docs: 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)