MNN/source/backend/cpu/compute/ConvolutionTiledExecutor.hpp

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//
// ConvolutionTiledExecutor.hpp
// MNN
//
// Created by MNN on 2018/07/16.
// Copyright © 2018, Alibaba Group Holding Limited
//
#ifndef ConvolutionTiledExecutor_hpp
#define ConvolutionTiledExecutor_hpp
#include <functional>
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#include "backend/cpu/CPUConvolution.hpp"
- build: - unify schema building in core and converter; - add more build script for android; - add linux build script for python; - ops impl: - add floor mod support in binary; - use eltwise impl in add/max/sub/mul binary for optimization; - remove fake double support in cast; - fix 5d support for concat; - add adjX and adjY support for batch matmul; - optimize conv2d back prop filter; - add pad mode support for conv3d; - fix bug in conv2d & conv depthwise with very small feature map; - optimize binary without broacast; - add data types support for gather; - add gather ND support; - use uint8 data type in gather v2; - add transpose support for matmul; - add matrix band part; - add dim != 4 support for padding, reshape & tensor convert; - add pad type support for pool3d; - make ops based on TensorFlow Lite quantization optional; - add all & any support for reduction; - use type in parameter as output type in reduction; - add int support for unary; - add variable weight support for conv2d; - fix conv2d depthwise weights initialization; - fix type support for transpose; - fix grad outputs count for reduce grad and reshape grad; - fix priorbox & detection output; - fix metal softmax error; - python: - add runSessionWithCallBackInfo interface; - add max nodes limit (1400) for visualization tool; - fix save error in python3; - align default dim; - convert: - add extra design for optimization; - add more post converting optimizers; - add caffe v1 weights blob support; - add cast, unary, conv transpose support for onnx model; - optimize batchnorm, conv with variable weights, prelu, reshape, slice, upsample for onnx model; - add cos/sin/atan/tan support for unary for tensorflow model; - add any/all support for reduction for tensorflow model; - add elu, conv3d, pool3d support for tensorflow model; - optimize argmax, batchnorm, concat, batch to space, conv with variable weights, prelu, slice for tensorflow model; - others: - fix size computer lock; - fix thread pool deadlock; - add express & parameters in express; - rewrite blitter chooser without static map; - add tests for expr;
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// Tiled Slide Window or Im2Col + GEMM
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namespace MNN {
class ConvolutionTiledExecutorBasic : public CPUConvolution {
public:
ConvolutionTiledExecutorBasic(const Convolution2DCommon *common, Backend *b) : CPUConvolution(common, b) {
}
virtual ~ConvolutionTiledExecutorBasic() = default;
virtual ErrorCode onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override;
virtual ErrorCode onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override;
protected:
Tensor mTempBuffer;
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Tensor mTempBufferTranspose;
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std::pair<int, std::function<void(int)>> mFunction;
};
class ConvolutionTiledExecutorMultiInput : public Execution {
public:
ConvolutionTiledExecutorMultiInput(const Convolution2DCommon *common, Backend *b) : Execution(b) {
mProxy.reset(new ConvolutionTiledExecutorBasic(common, b));
}
virtual ~ConvolutionTiledExecutorMultiInput() = default;
virtual ErrorCode onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override;
virtual ErrorCode onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override;
private:
std::shared_ptr<Tensor> mTempWeight;
std::shared_ptr<Tensor> mTempWeightCache;
std::shared_ptr<Tensor> mTempBias;
std::shared_ptr<ConvolutionTiledExecutorBasic> mProxy;
std::vector<Tensor *> mInputs;
};
class ConvolutionTiledExecutor : public Execution {
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public:
ConvolutionTiledExecutor(const Convolution2DCommon *common, Backend *b, const float *originWeight,
size_t originWeightSize, const float *bias, size_t biasSize);
ConvolutionTiledExecutor(const Convolution2DCommon *common,
const RearrangedWeightParam *rearranged_params,
Backend *b, const float *originWeight,
size_t originWeightSize, const float *bias,
size_t biasSize);
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virtual ~ConvolutionTiledExecutor();
virtual ErrorCode onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override {
return mProxy->onExecute(inputs, outputs);
}
virtual ErrorCode onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override {
mInputs = {inputs[0], mWeight.get(), mBias.get()};
return mProxy->onResize(mInputs, outputs);
}
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virtual std::vector<MNN::RearrangedType> RearrangedTypes() const override {
return std::vector<MNN::RearrangedType>{RearrangedType_RT_CONVOLUTION_GENERIC};
}
virtual std::vector<std::shared_ptr<Tensor>> RearrangedWeights() const override {
return std::vector<std::shared_ptr<Tensor>>{mWeight};
}
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protected:
std::shared_ptr<Tensor> mWeight;
std::shared_ptr<Tensor> mBias;
std::shared_ptr<ConvolutionTiledExecutorBasic> mProxy;
std::vector<Tensor *> mInputs;
bool mBorrowedWeight = false;
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};
} // namespace MNN
#endif /* ConvolutionTiledExecutor_hpp */