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dnn(ocl): avoid mess FP16/FP32 in convolution layer

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This commit is contained in:
Alexander Alekhin
2020-12-15 01:34:20 +00:00
parent 1bfc75ac23
commit c240355cc6
6 changed files with 77 additions and 61 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+13 -13
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@@ -1461,16 +1461,7 @@ public:
umat_blobs.resize(n);
for (size_t i = 0; i < n; i++)
{
if (use_half)
{
Mat matFP32;
convertFp16(inputs[i + 1], matFP32);
matFP32.copyTo(umat_blobs[i]);
}
else
{
inputs[i + 1].copyTo(umat_blobs[i]);
}
inputs[i + 1].copyTo(umat_blobs[i]);
}
inputs.resize(1);
}
@@ -1481,7 +1472,10 @@ public:
umat_blobs.resize(n);
for (size_t i = 0; i < n; i++)
{
blobs[i].copyTo(umat_blobs[i]);
if (use_half)
convertFp16(blobs[i], umat_blobs[i]);
else
blobs[i].copyTo(umat_blobs[i]);
}
}
@@ -1537,14 +1531,20 @@ public:
if (fusedWeights)
{
weightsMat.copyTo(umat_blobs[0]);
if (use_half)
convertFp16(weightsMat, umat_blobs[0]);
else
weightsMat.copyTo(umat_blobs[0]);
fusedWeights = false;
}
if (fusedBias)
{
if ( umat_blobs.size() < 2 )
umat_blobs.resize(2);
umat_blobs[1] = UMat(biasvec, true);
if (use_half)
convertFp16(Mat(biasvec, true), umat_blobs[1]);
else
Mat(biasvec, true).copyTo(umat_blobs[1]);
convolutionOp->setBias(true);
fusedBias = false;
}