source/backend/cpu/compute/CommonOptFunction.h (277 lines of code) (raw):
//
// CommonOptFunction.h
// MNN
//
// Created by MNN on 2018/07/16.
// Copyright © 2018, Alibaba Group Holding Limited
//
#ifndef CommonOptFunction_h
#define CommonOptFunction_h
#include <stdint.h>
#include <stdio.h>
#include <string.h>
#include <vector>
#include <MNN/Rect.h>
#include "core/Macro.h"
#include "backend/cpu/compute/Int8FunctionsOpt.h"
extern "C" {
#ifdef MNN_LOW_MEMORY
#ifdef __aarch64__
void MNNGeneralIm2col_Fp32Arm82(float* destOrigin, float const** sourceGroup, const int32_t* info, const int32_t* el, int32_t LP, int32_t pack);
void MNNGeneralIm2col_Fp32Arm86(float* destOrigin, float const** sourceGroup, const int32_t* info, const int32_t* el, int32_t LP, int32_t pack);
void MNNLocalMinMaxFP32_Pack4(float* dstMin, float* dstMax, const float* source, size_t blockNum, size_t blockLU, size_t EP, size_t LP, size_t loadDstBuffer);
void MNNLocalMinMaxFP32_Pack8(float* dstMin, float* dstMax, const float* source, size_t blockNum, size_t blockLU, size_t EP, size_t LP, size_t loadDstBuffer);
void MNNDynamicQuantFP32_Pack4(const float* src, int8_t* dst, const float* scale, size_t src_depth_quad, size_t realSize, const float* bias, size_t pack);
void MNNDynamicQuantFP32_Pack8(const float* src, int8_t* dst, const float* scale, size_t src_depth_quad, size_t realSize, const float* bias, size_t pack);
void MNNAbsMaxFP32_Pack4(const float* source, float* absmax, size_t src_depth_quad, size_t realSize, int pack);
void MNNAbsMaxFP32_Pack8(const float* source, float* absmax, size_t src_depth_quad, size_t realSize, int pack);
void MNNQuantScaleFP32(float* absmax, float* quant_scale, float* dequant_scale, size_t thread, size_t batch);
void MNNDynamicUpdateConvBiasScale(float* newbias, float* oldbias, float* weightKernelSum, float* inputZero, size_t ocQuad);
#endif
#endif
void MNNFp32ToFp8(uint8_t* dst, const float* src, size_t size);
void MNNFp8ToFp32(float* dst, const uint8_t* src, size_t size);
void MNNFp16ToFp8(uint8_t* dst, const uint16_t* src, size_t size);
void MNNFp8ToFp16(uint16_t* dst, const uint8_t* src, size_t size);
void MNNReluWithSlope(float* dst, const float* src, size_t sizeQuad, float slope);
void MNNReluInt8(int8_t* dst, const int8_t* src, size_t size, ssize_t zeroPoint);
void MNNReluWithSlopeChannel(float* dst, const float* src, const float* slope, size_t sizeQuad, size_t depthQuad);
void MNNHardSwish(float* dst, const float* src, size_t size);
void MNNGelu(float* dst, const float* src, size_t size, float* parameters);
void MNNPackC4(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void MNNPackC4Origin(float* dst, const float* src, size_t area, size_t depth, int areaOffset);
void MNNPackC2(double* dst, const double* src, size_t area, size_t depth, int* areaOffset);
void MNNPackC2Origin(double* dst, const double* src, size_t area, size_t depth, int areaOffset);
void MNNPackInt8C2(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void MNNPackInt8C2Origin(float* dst, const float* src, size_t area, size_t depth, int areaOffset);
void MNNPackC4Int16(int16_t* dst, const int16_t* src, size_t area,size_t depth, int* areaOffset);
void MNNPackC4Uint8(uint8_t* dst, const uint8_t* src, size_t area,size_t depth, int* areaOffset);
void MNNUnpackC4(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void MNNUnpackC4Origin(float* dst, const float* src, size_t area, size_t depth, int areaOffset);
void MNNUnpackC2(double* dst, const double* src, size_t area, size_t depth, int* areaOffset);
void MNNUnpackC2Origin(double* dst, const double* src, size_t area, size_t depth, int areaOffset);
void MNNUnpackC2Float(float* dst, const float* src, size_t area, size_t depth, int* areaOffset, int pack = 1);
