mirror of https://github.com/alibaba/MNN.git
64 lines
1.9 KiB
C++
64 lines
1.9 KiB
C++
//
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// ConvExecution.hpp
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// MNN
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//
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// Created by MNN on 2019/01/31.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#ifndef ConvExecution_hpp
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#define ConvExecution_hpp
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#include "Execution.hpp"
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#include <array>
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#include <functional>
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#include <memory>
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#include <vector>
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#include "core/OpenCLBackend.hpp"
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#include "core/OpenCLRunningUtils.hpp"
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namespace MNN {
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namespace OpenCL {
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class ConvCommonExecution : public Execution {
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public:
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ConvCommonExecution(const Convolution2D *op, Backend *backend);
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virtual ~ConvCommonExecution();
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protected:
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std::shared_ptr<Tensor> mBias;
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};
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class ConvExecution : public ConvCommonExecution {
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public:
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ConvExecution(const std::vector<Tensor *> &inputs, const MNN::Op *op, Backend *backend);
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virtual ~ConvExecution();
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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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static std::shared_ptr<Tensor> getBias(OpenCLBackend *backend, const Convolution2D *conv);
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std::vector<uint32_t> conv2d1x1LocalWS(std::vector<uint32_t> &gws, const uint32_t maxWorkGroupSize);
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std::vector<uint32_t> conv2dGeneralLocalWS(const std::vector<uint32_t> &gws, const uint32_t kernelSize,
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const uint32_t maxWorkGroupSize);
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private:
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const Convolution2DCommon *mConv2dCommonParams;
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std::vector<int> mStrides{1, 1};
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std::vector<int> mPaddings{0, 0};
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std::vector<int> mDilations{1, 1};
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std::vector<uint32_t> mGlobalWorkSize{1, 1, 1};
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std::vector<uint32_t> mLocalWorkSize{1, 1, 1, 1};
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std::shared_ptr<Tensor> mFilter;
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cl::Kernel mKernel;
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uint32_t mMaxWorkGroupSize;
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bool mIsTurn = false;
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OpenCLBackend *mOpenCLBackend;
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};
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} // namespace OpenCL
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} // namespace MNN
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#endif /* ConvExecution_hpp */
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