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Code Packages Releases Wiki Activity

Move Inference Engine to new API

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This commit is contained in:
Dmitry Kurtaev
2019-01-14 09:55:44 +03:00
parent 4ced27e149
commit f0ddf302b2
34 changed files with 852 additions and 80 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+77 -25
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@@ -451,6 +451,54 @@ public:
const int inpGroupCn = blobs[0].size[1];
const int group = inpCn / inpGroupCn;
auto ieWeights = wrapToInfEngineBlob(blobs[0], InferenceEngine::Layout::OIHW);
if (newWeightAndBias)
{
if (weightsMat.isContinuous())
{
Mat fusedWeights = weightsMat.reshape(1, blobs[0].dims, blobs[0].size);
ieWeights = wrapToInfEngineBlob(fusedWeights, InferenceEngine::Layout::OIHW);
}
else
{
ieWeights = InferenceEngine::make_shared_blob<float>(
InferenceEngine::Precision::FP32, InferenceEngine::Layout::OIHW,
ieWeights->dims());
ieWeights->allocate();
Mat newWeights = infEngineBlobToMat(ieWeights).reshape(1, outCn);
Mat fusedWeights = weightsMat.colRange(0, newWeights.cols);
fusedWeights.copyTo(newWeights);
}
}
InferenceEngine::Blob::Ptr ieBiases;
if (hasBias() || fusedBias)
{
Mat biasesMat({outCn}, CV_32F, &biasvec[0]);
ieBiases = wrapToInfEngineBlob(biasesMat, {(size_t)outCn}, InferenceEngine::Layout::C);
}
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
InferenceEngine::Builder::ConvolutionLayer ieLayer(name);
ieLayer.setKernel({kernel.height, kernel.width});
ieLayer.setStrides({stride.height, stride.width});
ieLayer.setDilation({dilation.height, dilation.width});
ieLayer.setPaddingsBegin({pad.height, pad.width});
ieLayer.setPaddingsEnd({pad.height, pad.width});
ieLayer.setGroup(group);
ieLayer.setOutDepth(outCn);
ieLayer.setWeights(ieWeights);
if (ieBiases)
ieLayer.setBiases(ieBiases);
InferenceEngine::Builder::Layer l = ieLayer;
if (!padMode.empty())
l.getParameters()["auto_pad"] = padMode == "VALID" ? std::string("valid") : std::string("same_upper");
return Ptr<BackendNode>(new InfEngineBackendNode(l));
#else
InferenceEngine::LayerParams lp;
lp.name = name;
lp.type = "Convolution";
@@ -487,32 +535,11 @@ public:
ieLayer->_out_depth = outCn;
ieLayer->_group = group;
ieLayer->_weights = wrapToInfEngineBlob(blobs[0], InferenceEngine::Layout::OIHW);
if (newWeightAndBias)
{
if (weightsMat.isContinuous())
{
Mat fusedWeights = weightsMat.reshape(1, blobs[0].dims, blobs[0].size);
ieLayer->_weights = wrapToInfEngineBlob(fusedWeights, InferenceEngine::Layout::OIHW);
}
else
{
ieLayer->_weights = InferenceEngine::make_shared_blob<float>(
InferenceEngine::Precision::FP32, InferenceEngine::Layout::OIHW,
ieLayer->_weights->dims());
ieLayer->_weights->allocate();
Mat newWeights = infEngineBlobToMat(ieLayer->_weights).reshape(1, outCn);
Mat fusedWeights = weightsMat.colRange(0, newWeights.cols);
fusedWeights.copyTo(newWeights);
}
}
if (hasBias() || fusedBias)
{
Mat biasesMat({outCn}, CV_32F, &biasvec[0]);
ieLayer->_biases = wrapToInfEngineBlob(biasesMat, {(size_t)outCn}, InferenceEngine::Layout::C);
}
ieLayer->_weights = ieWeights;
if (ieBiases)
ieLayer->_biases = ieBiases;
return Ptr<BackendNode>(new InfEngineBackendNode(ieLayer));
#endif
#endif // HAVE_INF_ENGINE
return Ptr<BackendNode>();
}
@@ -1123,6 +1150,9 @@ public:
#ifdef HAVE_INF_ENGINE
if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
{
if (INF_ENGINE_RELEASE == 2018050000 && (adjustPad.height || adjustPad.width))
return false;
const int outGroupCn = blobs[0].size[1]; // Weights are in IOHW layout
const int group = numOutput / outGroupCn;
if (group != 1)
@@ -1677,6 +1707,27 @@ public:
virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> > &) CV_OVERRIDE
{
#ifdef HAVE_INF_ENGINE
#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2018R5)
const int outGroupCn = blobs[0].size[1]; // Weights are in IOHW layout
const int group = numOutput / outGroupCn;
InferenceEngine::Builder::DeconvolutionLayer ieLayer(name);
ieLayer.setKernel({kernel.height, kernel.width});
ieLayer.setStrides({stride.height, stride.width});
ieLayer.setDilation({dilation.height, dilation.width});
ieLayer.setPaddingsBegin({pad.height, pad.width});
ieLayer.setPaddingsEnd({pad.height, pad.width});
ieLayer.setGroup(group);
ieLayer.setOutDepth(numOutput);
ieLayer.setWeights(wrapToInfEngineBlob(blobs[0], InferenceEngine::Layout::OIHW));
if (hasBias())
{
ieLayer.setBiases(wrapToInfEngineBlob(blobs[1], {(size_t)numOutput}, InferenceEngine::Layout::C));
}
return Ptr<BackendNode>(new InfEngineBackendNode(ieLayer));
#else
const int outGroupCn = blobs[0].size[1]; // Weights are in IOHW layout
const int group = numOutput / outGroupCn;
@@ -1716,6 +1767,7 @@ public:
ieLayer->_biases = wrapToInfEngineBlob(blobs[1], {(size_t)numOutput}, InferenceEngine::Layout::C);
}
return Ptr<BackendNode>(new InfEngineBackendNode(ieLayer));
#endif
#endif // HAVE_INF_ENGINE
return Ptr<BackendNode>();
}