source/backend/cpu/CPUUnary.cpp (548 lines of code) (raw):

// // CPUUnary.cpp // MNN // // Created by MNN on 2018/08/02. // Copyright © 2018, Alibaba Group Holding Limited // #include "backend/cpu/CPUUnary.hpp" #include "UnaryUtils.hpp" #include "backend/cpu/CPUBackend.hpp" #include "core/Macro.h" #include "core/Concurrency.h" #include "compute/ConvOpt.h" #include "compute/CommonOptFunction.h" #include <MNN/AutoTime.hpp> #include "math/Vec.hpp" #include "core/TensorUtils.hpp" namespace MNN { using VecType = Math::Vec<int8_t, 8>; CPUUnary::CPUUnary(Backend *b, MNNUnaryExecute proc, MNNUnaryExecuteInt8 procInt8, const Op* op) : MNN::Execution(b), mProc(proc), mProcInt8(procInt8){ if (op->main_as_UnaryOp()->tableInt8()) { mTableBuffer.resize(255); ::memcpy(mTableBuffer.data(), op->main_as_UnaryOp()->tableInt8()->data(), 255); } } ErrorCode CPUUnary::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) { MNN_ASSERT(1 == outputs.size()); MNN_ASSERT(inputs[0]->getType() == halide_type_of<float>() || inputs[0]->getType() == halide_type_of<int32_t>()); if (mProcInt8) { auto quantIn = TensorUtils::getDescribe(inputs[0])->quantAttr; auto quantOut = TensorUtils::getDescribe(outputs[0])->quantAttr; float outpScale = quantOut->scale == 0.f ? 0.f: 1.0f / quantOut->scale; mInpScale.push_back(quantIn->scale); mOupScale.push_back(outpScale); mInpZeroPoint.push_back(quantIn->zero); mOupZeroPoint.push_back(quantOut->zero); mMaxMinValue = {static_cast<ssize_t>(quantOut->min), static_cast<ssize_t>(quantOut->max)}; } return NO_ERROR; } static void _Neg(void* out, const void* inp, int realSize) { MNNScaleAndAddBiasScalar((float*)out, (const float*)inp, 0.0f, -1.0f, realSize); } #ifdef MNN_USE_NEON static inline void exeNegInt8 (int8_t* out, const int8_t* inp, int sizeQuad, int8x8_t inZeroPoint, int8x8_t outZeroPoint, float32x4_t inpScale, float32x4_t outScale) { for (int i = 0;i < sizeQuad; ++i) { int8x16_t negValue = vld1q_s8(inp); int16x8_t val16_0 = vmovl_s8(vget_low_s8(negValue)); int16x8_t val16_1 = vmovl_s8(vget_high_s8(negValue)); val16_0 = vsubw_s8(val16_0, inZeroPoint); val16_1 = vsubw_s8(val16_1, inZeroPoint); int32x4_t val32_00 = vmovl_s16(vget_low_s16(val16_0)); int32x4_t val32_01 = vmovl_s16(vget_high_s16(val16_0)); int32x4_t val32_10 = vmovl_s16(vget_low_s16(val16_1)); int32x4_t val32_11 = vmovl_s16(vget_high_s16(val16_1)); float32x4_t valF_00 = vcvtq_f32_s32(val32_00); float32x4_t valF_01 = vcvtq_f32_s32(val32_01); float32x4_t valF_10 = vcvtq_f32_s32(val32_10); float32x4_t valF_11 = vcvtq_f32_s32(val32_11); valF_00 = vmulq_f32(valF_00, inpScale); valF_01 = vmulq_f32(valF_01, inpScale); valF_10 = vmulq_f32(valF_10, inpScale); valF_11 = vmulq_f32(valF_11, inpScale); valF_00 = vnegq_f32(valF_00); valF_01 = vnegq_f32(valF_01); valF_10 = vnegq_f32(valF_10); valF_11 = vnegq_f32(valF_11); valF_00 = vmulq_f32(valF_00, outScale); valF_01 = vmulq_f32(valF_01, outScale); valF_10 = vmulq_f32(valF_10, outScale); valF_11 = vmulq_f32(valF_11, outScale); int32x4_t val_00 = vcvtq_s32_f32(valF_00); int32x4_t val_01 = vcvtq_s32_f32(valF_01); int32x4_t val_10 = vcvtq_s32_f32(valF_10); int32x4_t