void MNNUnpackInt8C2(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void MNNUnpackInt8C2Origin(float* dst, const float* src, size_t area, size_t depth, int areaOffset);
void MNNUnpackC4Int16(int16_t* dst, const int16_t* src, size_t area,size_t depth, int* areaOffset);
void MNNUnpackC4Uint8(uint8_t* dst, const uint8_t* src, size_t area,size_t depth, int* areaOffset);
void MNNScaleAndAddBias(float* dst, const float* src, const float* bias, const float* alpha, size_t planeNumber,
size_t biasNumber);
void MNNScaleAndAddBiasScalar(float* dst, const float* src, float bias, float alpha, size_t number);
// TODO: Swap the name for MNNUnpackTranspose and MNNPackTranspose
void MNNUnpackTranspose(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void MNNUnpackTransposeInt16(int16_t* dst, const int16_t* src, size_t area,size_t depth, int* areaOffset);
void MNNUnpackTransposeUint8(uint8_t* dst, const uint8_t* src, size_t area,size_t depth, int* areaOffset);
void MNNPackTranspose(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void MNNPackTransposeInt16(int16_t* dst, const int16_t* src, size_t area,size_t depth, int* areaOffset);
void MNNPackTransposeUint8(uint8_t* dst, const uint8_t* src, size_t area,size_t depth, int* areaOffset);
void MNNCopyC4WithStride(const float* source, float* dest, size_t srcStride, size_t dstStride, size_t count);
void MNNAddC4WithStride(const float* source, float* dest, size_t srcStride, size_t dstStride, size_t count);
void MNNUInt8ToInt16WithOffsetC4Common(int16_t* dst, const uint8_t* src, size_t zeroPoint, size_t sizeQuad,
size_t dstStride, size_t srcStride);
void MNNUInt8ToInt16WithOffsetC4Fast(int16_t* dst, const uint8_t* src, size_t zeroPoint, size_t sizeQuad,
size_t depthQuad, size_t dstZStep, size_t srcZStep);
void MNNMaxFloat(float* input, float* maxBuffer, int32_t inputCountUnit);
void MNNMinFloat(float* input, float* maxBuffer, int32_t inputCountUnit);
void MNNPowC8(float* dest, const float* source, const float* powfParam, size_t betaInt, size_t countC8);
void MNNExpC8(float* dest, const float* source, float* offset, const float* parameters, size_t countC8);
// Offset: o0, o1, o2, o3: dst = exp(src*o0+o2)+o1, o3 = o3+sum(dst)
void MNNExp(float* dst, const float* src, float* offset, size_t dataSize);
void MNNSin(float* dst, const float* src, size_t dataSize);
void MNNTanh(float* dst, const float* src, size_t dataSize);
void MNNSigmoid(float* dst, const float* src, size_t dataSize);
void MNNSigmoidLowp(float* dst, const float* src, size_t dataSize);
void MNNSiLu(float* dst, const float* src, size_t dataSize);
void MNNSiLuLowp(float* dst, const float* src, size_t dataSize);
void MNNReluWithSlopeCommon(float* dst, const float* src, size_t size, float slope);
void MNNHardSwishCommon(float* dst, const float* src, size_t size);
void MNNGeluCommon(float* dst, const float* src, size_t size);
void MNNGeluStandardCommon(float* dst, const float* src, size_t size);
void MNNSoftmax(float* dest, const float* source, size_t size);
void MNNNorm(float* dest, const float* source, const float *gamma, const float *beta, float epsilon, size_t size, bool RMSNorm = false);
// Get Pack for MatMul's e , l , h , the pack number must be 1 or 4 * n
void MNNGetMatMulPackMode(int* eP, int *lP, int* hP);
void MNNGetSparseMatMulPackMode(int* eP, int *lP, int* hP);
/**
int number = info[0];
int eSrcStride = info[1];
int eDstStride = info[2];
int xStride = info[3];
el: number * 4
0: e
1: l
2: e-offset
3: l-offset
*/
void MNNPackC4ForMatMul_A(float* destOrigin, float const** sourceGroup, const int32_t* info, const int32_t* el);
void MNNPackForMatMul_B(float* dest, const float* source, size_t h, size_t l, bool transpose);
