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dnn(IE): use HAVE_DNN_IE_NN_BUILDER_2019 for NN Builder API code
- CMake option: OPENCV_DNN_IE_NN_BUILDER_2019
This commit is contained in:
committed by
Alexander Alekhin
parent
db5f1c3554
commit
29d214474f
@@ -622,7 +622,7 @@ public:
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return Ptr<BackendNode>();
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}
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#ifdef HAVE_INF_ENGINE
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#ifdef HAVE_DNN_IE_NN_BUILDER_2019
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virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
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{
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InferenceEngine::DataPtr input = infEngineDataNode(inputs[0]);
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@@ -683,7 +683,7 @@ public:
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return Ptr<BackendNode>(new InfEngineBackendNode(l));
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}
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#endif // HAVE_INF_ENGINE
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#endif // HAVE_DNN_IE_NN_BUILDER_2019
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#ifdef HAVE_DNN_NGRAPH
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virtual Ptr<BackendNode> initNgraph(const std::vector<Ptr<BackendWrapper> > &inputs,
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@@ -1558,6 +1558,7 @@ public:
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return group == 1;
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}
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#ifdef HAVE_DNN_IE_NN_BUILDER_2019
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if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
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{
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if (kernel_size.size() == 3 && preferableTarget != DNN_TARGET_CPU) {
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@@ -1601,10 +1602,12 @@ public:
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return std::accumulate(dilations.begin(), dilations.end(), 1, std::multiplies<size_t>()) == 1;
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return true;
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}
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else
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#endif // HAVE_DNN_IE_NN_BUILDER_2019
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#endif // HAVE_INF_ENGINE
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{
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return backendId == DNN_BACKEND_CUDA ||
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(kernel_size.size() == 2 && (backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE));
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}
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}
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bool getMemoryShapes(const std::vector<MatShape> &inputs,
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@@ -2244,7 +2247,7 @@ public:
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return Ptr<BackendNode>();
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}
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#ifdef HAVE_INF_ENGINE
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#ifdef HAVE_DNN_IE_NN_BUILDER_2019
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virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> > &) CV_OVERRIDE
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{
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InferenceEngine::Layout layout = blobs[0].dims == 5? InferenceEngine::Layout::NCDHW :
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@@ -2299,7 +2302,7 @@ public:
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addConstantData("biases", wrapToInfEngineBlob(biasesMat, {(size_t)numOutput}, InferenceEngine::Layout::C), l);
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return Ptr<BackendNode>(new InfEngineBackendNode(l));
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}
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#endif // HAVE_INF_ENGINE
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#endif // HAVE_DNN_IE_NN_BUILDER_2019
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#ifdef HAVE_DNN_NGRAPH
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