Library/ManagedCuda/CudaDNN/CudaDNNNativeMethods.cs
/// <summary>
/// This function initializes a previously created generic convolution descriptor object into
/// a n-D correlation. That same convolution descriptor can be reused in the backward path
/// provided it corresponds to the same layer. The convolution computation will done in the
/// specified dataType, which can be potentially different from the input/output tensors.
/// </summary>
/// <param name="convDesc">Handle to a previously created convolution descriptor.</param>
/// <param name="arrayLength">Dimension of the convolution.</param>
/// <param name="padA">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.</param>
/// <param name="filterStrideA">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.</param>
/// <param name="dilationA">Array of dimension arrayLength containing the dilation factor for each dimension.</param>
/// <param name="mode">Selects between CUDNN_CONVOLUTION and CUDNN_CROSS_CORRELATION.</param>
/// <param name="computeType">Selects the datatype in which the computation will be done.</param>
This function initializes a previously created generic convolution descriptor object into
a n-D correlation. That same convolution descriptor can be reused in the backward path
provided it corresponds to the same layer. The convolution computation will done in the
specified dataType, which can be potentially different from the input/output tensors.
This function initializes a previously created generic convolution descriptor object into a n - D correlation . That same convolution descriptor can be reused in the backward path provided it corresponds to the same layer . The convolution computation will done in the specified dataType which can be potentially different from the input / output tensors .
[DllImport(CUDNN_API_DLL_NAME)]  
		public static extern cudnnStatus cudnnSetConvolutionNdDescriptor(cudnnConvolutionDescriptor convDesc,
                                                              int arrayLength,               
                                                              int[] padA,                                          
                                                              int[] filterStrideA,         
                                                              int[] dilationA,              
                                                              cudnnConvolutionMode mode,
                                                              cudnnDataType computeType   
                                                         );
[ DllImport ( CUDNN_API_DLL_NAME ) ] public static extern cudnnStatus cudnnSetConvolutionNdDescriptor ( cudnnConvolutionDescriptor convDesc , int arrayLength , int [ ] padA , int [ ] filterStrideA , int [ ] dilationA , cudnnConvolutionMode mode , cudnnDataType computeType ) ;
This function initializes a previously created generic convolution descriptor object into
a n-D correlation.
This function initializes a previously created generic convolution descriptor object into a n - D correlation .
/* nbDims-2 size */ // convolution data type
convDesc
cudnnConvolutionDescriptor
Handle to a previously created convolution descriptor.
Handle to a previously created convolution descriptor .
arrayLength
int
Dimension of the convolution.
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.
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.
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 .
dilationA
int[]
Array of dimension arrayLength containing the dilation factor for each dimension.
Array of dimension arrayLength containing the dilation factor for each dimension .
mode
cudnnConvolutionMode
Selects between CUDNN_CONVOLUTION and CUDNN_CROSS_CORRELATION.
Selects between CUDNN_CONVOLUTION and CUDNN_CROSS_CORRELATION .
computeType
cudnnDataType
Selects the datatype in which the computation will be done.
Selects the datatype in which the computation will be done .