// parameters: e, l, h, CStride, AStride, BStride
void MNNPackedMatMul(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b);
void MNNFunctionInit();
void MNNPackedMatMulRemain(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b);
void MNNPackedMatMul_int4(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b);
void MNNPackedMatMulRemain_int4(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b);
void MNNPackedMatMul_int8(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b);
void MNNPackedMatMulRemain_int8(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b);
void MNNPackForSparseMatMul_B(float* dest, unsigned int* NNZMap, int* dataOffsetMap, int sparseBlockOC, const float* source, size_t h, size_t l, const int eP, bool transpose);
struct SparseMatMulParas
{
float* C;
const float* A;
const float* B;
unsigned int* NNZMap;
int* dataOffsetMap;
};
void MNNPackedSparseMatMulEpx1(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, unsigned int* NNZMap, int* dataOffsetMap);
void MNNPackedSparseMatMulEpx4(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, unsigned int* NNZMap, int* dataOffsetMap);
int MNNGetC4DivNumber(int hP);
void MNNAxByClampBroadcastUnit(float* C, const float* A, const float* B, size_t width, size_t cStride, size_t aStride, size_t height, const float* parameters);
// dim: 4-element, sizeDW, sizeDH, strideSW, strideDH
void MNNTranspose32Bit(int32_t* dstO, const int32_t* srcO, int32_t* dim); // not C4
void MNNTranspose16Bit(int16_t* dstO, const int16_t* srcO, int32_t* dim); // not C4
void MNNVectorTop1Float(float* input, float* maxValue, int32_t* maxIndex, size_t inputCountUnit);
void MNNVectorTop1Int32(int32_t* input, int32_t* maxValue, int32_t* maxIndex, size_t inputCountUnit);
struct MatMulParam {
int32_t e;
int32_t l;
int32_t h;
int32_t numberThread;
bool ATranspose;
bool BTranspose;
};
void MNNComputeMatMulForE_1(const float* A, const float* B, float* C, const float* biasPtr, const MatMulParam* param, size_t tId);
void MNNCopyC4Int16WithStride(const float* sourceF, float* destF, size_t srcStride, size_t dstStride, size_t count);
void MNNInt8ToInt16(int16_t* dest, const int8_t* source, size_t count);
struct SumByAxisParams {
ssize_t kernelCountUnitDouble;
ssize_t unitColBufferSize;
ssize_t DST_XUNIT;
ssize_t SRC_UNIT;
ssize_t blockNum;
ssize_t oneScale;
ssize_t valid;
ssize_t kernelxy;
ssize_t LU;
ssize_t inputBlock;
};
#ifdef __aarch64__
void MNNPermuteSumWeightInt4Arm86(uint8_t* dest, uint8_t* source, size_t outside, size_t inside, float* kernlesum);
void MNNPermuteSumWeightInt4Arm82(uint8_t* dest, uint8_t* source, size_t outside, size_t inside, float* kernlesum);
void MNNSumWeightInt8Arm86(float* kernelsum, int8_t* source, size_t outside, size_t reduceAxis, size_t hP, size_t lP);
void MNNSumWeightInt8Arm82(float* kernelsum, int8_t* source, size_t outside, size_t reduceAxis, size_t hP, size_t lP);
#endif
}
typedef void(*MNNBinaryExecute)(void* outputRaw, const void* inputRaw0, const void* inputRaw1, int elementSize, int broadcastIndex);
typedef void(*MNNUnaryExecute)(void* outputRaw, const void* inputRaw, int elementSize);
typedef void(*MNNUnaryExecuteInt8)(void* outputRaw, const void* inputRaw, int elementSize, QuanPrePostParameters* params);
typedef void(*MNNCopyWithStride)(uint8_t* dstO, const uint8_t* srcO, int size, int stride, int ds);
typedef void(*MNNBinaryExecInt8)(int8_t* outputRaw, const int8_t* inputRaw0, const int8_t* inputRaw1, ssize_t* inputScalesInt32, float* inputScalesFp32, const QuanPrePostParameters* params, size_t elementSize, size_t needBroadcast);
constexpr int InputTileMax = 14; // same value from DynamicGemm.h, cannot include from different backend code.
