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dnn(IE): use HAVE_DNN_IE_NN_BUILDER_2019 for NN Builder API code

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- CMake option: OPENCV_DNN_IE_NN_BUILDER_2019
This commit is contained in:
Alexander Alekhin
2020-03-03 08:01:44 +00:00
parent 4d0f13544d
commit 124bf8339f
32 changed files with 351 additions and 146 deletions
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modules/dnn/src/layers/convolution_layer.cpp
+8 -5
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@@ -467,7 +467,7 @@ public:
return Ptr<BackendNode>();
}
#ifdef HAVE_INF_ENGINE
#ifdef HAVE_DNN_IE_NN_BUILDER_2019
virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> > &inputs) CV_OVERRIDE
{
InferenceEngine::DataPtr input = infEngineDataNode(inputs[0]);
@@ -528,7 +528,7 @@ public:
return Ptr<BackendNode>(new InfEngineBackendNode(l));
}
#endif // HAVE_INF_ENGINE
#endif // HAVE_DNN_IE_NN_BUILDER_2019
#ifdef HAVE_DNN_NGRAPH
virtual Ptr<BackendNode> initNgraph(const std::vector<Ptr<BackendWrapper> > &inputs,
@@ -1328,6 +1328,7 @@ public:
return group == 1;
}
#ifdef HAVE_DNN_IE_NN_BUILDER_2019
if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
{
if (kernel_size.size() == 3 && preferableTarget != DNN_TARGET_CPU) {
@@ -1371,9 +1372,11 @@ public:
return std::accumulate(dilations.begin(), dilations.end(), 1, std::multiplies<size_t>()) == 1;
return true;
}
else
#endif // HAVE_DNN_IE_NN_BUILDER_2019
#endif // HAVE_INF_ENGINE
{
return kernel_size.size() == 2 && (backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_HALIDE);
}
}
bool getMemoryShapes(const std::vector<MatShape> &inputs,
@@ -1952,7 +1955,7 @@ public:
return Ptr<BackendNode>();
}
#ifdef HAVE_INF_ENGINE
#ifdef HAVE_DNN_IE_NN_BUILDER_2019
virtual Ptr<BackendNode> initInfEngine(const std::vector<Ptr<BackendWrapper> > &) CV_OVERRIDE
{
InferenceEngine::Layout layout = blobs[0].dims == 5? InferenceEngine::Layout::NCDHW :
@@ -2007,7 +2010,7 @@ public:
addConstantData("biases", wrapToInfEngineBlob(biasesMat, {(size_t)numOutput}, InferenceEngine::Layout::C), l);
return Ptr<BackendNode>(new InfEngineBackendNode(l));
}
#endif // HAVE_INF_ENGINE
#endif // HAVE_DNN_IE_NN_BUILDER_2019
#ifdef HAVE_DNN_NGRAPH