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Clone convolution layer weights only for fusion
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@ -278,7 +278,7 @@ public:
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const int outCn = blobs[0].size[0];
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// prepare weightsMat where each row is aligned and has enough zero padding on the right to
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// use vectorized (i.e. with intrinsics) loops without tail processing
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Mat wm = blobs[0].reshape(1, outCn).clone();
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Mat wm = blobs[0].reshape(1, outCn);
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if( wm.step1() % VEC_ALIGN != 0 )
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{
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int newcols = (int)alignSize(wm.step1(), VEC_ALIGN);
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@ -371,6 +371,10 @@ public:
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if (!w.empty())
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{
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// Keep origin weights unchanged.
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if (weightsMat.data == blobs[0].data)
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weightsMat = weightsMat.clone();
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Mat originWeights = blobs[0].reshape(1, outCn);
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for (int i = 0; i < outCn; ++i)
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{
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