namespace MNN {
struct CoreFunctions {
// fp8
void (*MNNFp32ToFp8)(uint8_t* dst, const float* src, size_t size);
void (*MNNFp16ToFp8)(uint8_t* dst, const uint16_t* src, size_t size);
void (*MNNFp8ToFp32)(float* dst, const uint8_t* src, size_t size);
void (*MNNFp8ToFp16)(uint16_t* dst, const uint8_t* src, size_t size);
// cpu feature
bool supportFp16arith = false;
bool supportSDot = false;
bool supportI8mm = false;
/**MatMul Pack and Functions*/
void(*MNNGetMatMulPackMode)(int* eP, int *lP, int* hP);
void(*MNNGetSparseMatMulPackMode)(int* eP, int *lP, int* hP);
void(*MNNPackC4ForMatMul_A)(float* destOrigin, float const** sourceGroup, const int32_t* info, const int32_t* el);
void(*MNNPackForMatMul_B)(float* dest, const float* source, size_t h, size_t l, bool transpose);
void(*MNNGeneralIm2Col)(float* destOrigin, float const** sourceGroup, const int32_t* info, const int32_t* el, int32_t LP, int32_t pack);
// parameters: e, l, h, CStride, AStride, BStride
void(*MNNPackedMatMul)(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b);
void(*MNNPackedMatMulRemain)(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b);
void(*MNNAbsMax)(const float* source, float* absmax, size_t src_depth_quad, size_t realSize, int pack) = nullptr;
void(*MNNQuantScale)(float* absmax, float* quant_scale, float* dequant_scale, size_t thread, size_t batch) = nullptr;
void(*MNNDynamicQuant)(const float* src, int8_t* dst, const float* scale, size_t src_depth_quad, size_t realSize, int pack, const float* bias) = nullptr;
void(*MNNPackedMatMul_int8)(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b) = nullptr;
void(*MNNPackedMatMulRemain_int8)(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b) = nullptr;
void(*MNNComputeMatMulForH_1)(const float* A, const float* B, float* C, const float* biasPtr, const MatMulParam* param, size_t tId);
void(*MNNComputeMatMulForE_1)(const float* A, const float* B, float* C, const float* biasPtr, const MatMulParam* param, size_t tId);
void(*MNNCountMaxMinValue)(const float* source, float* minVal, float* maxVal, size_t size);
void(*MNNDynamicUpdateConvBiasScale)(float* newbias, float* oldbias, float* weightKernelSum, float* inputZero, size_t ocQuad);
void(*MNNAsyQuantInfo)(float* scale, float* bias, float* qscale, float* qbias, float* dstMin, float* dstMax, const float* src, const size_t* info);
void(*MNNAsyQuantFunc)(int8_t* dst, const float* src, float* qscale, float* qbias, const size_t* info);
typedef void(*MNNPackedMatMulKernel)(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias);
MNNPackedMatMulKernel MNNPackedMatMulOC16Functions[InputTileMax] = {0};
MNNPackedMatMulKernel MNNPackedMatMulOC32Functions[InputTileMax] = {0};
MNNPackedMatMulKernel MNNPackedMatMulOC48Functions[InputTileMax] = {0};
// For Atomic Op
MNNBinaryExecute(*MNNSelectBinaryFunctionForFloat)(int opType);
MNNUnaryExecute(*MNNSelectUnaryFunctionForFloat)(int opType, int precisionMode);
MNNUnaryExecuteInt8(*MNNSelectUnaryFunctionForInt8)(int opType);
// B matrix is sparsed
typedef void(*MNNPackedSparseMatMul)(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, unsigned int* NNZMap, int* dataOffsetMap);