val_11 = vcvtq_s32_f32(valF_11); int16x4_t v16_0 = vqmovn_s32(val_00); int16x4_t v16_1 = vqmovn_s32(val_01); int16x4_t v16_2 = vqmovn_s32(val_10); int16x4_t v16_3 = vqmovn_s32(val_11); int16x8_t v16_4 = vcombine_s16(v16_0, v16_1); int16x8_t v16_5 = vcombine_s16(v16_2, v16_3); v16_4 = vaddw_s8(v16_4, outZeroPoint); v16_5 = vaddw_s8(v16_5, outZeroPoint); int8x8_t v8_0 = vqmovn_s16(v16_4); int8x8_t v8_1 = vqmovn_s16(v16_5); vst1_s8(out, v8_0); vst1_s8(out + 8, v8_1); inp += 16; out += 16; } } #endif static void _NegInt8(void* out, const void* inp, int realSize, QuanPrePostParameters* params) { int sizeDiv16 = realSize / 16; int remain = realSize % 16; #ifdef MNN_USE_NEON int8_t* outPtr = (int8_t*)out; int8_t* inPtr = (int8_t*)inp; int8x8_t inZeroPoint = vdup_n_s8(params->inputZeroPoint[0]); int8x8_t outZeroPoint = vdup_n_s8(params->outputZeroPoint[0]); float32x4_t inpScale = vdupq_n_f32(params->inputScale[0]); float32x4_t outScale = vdupq_n_f32(params->outputScale[0]); if (sizeDiv16 > 0) { exeNegInt8(outPtr, inPtr, sizeDiv16, inZeroPoint, outZeroPoint, inpScale, outScale); } if (remain > 0) { int8_t intmp[16] = {0}; int8_t outmp[16] = {0}; ::memcpy(intmp, reinterpret_cast<const int8_t*>(inp) + 16 * sizeDiv16, remain * sizeof(int8_t)); exeNegInt8(outmp, intmp, 1, inZeroPoint, outZeroPoint, inpScale, outScale); ::memcpy(reinterpret_cast<int8_t*>(out) + 16 * sizeDiv16, outmp, remain * sizeof(int8_t)); } #else #ifdef MNN_USE_SSE uint8_t* dst = (uint8_t*)out; uint8_t* src = (uint8_t*)inp; int offset = 128; #else int8_t* dst = (int8_t*)out; int8_t* src = (int8_t*)inp; int offset = 0; #endif int inzero_ = static_cast<int>(params->inputZeroPoint[0]); int outzero_ = static_cast<int>(params->outputZeroPoint[0]); float inscale_ = params->inputScale[0]; float outscale_ = params->outputScale[0]; int min_ = static_cast<int>(params->minValue); int max_ = static_cast<int>(params->maxValue); for (int i = 0; i < realSize; ++i) { int value = -(src[i] - inzero_ - offset) * inscale_ * outscale_ + outzero_; if (value > max_) { value = max_; } if (value < min_) { value = min_; } dst[i] = value + offset; } #endif } static void _ABS(void* out, const void* inp, int realSize) { MNNReluWithSlopeCommon((float*)out, (const float*)inp, realSize, -1.0f); } #ifdef MNN_USE_NEON static inline void exeAbsInt8(int8_t* out, const int8_t* inp, int sizeQuad, int8x8_t inZeroPoint, int8x8_t outZeroPoint, float32x4_t inpScale, float32x4_t outScale) { for (int i = 0;i < sizeQuad; ++i) { int8x16_t absValue = vld1q_s8(inp); int16x8_t val16_0 = vmovl_s8(vget_low_s8(absValue)); int16x8_t val16_1 = vmovl_s8(vget_high_s8(absValue)); val16_0 = vsubw_s8(val16_0, inZeroPoint); val16_1 = vsubw_s8(val16_1, inZeroPoint); int32x4_t val32_00 = vmovl_s16(vget_low_s16(val16_0)); int32x4_t val32_01 = vmovl_s16(vget_high_s16(val16_0)); int32x4_t val32_10 = vmovl_s16(vget_low_s16(val16_1)); int32x4_t val32_11 = vmovl_s16(vget_high_s16(val16_1)); float32x4_t valF_00 = vcvtq_f32_s32(val32_00); float32x4_t valF_01 = vcvtq_f32_s32(val32_01); float32x4_t valF_10 = vcvtq_f32_s32(val32_10); float32x4_t valF_11 = vcvtq_f32_s32(val32_11); valF_00 = vmulq_f32(valF_00, inpScale); valF_01 = vmulq_f32(valF_01, inpScale); valF_10 = vmulq_f32(valF_10, inpScale); valF_11 = vmulq_f32(valF_11, inpScale); valF_00 = vabsq_f32(valF_00); valF_01 = vabsq_f32(valF_01); valF_10 = vabsq_f32(valF_10); valF_11 = vabsq_f32(valF_11); valF_00 = vmulq_f32(valF_00, outScale); valF_01 = vmulq_f32(valF_01, outScale); valF_10 = vmulq_f32(valF_10, outScale); valF_11 = vmulq_f32(valF_11, outScale); int32x4_t val_00 = vcvtq_s32_f32(valF_00); int32x4_t val_01 = vcvtq_s32_f32(valF_01); int32x4_t val_10 = vcvtq_s32_f32(valF_10); int32x4_t val_11 = vcvtq_s32_f32(valF_11); int16x4_t v16_0 = vqmovn_s32(val_00); int16x4_t v16_1 = vqmovn_s32(val_01); int16x4_t v16_2 = vqmovn_s32(val_10); int16x4_t v16_3 = vqmovn_s32(val_11); int16x8_t v16_4 = vcombine_s16(v16_0, v16_1); int16x8_t v16_5 = vcombine_s16(v16_2, v16_3); v16_4 = vaddw_s8(v16_4, outZeroPoint); v16_5 = vaddw_s8(v16_5, outZeroPoint); int8x8_t v8_0 = vqmovn_s16(v16_4); int8x8_t v8_1 = vqmovn_s16(v16_5); vst1_s8(out, v8_0); vst1_s8(out + 8, v8_1); inp += 16; out += 16; } } #endif static void _ABSInt8(void* out, const void* inp, int realSize, QuanPrePostParameters* params) { int sizeDiv16 = realSize / 16; int remain = realSize % 16; #ifdef MNN_USE_NEON int8_t* outPtr = (int8_t*)out; int8_t* inPtr = (int8_t*)inp; int8x8_t inZeroPoint = vdup_n_s8(params->inputZeroPoint[0]); int8x8_t outZeroPoint = vdup_n_s8(params->outputZeroPoint[0]); float32x4_t inpScale = vdupq_n_f32(params->inputScale[0]); float32x4_t outScale = vdupq_n_f32(params->outputScale[0]); if (sizeDiv16 > 0) { exeAbsInt8(outPtr, inPtr, sizeDiv16, inZeroPoint, outZeroPoint, inpScale, outScale); } if (remain > 0) { int8_t intmp[16] = {0}; int8_t outmp[16] = {0}; ::memcpy(intmp, reinterpret_cast<const int8_t*>(inp) + 16 * sizeDiv16, remain * sizeof(int8_t)); exeAbsInt8(outmp, intmp, 1, inZeroPoint, outZeroPoint, inpScale, outScale); ::memcpy(reinterpret_cast<int8_t*>(out) + 16 * sizeDiv16, outmp, remain * sizeof(int8_t)); } #else #ifdef MNN_USE_SSE uint8_t* dst = (uint8_t*)out; uint8_t* src = (uint8_t*)inp; int offset = 128; #else int8_t* dst = (int8_t*)out; int8_t* src = (int8_t*)inp; int offset = 0; #endif int inzero_ = static_cast<int>(params->inputZeroPoint[0]); int outzero_ = static_cast<int>(params->outputZeroPoint[0]); for (int i = 0; i < realSize; ++i) { auto value = abs((src[i] - inzero_ - offset) * params->inputScale[0]); value = value * params->outputScale[0] + outzero_; if (value > params->maxValue) { value = params->maxValue; } if (value < params->minValue) { value = params->minValue; } dst[i] = value + offset; } #endif } #ifdef MNN_USE_NEON static inline void exeSignInt8 (int8_t* out, const int8_t* inp, int sizeQuad, int16x8_t one, int16x8_t negone, int16x8_t zero, int8x8_t inZeroPoint, int8x8_t outZeroPoint, float32x4_t outScale) { for (int i = 0;i < sizeQuad; ++i) { int8x16_t value = vld1q_s8(inp); int16x8_t vallow = vmovl_s8(vget_low_s8(value)); int16x8_t valhi = vmovl_s8(vget_high_s8(value)); vallow = vsubw_s8(vallow, inZeroPoint); valhi = vsubw_s8(valhi, inZeroPoint); uint16x8_t