| public SetConvolutionNdDescriptor ( int arrayLength, int padA, int filterStrideA, int upscaleA, cudnnConvolutionMode mode, cudnnDataType dataType ) : void | ||
| arrayLength | int | Dimension of the convolution. |
| padA | int | Array of dimension arrayLength containing the zero-padding size /// for each dimension. For every dimension, the padding represents the /// number of extra zeros implicitly concatenated at the start and at the /// end of every element of that dimension. |
| filterStrideA | int | Array of dimension arrayLength containing the filter stride for each /// dimension. For every dimension, the fitler stride represents the number /// of elements to slide to reach the next start of the filtering window of /// the next point. |
| upscaleA | int | Array of dimension arrayLength containing the upscale factor for each dimension. |
| mode | cudnnConvolutionMode | Selects between CUDNN_CONVOLUTION and CUDNN_CROSS_CORRELATION. |
| dataType | cudnnDataType | Selects the datatype in which the computation will be done. |
| return | void | |
public void SetConvolutionNdDescriptor(int arrayLength, /* nbDims-2 size */
int[] padA,
int[] filterStrideA,
int[] upscaleA,
cudnnConvolutionMode mode, cudnnDataType dataType
)
{
res = CudaDNNNativeMethods.cudnnSetConvolutionNdDescriptor(_desc, arrayLength, padA, filterStrideA, upscaleA, mode, dataType);
Debug.WriteLine(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnSetConvolutionNdDescriptor", res));
if (res != cudnnStatus.Success) throw new CudaDNNException(res);
}