void(*MNNAdjustOptimalSparseKernel)(int& sparseBlockOC, MNNPackedSparseMatMul& packedSparseMatMul);
/**Lowp Backend Setting*/
void(*MNNFp32ToLowp)(const float* src, int16_t* dst, size_t size);
void(*MNNLowpToFp32)(const int16_t* src, float* dst, size_t size);
int bytes; // Byte for float
int matmulBytes = 0; // Special bytes for dense matmul, C = A*B, A, B is matmulBytes, C is bytes. If 0, means the same as bytes
/**NC4HW4's Functions*/
int pack;
// For pack * bytes > 16
MNNCopyWithStride(*MNNSelectBlitFunction)(int blitBytes) = nullptr;
void(*MNNPackCUnitInt16)(int16_t* dst, const int16_t* src, size_t area, size_t depth, int* areaOffset);
void(*MNNUnpackCUnitInt16)(int16_t* dst, const int16_t* src, size_t area, size_t depth, int* areaOffset);
void(*MNNPackCUnitTransposeInt16)(int16_t* dst, const int16_t* src, size_t area, size_t depth, int* areaOffset);
void(*MNNUnpackCUnitTransposeInt16)(int16_t* dst, const int16_t* src, size_t area, size_t depth, int* areaOffset);
void(*MNNPackCUnitInt8)(int8_t* dst, const int8_t* src, size_t area, size_t depth, int* areaOffset);
void(*MNNUnpackCUnitInt8)(int8_t* dst, const int8_t* src, size_t area, size_t depth, int* areaOffset);
void(*MNNPackCUnitTransposeInt8)(int8_t* dst, const int8_t* src, size_t area, size_t depth, int* areaOffset);
void(*MNNUnpackCUnitTransposeInt8)(int8_t* dst, const int8_t* src, size_t area, size_t depth, int* areaOffset);
void(*MNNPackCUnit)(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void(*MNNUnpackCUnit)(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void(*MNNPackCUnitTranspose)(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
void(*MNNUnpackCUnitTranspose)(float* dst, const float* src, size_t area, size_t depth, int* areaOffset);
// NC4HW4's compute function
void(*MNNConvRunForLineDepthwise)(float* dst, const float* src, const float* weight, size_t width, size_t src_w_setup,
size_t fw, size_t fh, size_t dilateX_step, size_t dilateY_step, size_t height,
size_t srcHStep, size_t dstHStep, const float* bias, const float* parameters);
void(*MNNAxByClampBroadcastUnit)(float* C, const float* A, const float* B, size_t width, size_t cStride, size_t aStride, size_t height, const float* parameters);
void(*MNNMatrixAdd)(float* C, const float* A, const float* B, size_t widthC4, size_t cStride, size_t aStride,
size_t bStride, size_t height);
void(*MNNMatrixSub)(float* C, const float* A, const float* B, size_t widthC4, size_t cStride, size_t aStride,
size_t bStride, size_t height);
void(*MNNStrassenMergeCFunction)(float* c11, float* c12, float* c21, float* c22, float* xAddr, size_t cStride, size_t eSub, size_t hSub);
void(*MNNScaleAndAddBias)(float* dst, const float* src, const float* bias, const float* alpha, size_t planeNumber, size_t biasNumber);
void(*MNNGridSampleComputeCord)(float* dst, const float* src, size_t inH, size_t inW, size_t outH, size_t outW, bool alignCorners);
void(*MNNGridSampleInterp)(float* outputPtr, const float* inputPtr, const float* cordPtr, size_t inH, size_t inW, size_t outW, size_t channelCUnit, size_t inOffset, size_t outOffset, bool sampleMode, bool padMode);
