docs: def cudnnSetConvolution2dDescriptor(convDesc, pad_h, pad_w, u, v, dilation_h, dilation_w, mode,
                                      computeType):
      """"
      Initialize a convolution descriptor.
  
      This function initializes a previously created convolution descriptor object into a 2D
      correlation. This function assumes that the tensor and filter descriptors corresponds
      to the formard convolution path and checks if their settings are valid. That same
      convolution descriptor can be reused in the backward path provided it corresponds to
      the same layer.
  
      Parameters
      ----------
      convDesc : cudnnConvolutionDescriptor
          Handle to a previously created convolution descriptor.
      pad_h : int
          zero-padding height: number of rows of zeros implicitly concatenated
          onto the top and onto the bottom of input images.
      pad_w : int
          zero-padding width: number of columns of zeros implicitly concatenated
          onto the left and onto the right of input images.
      u : int
          Vertical filter stride.
      v : int
          Horizontal filter stride.
      dilation_h : int
          Filter height dilation.
      dilation_w : int
          Filter width dilation.
      mode : cudnnConvolutionMode
          Select between CUDNN_CONVOLUTION or CUDNN_CROSS_CORRELATION.
      computeType : cudnnDataType
          Compute precision
      """
  
      status = _libcudnn.cudnnSetConvolution2dDescriptor(convDesc, pad_h, pad_w, u, v,
                                                          dilation_h, dilation_w, mode,
                                                          computeType)
      cudnnCheckStatus(status)