source/backend/cpu/compute/Int8FunctionsOpt.h (100 lines of code) (raw):
//
// Int8FunctionsOpt.h
// MNN
//
// Created by MNN on 2018/08/15.
// Copyright © 2018, Alibaba Group Holding Limited
//
#ifndef Int8FunctionsOpt_h
#define Int8FunctionsOpt_h
#include <stdint.h>
#include <stdio.h>
#include <sys/types.h>
#include "core/Macro.h"
#include "core/ConvolutionCommon.hpp"
#if defined(_MSC_VER)
#include <BaseTsd.h>
typedef SSIZE_T ssize_t;
#endif
/* CPU without sdot */
#define GEMM_INT8_UNIT 4
#define GEMM_INT8_SRC_UNIT 16
#ifndef MNN_USE_SSE
#ifdef __aarch64__
#define GEMM_INT8_DST_XUNIT 4
#else
#define GEMM_INT8_DST_XUNIT 2
#endif
#else
#define GEMM_INT8_DST_XUNIT 4
#endif
#ifdef __cplusplus
extern "C" {
#endif
struct QuanPostTreatParameters {
const float* scale;
const float* biasFloat;
int32_t maxValue;
int32_t minValue;
int32_t useInt8 = 1; // Save result as int8_t dataType; otherwise float32.
float roundValuePos = 0.5f;
float roundValueNeg = -0.5f;
float* srcKernelSum;
float* weightKernelSum;
float* fp32minmax;
ssize_t blockNum = 1;
const int32_t* bias = nullptr;
const float* inputScale = nullptr;
const float* inputBias = nullptr;
float* accumBuffer = nullptr;
};
struct QuanPrePostParameters{
float* inputScale;
float* outputScale;
ssize_t* inputZeroPoint;
ssize_t* outputZeroPoint;
ssize_t minValue;
ssize_t maxValue;
};
void MNNFloat2Int8(const float* src, int8_t* dst, size_t sizeQuad, const float* scalep, ssize_t minValue,
ssize_t maxValue, const float* zeroPoint, ssize_t quanParamVec);
void MNNInt8ScaleToFloat(float* dst, const int8_t* src, const float* scale, size_t size, const float* zeroPoint, ssize_t quanParamVec);
void MNNInt8FunctionInit();
void MNNPackedSparseQuantMatMulEpx1(int8_t* C, const int8_t* A, const int8_t* B, const size_t* sparseQuantParam, const QuanPostTreatParameters* post, unsigned int* NNZMap, int* dataOffsetMap);
void MNNPackedSparseQuantMatMulEpx4(int8_t* C, const int8_t* A, const int8_t* B, const size_t* sparseQuantParam, const QuanPostTreatParameters* post, unsigned int* NNZMap, int* dataOffsetMap);
void MNNBinaryAddInt8(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);
void MNNBinarySubInt8(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);
void MNNBinaryMulInt8(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);
void MNNBinarySqdInt8(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);
void MNNBinaryMaxInt8(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);
void MNNBinaryMinInt8(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);
void MNNScaleAndAddBiasInt8(int8_t* dst, const int8_t* src, const int32_t* bias, const int32_t* alpha, int32_t mShiftBits, ssize_t minValue, ssize_t maxValue, int8_t* inputZeroPoint, int8_t* outputZeroPoint, ssize_t planeNumber, ssize_t biasNumber, ssize_t pack = 4);
#ifdef __cplusplus
}
#endif
namespace MNN {
struct CoreInt8Functions {
// MatMul
void(*Int8GemmKernel)(int8_t* dst, const int8_t* src, const int8_t* weight, size_t src_depth_quad, size_t dst_step, size_t dst_depth_quad, const QuanPostTreatParameters* post, size_t realCount);
void(*Int8GemmKernelFast)(int8_t* dst, const int8_t* src, const int8_t* weight, size_t src_depth_quad, size_t dst_step, size_t dst_depth_quad, const QuanPostTreatParameters* post, size_t realCount);
void(*MNNGetGemmUnit)(int* UNIT, int* SRC_UNIT, int* DST_XUNIT);
void(*MNNPackC4Int8ForMatMul_A)(int8_t* destOrigin, int8_t const** sourceGroup, const int32_t* info, const int32_t* el);