void (*MNNGridSampleInterpGrad)(float* outputPtr, float* inputPtr, const float* cordPtr, size_t inH, size_t inW, size_t outW, size_t channelCUnit, size_t inOffset, size_t outOffset, bool sampleMode, bool padMode);
void(*MNNGridSampleComputeCord3D)(float* dst, const float* src, size_t inD, size_t inH, size_t inW, size_t outD, size_t outH, size_t outW, bool alignCorners);
void(*MNNGridSampleInterp3D)(float* outputPtr, const float* inputPtr, const float* cordPtr, size_t inD, size_t inH, size_t inW, size_t outW, size_t channelCUnit, size_t inOffset, size_t outOffset, bool sampleMode, bool padMode) = nullptr;
void(*MNNRoiPoolingMax)(float* dst, const float* src, int hLen, int wLen, int iw);
void(*MNNRoiAlignMax)(float* dst, const float* src, const std::vector<std::vector<int>> &vecPos, const std::vector<std::vector<float>> &vecArea, int samplingRatioArea, int pooledHeight, int pooledWidth);
void(*MNNRoiAlignAvg)(float* dst, const float* src, const std::vector<std::vector<int>> &vecPos, const std::vector<std::vector<float>> &vecArea, int samplingRatioArea, int pooledHeight, int pooledWidth);
float penalty;
void(*MNNCopyC4WithStride)(const float* source, float* dest, size_t srcStride, size_t dstStride, size_t count);
void(*MNNAddC4WithStride)(const float* source, float* dest, size_t srcStride, size_t dstStride, size_t count);
typedef void (*WinoTransPackFunc)(float* srcBlock, float* dstStart, size_t dstStep);
WinoTransPackFunc(*chooseWinoSourceTransformPack)(int k, int w, int ePack, int lPack, int packCUnit);
typedef void (*WinoUnrollTransFunc)(const float* srcBlock, float* dstStart, size_t srcRowStep, size_t dstRowStep, size_t srcStep, size_t dstStep);
typedef void (*WinoUnrollDestTransFunc)(const float* srcBlock, float* dstStart, const float* bias, const float* postParameters, size_t srcRowStep, size_t dstRowStep, size_t srcStep, size_t dstStep);
WinoUnrollTransFunc(*chooseWinoSourceUnrollTransform)(int k, int w);
void(*chooseWinoDestUnrollTransform)(WinoUnrollDestTransFunc *destFunctions, size_t maxUnit, int k, int h);
void(*MNNDeconvRunForUnitDepthWise)(const float* dst, float* src, const float* weight, size_t fw, size_t fh,
size_t weight_y_step, size_t dilateX_step, size_t dilateY_step);
void(*MNNDeconvRunForLineDepthwise)(const float* dst, float* src, const float* weight, size_t width, size_t src_w_setup,
size_t fw, size_t fh, size_t dilateX_step, size_t dilateY_step);
void(*MNNDepthwiseConvFastKernel)(float* dst, const float* src, const float* weight, size_t width, size_t src_w_setup,
size_t fw, size_t fh, size_t dilateX_step, size_t dilateY_step, size_t height,
size_t srcHStep, size_t dstHStep, const float* bias, const float* parameters) = nullptr;
void(*MNNReluWithSlopeChannel)(float* dst, const float* src, const float* slope, size_t sizeQuad, size_t depthQuad);
void(*MNNPoolingAvg)(const void* channelInput, int inputWidth, int inputHeight, void *channelOutput,
int outputWidth, int outputHeight, int kernelWidth, int kernelHeight, int strideWidth,
int strideHeight, int padWidth, int padHeight, int padType, int countType);
void(*MNNPoolingMax)(const void* channelInput, int inputWidth, int inputHeight, void *channelOutput,
int outputWidth, int outputHeight, int kernelWidth, int kernelHeight, int strideWidth,
