(x_gpu, a_gpu, axis=None, out=None, stream=None)
return binaryop_matvec('*', x_gpu, a_gpu, axis, out, stream)
Multiplies a vector elementwise with each column/row of the matrix.

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

    Parameters
    ----------
    x_gpu : pycuda.gpuarray.GPUArray
        Matrix to multiply by the vector `a_gpu`.
    a_gpu : pycuda.gpuarray.GPUArray
        The matrix `x_gpu` will be multiplied by this vector.
    axis : int (optional)
        The axis on which multiplication occurs. By default this is
        determined automatically by using the first axis with the correct
        dimensionality.
    out : pycuda.gpuarray.GPUArray (optional)
        Optional destination matrix.
    stream : pycuda.driver.Stream (optional)
        Optional Stream in which to perform this calculation.

    Returns
    -------
    out : pycuda.gpuarray.GPUArray
        result of `x_gpu` * `a_gpu`
Multiplies a vector elementwise with each column/row of the matrix.
Multiplies a vector elementwise with each column / row of the matrix .
def mult_matvec(x_gpu, a_gpu, axis=None, out=None, stream=None):
    """
    Multiplies a vector elementwise with each column/row of the matrix.

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

    Parameters
    ----------
    x_gpu : pycuda.gpuarray.GPUArray
        Matrix to multiply by the vector `a_gpu`.
    a_gpu : pycuda.gpuarray.GPUArray
        The matrix `x_gpu` will be multiplied by this vector.
    axis : int (optional)
        The axis on which multiplication occurs. By default this is
        determined automatically by using the first axis with the correct
        dimensionality.
    out : pycuda.gpuarray.GPUArray (optional)
        Optional destination matrix.
    stream : pycuda.driver.Stream (optional)
        Optional Stream in which to perform this calculation.

    Returns
    -------
    out : pycuda.gpuarray.GPUArray
        result of `x_gpu` * `a_gpu`
    """
    return binaryop_matvec('*', x_gpu, a_gpu, axis, out, stream)
def mult_matvec ( x_gpu , a_gpu , axis = None , out = None , stream = None ) : return binaryop_matvec ( '*' , x_gpu , a_gpu , axis , out , stream )