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Clone convolution layer weights only for fusion

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Dmitry Kurtaev 2019-01-29 14:29:47 +03:00
parent d998e70a25
commit ac262f5b5d
1 changed files with 5 additions and 1 deletions
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6
modules/dnn/src/layers/convolution_layer.cpp
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@ -278,7 +278,7 @@ public:
const int outCn = blobs[0].size[0]; const int outCn = blobs[0].size[0];
// prepare weightsMat where each row is aligned and has enough zero padding on the right to // prepare weightsMat where each row is aligned and has enough zero padding on the right to
// use vectorized (i.e. with intrinsics) loops without tail processing // use vectorized (i.e. with intrinsics) loops without tail processing
Mat wm = blobs[0].reshape(1, outCn).clone(); Mat wm = blobs[0].reshape(1, outCn);
if( wm.step1() % VEC_ALIGN != 0 ) if( wm.step1() % VEC_ALIGN != 0 )
{ {
int newcols = (int)alignSize(wm.step1(), VEC_ALIGN); int newcols = (int)alignSize(wm.step1(), VEC_ALIGN);
@ -371,6 +371,10 @@ public:
if (!w.empty()) if (!w.empty())
{ {
// Keep origin weights unchanged.
if (weightsMat.data == blobs[0].data)
weightsMat = weightsMat.clone();
Mat originWeights = blobs[0].reshape(1, outCn); Mat originWeights = blobs[0].reshape(1, outCn);
for (int i = 0; i < outCn; ++i) for (int i = 0; i < outCn; ++i)
{ {