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Add grouped convolutions in CUDNN and tensorRT.

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Signed-off-by: Davide Sapienza <sapienza.dav@gmail.com>
This commit is contained in:
Davide Sapienza
2020-02-05 14:32:58 +01:00
parent fe85c26888
commit 4616be0738
5 changed files with 25 additions and 15 deletions
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src/Conv2d.cpp
+9 -7
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@@ -17,8 +17,6 @@ void Conv2d::initCUDNN(bool back) {
idim = output_dim;
odim = input_dim;
}
//idim.print();
//odim.print();
checkCUDNN( cudnnCreateFilterDescriptor(&filterDesc) );
checkCUDNN( cudnnCreateConvolutionDescriptor(&convDesc) );
@@ -29,7 +27,7 @@ void Conv2d::initCUDNN(bool back) {
net->tensorFormat, net->dataType, idim.n, idim.c, idim.h, idim.w) );
checkCUDNN( cudnnSetFilter4dDescriptor(filterDesc,
net->dataType, net->tensorFormat, odim.c, idim.c,
net->dataType, net->tensorFormat, odim.c, idim.c/groups,
kernelH, kernelW) );
checkCUDNN( cudnnSetConvolution2dDescriptor(convDesc,
@@ -38,16 +36,20 @@ void Conv2d::initCUDNN(bool back) {
1,1, // upscale
CUDNN_CROSS_CORRELATION, CUDNN_DATA_FLOAT) );
checkCUDNN( cudnnSetConvolutionGroupCount(convDesc,
groups) );
// check dimension of convolution output
dataDim_t tmpdim;
checkCUDNN( cudnnGetConvolution2dForwardOutputDim(
convDesc, srcTensor, filterDesc,
&tmpdim.n, &tmpdim.c, &tmpdim.h, &tmpdim.w) );
if(odim.n != tmpdim.n || odim.c != tmpdim.c || odim.h != tmpdim.h || odim.w != tmpdim.w) {
std::cout<<"tkdim input: "; idim.print();
std::cout<<"tkdim output: "; odim.print();
std::cout<<"cudnndim: "; tmpdim.print();
FatalError("Eror conv dimension mismatch");
FatalError("Error conv dimension mismatch");
}
checkCUDNN( cudnnSetTensor4dDescriptor(dstTensor,
@@ -119,11 +121,10 @@ void Conv2d::inferCUDNN(dnnType* srcData, bool back) {
Conv2d::Conv2d( Network *net, int out_ch, int kernelH, int kernelW,
int strideH, int strideW, int paddingH, int paddingW,
std::string fname_weights, bool batchnorm, bool deConv, bool final) :
std::string fname_weights, bool batchnorm, bool deConv, bool final, int groups) :
LayerWgs(net, net->getOutputDim().c, out_ch, kernelH, kernelW, 1,
fname_weights, batchnorm, false, final) {
fname_weights, batchnorm, false, final, deConv, groups) {
this->kernelH = kernelH;
this->kernelW = kernelW;
this->strideH = strideH;
@@ -131,6 +132,7 @@ Conv2d::Conv2d( Network *net, int out_ch, int kernelH, int kernelW,
this->paddingH = paddingH;
this->paddingW = paddingW;
this->deConv = deConv;
this->groups = groups;
if(!deConv) {
output_dim.n = input_dim.n;