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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin
2019-12-02 16:18:07 +03:00
parent 78c5e41c23 7523c777c5
commit 4b0132ed7a
51 changed files with 3276 additions and 496 deletions
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modules/dnn/src/layers/fully_connected_layer.cpp
+28 -1
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@@ -45,6 +45,8 @@
#include "../op_cuda.hpp"
#include "../op_halide.hpp"
#include "../op_inf_engine.hpp"
#include "../ie_ngraph.hpp"
#include <opencv2/dnn/shape_utils.hpp>
#ifdef HAVE_OPENCL
@@ -131,7 +133,7 @@ public:
return backendId == DNN_BACKEND_OPENCV ||
backendId == DNN_BACKEND_CUDA ||
(backendId == DNN_BACKEND_HALIDE && haveHalide() && axis == 1) ||
(backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine() && axis == 1);
((backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && haveInfEngine() && axis == 1);
}
virtual bool setActivation(const Ptr<ActivationLayer>& layer) CV_OVERRIDE
@@ -481,6 +483,31 @@ public:
}
#endif // HAVE_INF_ENGINE
#ifdef HAVE_DNN_NGRAPH
virtual Ptr<BackendNode> initNgraph(const std::vector<Ptr<BackendWrapper> >& inputs,
const std::vector<Ptr<BackendNode> >& nodes) CV_OVERRIDE
{
auto& ieInpNode = nodes[0].dynamicCast<InfEngineNgraphNode>()->node;
int batch = ieInpNode->get_shape()[0];
std::vector<size_t> data = {(size_t)batch, (size_t)blobs[0].size[1]};
auto new_shape = std::make_shared<ngraph::op::Constant>(ngraph::element::i64, ngraph::Shape{2}, data.data());
auto inp = std::make_shared<ngraph::op::v1::Reshape>(ieInpNode, new_shape, true);
std::vector<size_t> weight_shape{(size_t)blobs[0].size[0], (size_t)blobs[0].size[1]};
auto ieWeights = std::make_shared<ngraph::op::Constant>(ngraph::element::f32, weight_shape, blobs[0].data);
auto matmul = std::make_shared<ngraph::op::MatMul>(inp, ieWeights, false, true);
if (bias) {
auto bias_node = std::make_shared<ngraph::op::Constant>(ngraph::element::f32,
ngraph::Shape{(size_t)blobs[1].size[1]}, blobs[1].data);
auto fc = std::make_shared<ngraph::op::v1::Add>(matmul, bias_node, ngraph::op::AutoBroadcastType::NUMPY);
return Ptr<BackendNode>(new InfEngineNgraphNode(fc));
}
return Ptr<BackendNode>(new InfEngineNgraphNode(matmul));
}
#endif // HAVE_DNN_NGRAPH
virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
const std::vector<MatShape> &outputs) const CV_OVERRIDE
{