def cudnnSoftmaxForward(handle, algorithm, mode, alpha, srcDesc, srcData, beta, destDesc, destData):
    """"
    This routing computes the softmax function

    Parameters
    ----------
    handle : cudnnHandle
        Handle to a previously created cuDNN context.
    algorithm : cudnnSoftmaxAlgorithm
        Enumerant to specify the softmax algorithm.
    mode : cudnnSoftmaxMode
        Enumerant to specify the softmax mode.
    alpha: float
        Scaling factor with which every element of the input tensors is multiplied.
    srcDesc : cudnnTensorDescriptor
        Handle to the previously initialized input tensor descriptor.
    srcData : void_p
        Data pointer to GPU memory associated with the tensor descriptor
        srcDesc.
    beta: float
        Scaling factor which is applied on every element of the output tensor prior
        to adding the result of the activation Note that if beta is zero, the output
        is not read and can contain any uninitialized data (including Nan numbers).
    destDesc : cudnnTensorDescriptor
        Handle to the previously initialized output tensor descriptor.
    destData : void_p
        Data pointer to GPU memory associated with the output tensor descriptor
        destDesc.
    """

    dataType = cudnnGetTensor4dDescriptor(destDesc)[0]
    if dataType == cudnnDataType['CUDNN_DATA_DOUBLE']:
        alphaRef = ctypes.byref(ctypes.c_double(alpha))
        betaRef = ctypes.byref(ctypes.c_double(beta))
    else:
        alphaRef = ctypes.byref(ctypes.c_float(alpha))
        betaRef = ctypes.byref(ctypes.c_float(beta))

    status = _libcudnn.cudnnSoftmaxForward(handle, algorithm, mode, alphaRef,
                                        srcDesc, srcData, betaRef,
                                        destDesc, destData)
    cudnnCheckStatus(status)
This routing computes the softmax function

    Parameters
    ----------
    handle : cudnnHandle
        Handle to a previously created cuDNN context.
    algorithm : cudnnSoftmaxAlgorithm
        Enumerant to specify the softmax algorithm.
    mode : cudnnSoftmaxMode
        Enumerant to specify the softmax mode.
    alpha: float
        Scaling factor with which every element of the input tensors is multiplied.
    srcDesc : cudnnTensorDescriptor
        Handle to the previously initialized input tensor descriptor.
    srcData : void_p
        Data pointer to GPU memory associated with the tensor descriptor
        srcDesc.
    beta: float
        Scaling factor which is applied on every element of the output tensor prior
        to adding the result of the activation Note that if beta is zero, the output
        is not read and can contain any uninitialized data (including Nan numbers).
    destDesc : cudnnTensorDescriptor
        Handle to the previously initialized output tensor descriptor.
    destData : void_p
        Data pointer to GPU memory associated with the output tensor descriptor
        destDesc.