lomask1 = vcgtq_s16(vallow, zero); uint16x8_t lomask_1 = vcltq_s16(vallow, zero); uint16x8_t himask1 = vcgtq_s16(valhi, zero); uint16x8_t himask_1 = vcltq_s16(valhi, zero); uint16x8_t zeromask_low = vceqq_u16(lomask1, lomask_1); uint16x8_t zeromask_hi = vceqq_u16(himask1, himask_1); vallow = vbslq_s16(lomask1, one, negone); vallow = vbslq_s16(zeromask_low, zero, vallow); valhi = vbslq_s16(himask1, one, negone); valhi = vbslq_s16(zeromask_hi, zero, valhi); int8x8_t v8_0 = vqmovn_s16(vallow); int8x8_t v8_1 = vqmovn_s16(valhi); vst1_s8(out, v8_0); vst1_s8(out + 8, v8_1); inp += 16; out += 16; } } #endif static void _SignInt8(void* out, const void* inp, int realSize, QuanPrePostParameters* params) { int sizeDiv16 = realSize / 16; int remain = realSize % 16; #ifdef MNN_USE_NEON int8_t* outPtr = (int8_t*)out; int8_t* inPtr = (int8_t*)inp; int16x8_t one = vdupq_n_s16(1); int16x8_t negone = vdupq_n_s16(-1); int16x8_t zero = vdupq_n_s16(0); int8x8_t inZeroPoint = vdup_n_s8(params->inputZeroPoint[0]); int8x8_t outZeroPoint = vdup_n_s8(params->outputZeroPoint[0]); float32x4_t outScale = vdupq_n_f32(params->outputScale[0]); if (sizeDiv16 > 0) { exeSignInt8(outPtr, inPtr, sizeDiv16, one, negone, zero, inZeroPoint, outZeroPoint, outScale); } if (remain > 0) { int8_t intmp[16] = {0}; int8_t outmp[16] = {0}; ::memcpy(intmp, reinterpret_cast<const int8_t*>(inp) + 16 * sizeDiv16, remain * sizeof(int8_t)); exeSignInt8(outmp, intmp, 1, one, negone, zero, inZeroPoint, outZeroPoint, outScale); ::memcpy(reinterpret_cast<int8_t*>(out) + 16 * sizeDiv16, outmp, remain * sizeof(int8_t)); } #else #ifdef MNN_USE_SSE uint8_t* dst = (uint8_t*)out; uint8_t* src = (uint8_t*)inp; int offset = 128; #else int8_t* dst = (int8_t*)out; int8_t* src = (int8_t*)inp; int offset = 0; #endif int inzero_ = static_cast<int>(params->inputZeroPoint[0]); int outzero_ = static_cast<int>(params->outputZeroPoint[0]); for (int i = 0; i < realSize; ++i) { auto value = src[i] - offset - inzero_; if (value > 0) { int f = 1 * params->outputScale[0] + outzero_; dst[i] = f + offset; } else if (value < 0) { int f = -1 * params->outputScale[0] + outzero_; dst[i] = f + offset; } else { dst[i] = outzero_ + offset; } } #endif } static void _Square(void* out, const void* inp, int realSize) { MNNMatrixProdCommon((float*)out, (const float*)inp, (const float*)inp, realSize, 0, 0, 0, 1); } static void _EXP(void* outRaw, const void* inpRaw, int realSize) { auto out = (float*)outRaw; auto inp = (const float*)inpRaw; float offset[] = { 1.0f, 0.0f, 0.0f, 0.0f }; MNNExp(out, inp, offset, realSize); } static void _EXPM1(void* outRaw, const void* inpRaw, int realSize) { auto out = (float*)outRaw; auto inp = (const float*)inpRaw; float offset[] = { 1.0f, -1.0f, 0.0f, 0.0f }; MNNExp(out, inp, offset, realSize); } MNNUnaryExecute CPUUnary::selectForFloat(int type, int precision) { switch (type) { case UnaryOpOperation_ABS: return _ABS; case UnaryOpOperation_SQUARE: return _Square; case UnaryOpOperation_NEG: return _Neg; case UnaryOpOperation_RSQRT: return _unaryOp<UnaryRsqrt<float>, float>; case UnaryOpOperation_EXP: return _EXP; case