, False, x_gpu, y_gpu)
def divide ( x_gpu , y_gpu ) : return binaryop_2d ( "/" , operator . truediv , False , x_gpu , y_gpu )