int strideHeight, int padWidth, int padHeight, int padType, int countType);
void(*MNNPoolingMaxWithRedice)(const void* channelInput, int inputWidth, int inputHeight, void *channelOutput,
int outputWidth, int outputHeight, int kernelWidth, int kernelHeight, int strideWidth,
int strideHeight, int padWidth, int padHeight, int padType, int countType, int *RediceOutput);
// ImageProcess Funtions
void(*MNNRGBAToBGRA)(const unsigned char* source, unsigned char* dest, size_t count);
void(*MNNNV21ToRGBA)(const unsigned char* source, unsigned char* dest, size_t count);
void(*MNNNV21ToRGB)(const unsigned char* source, unsigned char* dest, size_t count);
void(*MNNNV21ToBGRA)(const unsigned char* source, unsigned char* dest, size_t count);
void(*MNNNV21ToBGR)(const unsigned char* source, unsigned char* dest, size_t count);
void(*MNNC1ToFloatC1)(const unsigned char* source, float* dest, const float* mean, const float* normal, size_t count);
void(*MNNC3ToFloatC3)(const unsigned char* source, float* dest, const float* mean, const float* normal, size_t count);
void(*MNNC3ToFloatRGBA)(const unsigned char* source, float* dest, const float* mean, const float* normal, size_t count);
void(*MNNsampleBilinearCommon)(const unsigned char* source, unsigned char* dest, MNN::CV::Point* points, size_t count,
size_t iw, size_t ih, size_t yStride, size_t bpp);
void(*MNNSamplerC4Nearest)(const unsigned char* source, unsigned char* dest, MNN::CV::Point* points, size_t sta,
size_t count, size_t capacity, size_t iw, size_t ih, size_t yStride);
void(*MNNSamplerC4Bilinear)(const unsigned char* source, unsigned char* dest, MNN::CV::Point* points, size_t sta,
size_t count, size_t capacity, size_t iw, size_t ih, size_t yStride);
void(*MNNSampleC4Bilinear)(const unsigned char* source, unsigned char* dest, MNN::CV::Point* points, size_t sta,
size_t count, size_t capacity, size_t iw, size_t ih, size_t yStride);
void(*MNNSampleBilinear)(const unsigned char* source, unsigned char* dest, MNN::CV::Point* points, size_t count,
size_t iw, size_t ih, size_t yStride, size_t bpp);
void(*MNN4BitcopyWithStride)(uint8_t* dstO, const uint8_t* srcO, int size, int stride, int ds);
void(*MNN2BitcopyWithStride)(uint8_t* dstO, const uint8_t* srcO, int size, int stride, int ds);
void(*MNN1BitcopyWithStride)(uint8_t* dstO, const uint8_t* srcO, int size, int stride, int ds);
void(*MNN4BitcopyFast)(uint8_t* dstO, const uint8_t* srcO, int size, int stride, int ds);
void(*MNN2BitcopyFast)(uint8_t* dstO, const uint8_t* srcO, int size, int stride, int ds);
void(*MNN1BitcopyFast)(uint8_t* dstO, const uint8_t* srcO, int size, int stride, int ds);
void(*MNNAccumulateSequenceNumber)(float* dst, const float* src, int size);
void(*MNNSumByAxisLForMatmul_A)(float* dest, int8_t* source, const float* dequantScale, ssize_t realDstCount, SumByAxisParams sumParams);
void(*MNNReorderWeightInt4)(uint8_t* dest, const uint8_t* source, int32_t* shape, size_t size, float* kernelsum);
void(*MNNSumWeightInt8)(float* kernlesum, int8_t* source, size_t outside, size_t reduceAxis, size_t hP, size_t lP);
};
void MNNCoreFunctionInit();
CoreFunctions* MNNGetCoreFunctions();
};
#endif /* CommonOptFunction_h */