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Merge remote-tracking branch 'upstream/3.4' into merge-3.4
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@@ -278,11 +278,28 @@ void InfEngineBackendNet::connect(const std::vector<Ptr<BackendWrapper> >& input
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{
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const auto& inp = inpWrappers[i];
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const std::string& inpName = inp->dataPtr->getName();
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std::string inpLayerName = inpName;
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size_t inpPortId = inpName.rfind('.');
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if (inpPortId != std::string::npos)
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{
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std::string portIdStr = inpName.substr(inpPortId + 1);
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if (std::all_of(portIdStr.begin(), portIdStr.end(), ::isdigit))
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{
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inpLayerName = inpName.substr(0, inpPortId);
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inpPortId = atoi(portIdStr.c_str());
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}
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else
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inpPortId = 0;
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}
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else
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inpPortId = 0;
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int inpId;
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it = layers.find(inpName);
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it = layers.find(inpLayerName);
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if (it == layers.end())
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{
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InferenceEngine::Builder::InputLayer inpLayer(!inpName.empty() ? inpName : kDefaultInpLayerName);
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InferenceEngine::Builder::InputLayer inpLayer(!inpLayerName.empty() ? inpLayerName : kDefaultInpLayerName);
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std::vector<size_t> shape(inp->blob->getTensorDesc().getDims());
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inpLayer.setPort(InferenceEngine::Port(shape));
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inpId = netBuilder.addLayer(inpLayer);
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@@ -292,24 +309,28 @@ void InfEngineBackendNet::connect(const std::vector<Ptr<BackendWrapper> >& input
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else
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inpId = it->second;
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netBuilder.connect((size_t)inpId, {(size_t)layerId, i});
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unconnectedLayersIds.erase(inpId);
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netBuilder.connect({(size_t)inpId, inpPortId}, {(size_t)layerId, i});
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unconnectedPorts.erase({inpId, inpPortId});
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}
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CV_Assert(!outputs.empty());
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InferenceEngine::DataPtr dataPtr = infEngineDataNode(outputs[0]);
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for (int i = 0; i < outputs.size(); ++i)
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{
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InferenceEngine::DataPtr dataPtr = infEngineDataNode(outputs[i]);
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std::string outputName = outputs.size() > 1 ? (layerName + "." + std::to_string(i)) : layerName;
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#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2019R1)
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dataPtr->name = layerName;
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dataPtr->name = outputName;
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#else
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dataPtr->setName(layerName);
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dataPtr->setName(outputName);
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#endif
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}
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}
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void InfEngineBackendNet::init(Target targetId)
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{
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if (!hasNetOwner)
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{
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CV_Assert(!unconnectedLayersIds.empty());
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for (int id : unconnectedLayersIds)
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CV_Assert(!unconnectedPorts.empty());
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for (const auto& port : unconnectedPorts)
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{
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InferenceEngine::Builder::OutputLayer outLayer("myconv1");
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#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
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@@ -320,7 +341,7 @@ void InfEngineBackendNet::init(Target targetId)
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InferenceEngine::Precision::FP32;
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outLayer.setPort(InferenceEngine::Port({}, p));
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#endif
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netBuilder.addLayer({InferenceEngine::PortInfo(id)}, outLayer);
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netBuilder.addLayer({InferenceEngine::PortInfo(port.first, port.second)}, outLayer);
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}
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netBuilder.getContext().addShapeInferImpl(kOpenCVLayersType,
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std::make_shared<InfEngineCustomLayerShapeInfer>());
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@@ -409,8 +430,10 @@ void InfEngineBackendNet::addLayer(InferenceEngine::Builder::Layer& layer)
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int id = netBuilder.addLayer(layer);
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const std::string& layerName = layer.getName();
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CV_Assert(layers.insert({layerName, id}).second);
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unconnectedLayersIds.insert(id);
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for (int i = 0; i < layer.getOutputPorts().size(); ++i)
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unconnectedPorts.insert({id, i});
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#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2019R1)
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// By default, all the weights are connected to last ports ids.
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