void(*MNNGemmInt8AddBiasScale_Unit_FP16)(int8_t* dst, const int8_t* src, const int8_t* weight, size_t src_depth_quad, size_t dst_step, size_t dst_depth_quad,
const QuanPostTreatParameters* post, size_t realDstCount) = nullptr;
void(*MNNGemmInt8AddBiasScale_w4_Unit_FP16)(int8_t* dst, const int8_t* src, const int8_t* weight, size_t src_depth_quad, size_t dst_step, size_t dst_depth_quad,
const QuanPostTreatParameters* post, size_t realDstCount) = nullptr;
void(*Int8GemmKernel_W4)(int8_t* dst, const int8_t* src, const int8_t* weight, size_t src_depth_quad, size_t dst_step, size_t dst_depth_quad,
const QuanPostTreatParameters* post, size_t realDstCount);
// sparse
void(*MNNGetSparseQuantMatMulPackMode)(int* eP, int *lP, int* hP);
void(*MNNPackForSparseQuantMatMul_B)(int8_t* dest, unsigned int* NNZMap, int* dataOffsetMap, int sparseBlockOC, const int8_t* source, size_t h, size_t kernelCount, size_t icCount, const int eP);
void(*MNNPackedSparseQuantMatMulEpx1)(int8_t* C, const int8_t* A, const int8_t* B, const size_t* sparseQuantParam, const QuanPostTreatParameters* post, unsigned int* NNZMap, int* dataOffsetMap);
void(*MNNPackedSparseQuantMatMulEpx4)(int8_t* C, const int8_t* A, const int8_t* B, const size_t* sparseQuantParam, const QuanPostTreatParameters* post, unsigned int* NNZMap, int* dataOffsetMap);
void(*MNNPackC4Int8ForMatMul_ASparse)(int8_t* destOrigin, int8_t const** sourceGroup, const int32_t* info, const int32_t* el);
void(*ConvDepthwiseLineInt8)(int8_t* dst, const int8_t* src, const int8_t* weight, const QuanPostTreatParameters* parameters, size_t width,
size_t src_w_step, size_t fw, size_t fh, size_t dilateX_step, size_t dilateY_step, int8_t* idxOrder);
void(*ConvDepthwise3x3LineInt8_ARM82)(int8_t* dst, const int8_t* src, const int8_t* weight, const QuanPostTreatParameters* parameters, size_t width,
size_t src_w_step, size_t fw, size_t fh, size_t dilateX_step, size_t dilateY_step, int8_t* idxOrder) = nullptr;
void(*DynamicQuanInput_ARM82)(const float* src, int8_t* dst, size_t sizeQuad, const float* scalep, ssize_t minValue, ssize_t maxValue, const float* zeroPoint, ssize_t quanParamVec) = nullptr;
void (*DynamicQuanInputAndReorder_ARM82)(const float* src, int8_t* dst, size_t planeSize, const float* scale, ssize_t aMin, ssize_t aMax, const float* zeroPoint, size_t ocQuad, size_t offset) = nullptr;
void(*MNNFloat2Int8)(const float* src, int8_t* dst, size_t sizeQuad, const float* scalep, ssize_t minValue, ssize_t maxValue, const float* zeroPoint, ssize_t quanParamVec);
void(*MNNInt8ScaleToFloat)(float* dst, const int8_t* src, const float* scale, size_t size, const float* zeroPoint, ssize_t quanParamVec);
void(*MNNScaleAndAddBias)(float* dst, const float* src, const float* bias, const float* alpha, size_t planeNumber, size_t biasNumber);
// Pooling
void (*MNNMaxPoolInt8)(int8_t* dst, int8_t* src, size_t outputWidth, size_t inputWidth, size_t kernelx, size_t kernely, size_t stridesx);
void (*MNNAvgPoolInt8)(int8_t* dst, int8_t* src, size_t outputWidth, size_t inputWidth, size_t kernelx, size_t kernely, size_t stridesx, ssize_t paddingx, ssize_t factor);
// Relu
void (*MNNReluWithSlopeChannelInt8)(int8_t* dst, const int8_t* src, const float* slope, size_t planeNumber, size_t depthQuad, const QuanPrePostParameters *params, size_t pack);
};
void MNNCoreInt8FunctionInit();
CoreInt8Functions* MNNGetInt8CoreFunctions();
}
#endif /* Int8FunctionsOpt_h */