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Merge branch 'cnet' of https://github.com/ceccocats/tkDNN into cnet

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This commit is contained in:
Micaela Verucchi
2019-10-30 10:20:44 +01:00
parent 8b64d1876f d6d93a74f8
commit 6a1707f65e
9 changed files with 214 additions and 110 deletions
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src/NetworkRT.cpp
+17 -8
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@@ -162,7 +162,7 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Layer *l) {
if(type == LAYER_DENSE)
return convert_layer(input, (Dense*) l);
if(type == LAYER_CONV2D)
if(type == LAYER_CONV2D || type == LAYER_DECONV2D)
return convert_layer(input, (Conv2d*) l);
if(type == LAYER_POOLING)
return convert_layer(input, (Pooling*) l);
@@ -235,13 +235,22 @@ ILayer* NetworkRT::convert_layer(ITensor *input, Conv2d *l) {
else
b = { dtRT, nullptr, 0}; //on batchnorm bias are added later
// Add a convolution layer with 20 outputs and a 5x5 filter.
IConvolutionLayer *lRT = networkRT->addConvolution(*input,
l->outputs, DimsHW{l->kernelH, l->kernelW}, w, b);
checkNULL(lRT);
lRT->setStride(DimsHW{l->strideH, l->strideW});
lRT->setPadding(DimsHW{l->paddingH, l->paddingW});
ILayer *lRT = nullptr;
if(!l->deConv) {
IConvolutionLayer *lRTconv = networkRT->addConvolution(*input,
l->outputs, DimsHW{l->kernelH, l->kernelW}, w, b);
checkNULL(lRTconv);
lRTconv->setStride(DimsHW{l->strideH, l->strideW});
lRTconv->setPadding(DimsHW{l->paddingH, l->paddingW});
lRT = (ILayer*) lRTconv;
} else {
IDeconvolutionLayer *lRTconv = networkRT->addDeconvolution(*input,
l->outputs, DimsHW{l->kernelH, l->kernelW}, w, b);
checkNULL(lRTconv);
lRTconv->setStride(DimsHW{l->strideH, l->strideW});
lRTconv->setPadding(DimsHW{l->paddingH, l->paddingW});
lRT = (ILayer*) lRTconv;
}
if(l->batchnorm) {
Weights power{dtRT, power_b, l->outputs};