mirror of https://github.com/alibaba/MNN.git
44 lines
1.6 KiB
C++
44 lines
1.6 KiB
C++
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//
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// ConvInt8TiledExecutor.hpp
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// MNN
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//
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// Created by MNN on 2019/5/17.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#ifndef ConvInt8TiledExecutor_hpp
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#define ConvInt8TiledExecutor_hpp
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#include "backend/cpu/CPUConvolution.hpp"
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#include "ConvInt8Winograd.hpp"
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#include "Int8FunctionsOpt.h"
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namespace MNN {
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class ConvInt8TiledExecutor : public CPUConvolution {
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public:
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// given weight+bias+scale, do post process
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ConvInt8TiledExecutor(Backend* backend, const Convolution2D* convOp, std::shared_ptr<ResourceInt8> res);
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// only given weight, not do post process
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ConvInt8TiledExecutor(Backend* backend, const Convolution2DCommon* common, std::shared_ptr<Tensor> weight, bool fastgemm);
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virtual ~ConvInt8TiledExecutor();
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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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ConvInt8TiledExecutor(Backend* backend, const Convolution2DCommon* common, const ConvInt8TiledExecutor& exe);
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ConvolutionCommon::Im2ColParameter mIm2ColParamter;
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int mTileCount;
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int mThreadNums;
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std::shared_ptr<Tensor> mTempIm2ColBuffer;
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decltype(CoreInt8Functions::Int8GemmKernel) mGemmKernel;
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bool mDoPostProcess = true; //whether quan post process (add bias, min/max then scale to int8)
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std::shared_ptr<CPUConvolution::ResourceInt8> mResource;
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friend class ConvInt8Winograd;
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};
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} // namespace MNN
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#endif /* ConvInt8TiledExecutor_hpp */
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