mirror of https://github.com/alibaba/MNN.git
43 lines
1.3 KiB
C++
43 lines
1.3 KiB
C++
//
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// OneDNNConvInt8.hpp
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//
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//
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#ifndef OneDNNConvInt8_hpp
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#define OneDNNConvInt8_hpp
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#include "backend/cpu/CPUConvolution.hpp"
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#include "dnnl.hpp"
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using namespace dnnl;
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namespace MNN {
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class OneDNNConvInt8 : public CPUConvolution {
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public:
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struct Resource : public CPUConvolution::Resource {
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memory conv_weights;
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memory conv_bias;
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primitive_attr conv_attr;
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engine eng;
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};
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static Execution* create(Backend *backend, const MNN::Convolution2D *convOp, const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs);
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OneDNNConvInt8(std::shared_ptr<OneDNNConvInt8::Resource> resource, const MNN::Convolution2DCommon* common, Backend* bn);
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virtual ~OneDNNConvInt8();
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virtual ErrorCode onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override;
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virtual ErrorCode onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override;
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virtual bool onClone(Backend* bn, const Op* op, Execution** dst) override;
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private:
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std::shared_ptr<OneDNNConvInt8::Resource> mResource;
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stream stm;
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convolution_forward conv;
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std::shared_ptr<Tensor> mSrcTemp;
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std::shared_ptr<Tensor> mDstTemp;
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memory user_src;
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memory user_dst;
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memory conv_src;
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memory conv_dst;
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};
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} // namespace MNN
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#endif /* OneDNNConvInt8_hpp */
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