mirror of https://github.com/alibaba/MNN.git
95 lines
3.8 KiB
C++
95 lines
3.8 KiB
C++
//
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// CPUConvolutionDepthwise.hpp
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// MNN
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//
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// Created by MNN on 2018/07/20.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#ifndef CPUConvolutionDepthwise_hpp
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#define CPUConvolutionDepthwise_hpp
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#include "core/AutoStorage.h"
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#include "backend/cpu/CPUConvolution.hpp"
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#include "backend/cpu/compute/ConvolutionIntFactory.hpp"
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namespace MNN {
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class CPUConvolutionDepthwise : public Execution {
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public:
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class BasicFloatExecution : public CPUConvolution {
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public:
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BasicFloatExecution(const Convolution2DCommon *common, Backend *b) : CPUConvolution(common, b) {
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}
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virtual ~BasicFloatExecution() = default;
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virtual ErrorCode onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override;
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virtual ErrorCode onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override;
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private:
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std::function<void(const float *, float *, int)> mExecutor;
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int mNumber = 1;
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};
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class MultiInputFloatExecution : public BasicFloatExecution {
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public:
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MultiInputFloatExecution(const Convolution2DCommon *common, Backend *b) : BasicFloatExecution(common, b) {
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}
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virtual ~MultiInputFloatExecution() = default;
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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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private:
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std::unique_ptr<Tensor> mWeight;
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std::unique_ptr<Tensor> mBias;
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std::vector<Tensor *> mTempInputs;
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};
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class FloatExecution : public CPUConvolution {
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public:
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FloatExecution(const Convolution2DCommon *common, Backend *b, const float *originWeight,
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size_t originWeightSize, const float *bias, size_t biasSize);
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virtual ~FloatExecution();
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virtual ErrorCode onExecute(const std::vector<Tensor *> &inputs,
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const std::vector<Tensor *> &outputs) override {
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return mOrigin->onExecute(mTempInputs, outputs);
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}
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virtual ErrorCode onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override {
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mTempInputs = {inputs[0], mWeight.get(), mBias.get()};
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return mOrigin->onResize(mTempInputs, outputs);
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}
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private:
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std::unique_ptr<Tensor> mWeight;
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std::unique_ptr<Tensor> mBias;
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std::vector<Tensor *> mTempInputs;
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std::unique_ptr<BasicFloatExecution> mOrigin;
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};
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class Int8Execution : public CPUConvolution {
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public:
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Int8Execution(const Convolution2DCommon *convOp, Backend *b, const ConvolutionIntFactory::Int8Common *common,
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const float *bias, size_t biasSize);
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virtual ~Int8Execution() = default;
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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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private:
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AutoStorage<int8_t> mWeight;
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AutoStorage<float> mBias;
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AutoStorage<float> mAlpha;
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float mQuanScale[4];
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Tensor mInputTempBuffer;
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const IDSTQuan *mQuan;
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std::function<void()> mRun;
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};
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CPUConvolutionDepthwise(const Op *convOp, Backend *b);
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virtual ~CPUConvolutionDepthwise() = default;
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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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private:
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std::unique_ptr<Execution> mSubExecution;
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};
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} // namespace MNN
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#endif /* CPUConvolutionDepthwise_hpp */
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