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Fix weights fusion for Convolution and Deconvolution layers in nGraph

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This commit is contained in:
Dmitry Kurtaev 2019-12-09 19:06:47 +03:00
parent a011035ed6
commit c2ca3ee2fa
1 changed files with 5 additions and 5 deletions
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10
modules/dnn/src/layers/convolution_layer.cpp
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@ -553,10 +553,10 @@ public:
}
else
{
Mat newWeights = blobs[0].reshape(1, outCn);
Mat cvWeights = weightsMat.colRange(0, newWeights.cols);
Mat newWeights;
Mat cvWeights = weightsMat.colRange(0, blobs[0].total() / outCn);
cvWeights.copyTo(newWeights);
ieWeights = std::make_shared<ngraph::op::Constant>(ngraph::element::f32, kernel_shape, blobs[0].data);
ieWeights = std::make_shared<ngraph::op::Constant>(ngraph::element::f32, kernel_shape, newWeights.data);
}
}
@ -2033,9 +2033,9 @@ public:
if (fusedWeights)
{
int inpCn = blobs[0].size[0];
Mat newWeights = blobs[0].reshape(1, inpCn);
Mat newWeights;
transpose(weightsMat, newWeights);
ieWeights = std::make_shared<ngraph::op::Constant>(ngraph::element::f32, kernel_shape, newWeights.data);
}
size_t batch = ieInpNode->get_shape()[0];
std::vector<size_t> out_shape = {batch, (size_t)numOutput};