UnaryOpOperation_COS: return _unaryOp<UnaryCos<float>, float>; case UnaryOpOperation_SIN: return (MNNUnaryExecute)MNNSin; case UnaryOpOperation_SIGMOID: if (BackendConfig::Precision_Low == precision) { return (MNNUnaryExecute)MNNSigmoidLowp; } else { return (MNNUnaryExecute)MNNSigmoid; } break; case UnaryOpOperation_SILU: if (BackendConfig::Precision_Low == precision) { return (MNNUnaryExecute)MNNSiLuLowp; } else { return (MNNUnaryExecute)MNNSiLu; } break; case UnaryOpOperation_TANH: return (MNNUnaryExecute)MNNTanh; case UnaryOpOperation_TAN: return _unaryOp<UnaryTan<float>, float>; case UnaryOpOperation_ATAN: return _unaryOp<UnaryATan<float>, float>; case UnaryOpOperation_SQRT: return _unaryOp<UnarySqrt<float>, float>; case UnaryOpOperation_CEIL: return _unaryOp<UnaryCeil<float>, float>; case UnaryOpOperation_RECIPROCAL: return _unaryOp<UnaryRecipocal<float>, float>; case UnaryOpOperation_LOG1P: return _unaryOp<UnaryLog1p<float>, float>; case UnaryOpOperation_LOG: return _unaryOp<UnaryLog<float>, float>; case UnaryOpOperation_FLOOR: return _unaryOp<UnaryFloor<float>, float>; case UnaryOpOperation_BNLL: return _unaryOp<UnaryBNLL<float>, float>; case UnaryOpOperation_ACOSH: return _unaryOp<UnaryAcosh<float>, float>; case UnaryOpOperation_SINH: return _unaryOp<UnarySinh<float>, float>; case UnaryOpOperation_ASINH: return _unaryOp<UnaryAsinh<float>, float>; case UnaryOpOperation_ATANH: return _unaryOp<UnaryAtanh<float>, float>; case UnaryOpOperation_SIGN: return _unaryOp<UnarySign<float>, float>; case UnaryOpOperation_ROUND: return _unaryOp<UnaryRound<float>, float>; case UnaryOpOperation_COSH: return _unaryOp<UnaryCosh<float>, float>; case UnaryOpOperation_ERF: return _unaryOp<UnaryErf<float>, float>; case UnaryOpOperation_ERFC: return _unaryOp<UnaryErfc<float>, float>; case UnaryOpOperation_ERFINV: return _unaryOp<UnaryErfinv<float>, float>; case UnaryOpOperation_EXPM1: return _EXPM1; case UnaryOpOperation_ASIN: return _unaryOp<UnaryAsin<float>, float>; case UnaryOpOperation_ACOS: return _unaryOp<UnaryAcos<float>, float>; case UnaryOpOperation_HARDSWISH: return (MNNUnaryExecute)MNNHardSwishCommon; case UnaryOpOperation_GELU: return (MNNUnaryExecute)MNNGeluCommon; case UnaryOpOperation_GELU_STANDARD: return (MNNUnaryExecute)MNNGeluStandardCommon; default: MNN_ASSERT(false); break; } return nullptr; } static MNNUnaryExecute selectForInt(int type) { switch (type) { case UnaryOpOperation_ABS: return _unaryOp<UnaryAbs<int32_t>, int32_t>; case UnaryOpOperation_NEG: return _unaryOp<UnaryNeg<int32_t>, int32_t>; case UnaryOpOperation_SQUARE: return _unaryOp<UnarySquare<int32_t>, int32_t>; case UnaryOpOperation_SIGN: return _unaryOp<UnarySign<int32_t>, int32_t>; default: break; } return nullptr; } MNNUnaryExecuteInt8 CPUUnary::selectForInt8(int type) { switch (type) { case UnaryOpOperation_ABS: return _ABSInt8; case UnaryOpOperation_NEG: return _NegInt8; case UnaryOpOperation_SIGN: return _SignInt8; default: break; } return nullptr; } ErrorCode CPUUnary::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) { auto input = inputs[0]; auto output = outputs[0]; auto size = static_cast<CPUBackend*>(backend())->getTensorSize(input); auto schedule = ((CPUBackend*)backend())->multiThreadDivide(size); auto inputPtr = input->host<uint8_t>(); auto outputPtr = output->host<uint8_t>(); int outBytes = output->getType().bytes(); if (halide_type_float == output->getType().code) { outBytes = static_cast<CPUBackend*>(backend())->functions()->bytes; } if (mTableBuffer.data()) { #ifdef MNN_USE_SSE uint8_t* srcO = inputPtr; uint8_t* dstO = outputPtr; int offset = 128; #else int8_t* srcO = (int8_t*)inputPtr; int8_t* dstO = (int8_t*)outputPtr; int offset = 0; #endif MNN_CONCURRENCY_BEGIN(tId, schedule.second) { int start = schedule.first * (int)tId; int realSize = schedule.first; if (tId == schedule.second -1 ) { realSize = size - start; } if (realSize > 0) { auto inp = srcO + start; auto out = dstO + start; for (int i = 0; i < realSize; ++i) { int idx = inp[i] - offset + 127; out[i] = offset + mTableBuffer[idx]; } } } MNN_CONCURRENCY_END(); return NO_ERROR; } if (mProcInt8) { MNN_CONCURRENCY_BEGIN(tId, schedule.second) { QuanPrePostParameters params; params.inputScale = mInpScale.data(); params.outputScale = mOupScale.data(); params.inputZeroPoint= mInpZeroPoint.data(); params.outputZeroPoint = mOupZeroPoint.data(); params.maxValue = mMaxMinValue[1]; params.minValue = mMaxMinValue[0]; int start = schedule.first * (int)tId; int realSize = schedule.first; if (tId == schedule.second -1 ) { realSize = size - start; } if (realSize > 0) { auto inp = inputPtr + start; auto out = outputPtr + start; mProcInt8(out, inp, realSize, &params); } } MNN_CONCURRENCY_END(); return NO_ERROR; } MNN_CONCURRENCY_BEGIN(tId, schedule.second) { int start = schedule.first * (int)tId; int realSize = schedule.first; if (tId == schedule.second -1 ) { realSize = size - start; } if (realSize > 0) { auto inp = inputPtr + start * outBytes; auto out = outputPtr + start * outBytes; mProc(out, inp, realSize); } } MNN_CONCURRENCY_END(); return NO_ERROR; } class CPUUnaryCreator : public CPUBackend::Creator { public: virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs, const MNN::Op *op, Backend *backend) const override { auto core = static_cast<CPUBackend*>(backend)->functions(); auto precision = static_cast<CPUBackend*>(backend)->precisionMode(); auto type = inputs[0]->getType(); MNNUnaryExecute proc = nullptr; MNNUnaryExecuteInt8 procInt8 = nullptr; if (CPUBackend::getDataType(inputs[0]) == DataType_DT_INT8 || inputs[0]->getType().bytes() == 1) { procInt8 = core->MNNSelectUnaryFunctionForInt8(op->main_as_UnaryOp()->opType()); } else if (type.code == halide_type_int) { proc = selectForInt(op->main_as_UnaryOp()->opType()); } else if (type.code == halide_type_float) { proc = core->MNNSelectUnaryFunctionForFloat(op->main_as_UnaryOp()->opType(), static_cast<CPUBackend*>(backend)->precisionMode()); } if (nullptr == proc && nullptr == procInt8 && nullptr == op->main_as_UnaryOp()->tableInt8()) { MNN_ERROR("ERROR: Unary Op can not execute\n"); return nullptr; } return new CPUUnary(backend, proc, procInt8, op); } }; REGISTER_CPU_OP_CREATOR(CPUUnaryCreator, OpType_UnaryOp); } // namespace MNN