AlexNet模型实现（3. C++模型实现）
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对代码进行了一下修改https://github.com/aitazhixin/DL/tree/master/AlexNet，目前的运行效率比较低，准备采用多线程的方式实现一下。
根据原文，所有卷积层和池化层采用了ReLU激活函数，激活函数的导数为0或1（激活值非0时）。第三卷积层和第一、第二全连接层使用了Dropout方式。没有采用原文使用的LRN技术，采用了最大池化。在ImageNet2012数据集中选取了10类图片进行训练，但是迭代的效果不好。贴出代码希望集思广益，希望高手拔刀相助。
一些初始化或者辅助接口:
slqAlexNet::~slqAlexNet() { if (inRaw) { delete inRaw; inRaw = nullptr; } deletevar(&mlabel); deletevar(&inMap); deletevar(&c1Map); deletevar(&s1Map); deletevar(&c2Map); deletevar(&s2Map); deletevar(&c3Map); deletevar(&c4Map); deletevar(&c5Map); deletevar(&s5Map); deletevar(&f1Map); deletevar(&f2Map); deletevar(&f3Map); deletevar(&c1Conv); deletevar(&s1Pool); deletevar(&c2Conv); deletevar(&s2Pool); deletevar(&c3Conv); deletevar(&c4Conv); deletevar(&c5Conv); deletevar(&s5Pool); deletevar(&f1Conn); deletevar(&f2Conn); deletevar(&f3Conn); deletevar(&c1Bias); deletevar(&s1Bias); deletevar(&c2Bias); deletevar(&s2Bias); deletevar(&c3Bias); deletevar(&c4Bias); deletevar(&c5Bias); deletevar(&s5Bias); deletevar(&f1Bias); deletevar(&f2Bias); deletevar(&f3Bias); deletevar(&c1MapDt); deletevar(&s1MapDt); deletevar(&c2MapDt); deletevar(&s2MapDt); deletevar(&c3MapDt); deletevar(&c4MapDt); deletevar(&c5MapDt); deletevar(&s5MapDt); deletevar(&f1MapDt); deletevar(&f2MapDt); deletevar(&f3MapDt); deletevar(&c1ConvDt); deletevar(&s1PoolDt); deletevar(&c2ConvDt); deletevar(&s2PoolDt); deletevar(&c3ConvDt); deletevar(&c4ConvDt); deletevar(&c5ConvDt); deletevar(&s5PoolDt); deletevar(&f1ConnDt); deletevar(&f2ConnDt); deletevar(&f3ConnDt); deletevar(&c1BiasDt); deletevar(&s1BiasDt); deletevar(&c2BiasDt); deletevar(&s2BiasDt); deletevar(&c3BiasDt); deletevar(&c4BiasDt); deletevar(&c5BiasDt); deletevar(&s5BiasDt); deletevar(&f1BiasDt); deletevar(&f2BiasDt); deletevar(&f3BiasDt); deletevar(&c1ConvEDt); deletevar(&s1PoolEDt); deletevar(&c2ConvEDt); deletevar(&s2PoolEDt); deletevar(&c3ConvEDt); deletevar(&c4ConvEDt); deletevar(&c5ConvEDt); deletevar(&s5PoolEDt); deletevar(&f1ConnEDt); deletevar(&f2ConnEDt); deletevar(&f3ConnEDt); deletevar(&c1BiasEDt); deletevar(&s1BiasEDt); deletevar(&c2BiasEDt); deletevar(&s2BiasEDt); deletevar(&c3BiasEDt); deletevar(&c4BiasEDt); deletevar(&c5BiasEDt); deletevar(&s5BiasEDt); deletevar(&f1BiasEDt); deletevar(&f2BiasEDt); deletevar(&f3BiasEDt); } void slqAlexNet::init() { initParm(); } void slqAlexNet::CreateConv3Table() { int oIdx; int iIdx;#define AO true#define AX false for (oIdx = 0; oIdx < c3ConvNum; oIdx++) { for (iIdx = 0; iIdx < c3ConvDeep; iIdx++) { if ((oIdx >= iIdx) && (oIdx < iIdx + c3ConvDeep/2)) { CONV3Table[oIdx][iIdx] = AX; continue; } CONV3Table[oIdx][iIdx] = AO; } } for (oIdx = 0; oIdx < s5UnitNum; oIdx++) { for (iIdx = 0; iIdx < f1UnitNum; iIdx++) { if ((oIdx >= iIdx) && (oIdx < iIdx + f1UnitNum/2)) { F1Table[oIdx][iIdx] = AX; continue; } F1Table[oIdx][iIdx] = AO; } } for (oIdx = 0; oIdx < f1UnitNum; oIdx++) { for (iIdx = 0; iIdx < f2UnitNum; iIdx++) { if ((oIdx >= iIdx) && (oIdx < iIdx + f2UnitNum/2)) { F2Table[oIdx][iIdx] = AX; continue; } F2Table[oIdx][iIdx] = AO; } }#undef AO#undef AX } void slqAlexNet::deletevar(float **var) { if (nullptr != *var) { delete *var; *var = nullptr; } } void slqAlexNet::initParm() { newParam(); // all weights follow gauss distribution uniform_rand(c1Conv, c1ConvUNum, 0.f, 0.f); uniform_rand(s1Pool, s1MapNum, 0.f, 0.f); uniform_rand(c2Conv, c2ConvUNum, 0.f, 0.f); uniform_rand(s2Pool, s2MapNum, 0.f, 0.f); uniform_rand(c3Conv, c3ConvUNum, 0.f, 0.f); uniform_rand(c4Conv, c4ConvUNum, 0.f, 0.f); uniform_rand(c5Conv, c5ConvUNum, 0.f, 0.f); uniform_rand(s5Pool, s5MapNum, 0.f, 0.f); uniform_rand(f1Conn, f1ConnNum, 0.f, 0.f); uniform_rand(f2Conn, f2ConnNum, 0.f, 0.f); uniform_rand(f3Conn, f3ConnNum, 0.f, 0.f); // 2th, 4th, 5th conv bias set to 1 std::fill(c2Bias, c2Bias + c2MapNum, 1.0f); std::fill(c4Bias, c4Bias + c4MapNum, 1.0f); std::fill(c5Bias, c5Bias + c5MapNum, 1.0f); } void slqAlexNet::newParam() { mlabel = new float[f3UnitNum](); inRaw = new char[inUnitNum](); inMap = new float[inUnitNum](); c1Map = new float[c1UnitNum](); s1Map = new float[s1UnitNum](); c2Map = new float[c2UnitNum](); s2Map = new float[s2UnitNum](); c3Map = new float[c3UnitNum](); c4Map = new float[c4UnitNum](); c5Map = new float[c5UnitNum](); s5Map = new float[s5UnitNum](); f1Map = new float[f1UnitNum](); f2Map = new float[f2UnitNum](); f3Map = new float[f3UnitNum](); c1Conv = new float[c1ConvUNum](); s1Pool = new float[s1MapNum](); c2Conv = new float[c2ConvUNum](); s2Pool = new float[s2MapNum](); c3Conv = new float[c3ConvUNum](); c4Conv = new float[c4ConvUNum](); c5Conv = new float[c5ConvUNum](); s5Pool = new float[s5MapNum](); f1Conn = new float[f1ConnNum](); f2Conn = new float[f2ConnNum](); f3Conn = new float[f3ConnNum](); c1Bias = new float[c1MapNum](); s1Bias = new float[s1MapNum](); c2Bias = new float[c2MapNum](); s2Bias = new float[s2MapNum](); c3Bias = new float[c3MapNum](); c4Bias = new float[c4MapNum](); c5Bias = new float[c5MapNum](); s5Bias = new float[s5MapNum](); f1Bias = new float[f1UnitNum](); f2Bias = new float[f2UnitNum](); f3Bias = new float[f3UnitNum](); c1MapDt = new float[c1UnitNum](); s1MapDt = new float[s1UnitNum](); c2MapDt = new float[c2UnitNum](); s2MapDt = new float[s2UnitNum](); c3MapDt = new float[c3UnitNum](); c4MapDt = new float[c4UnitNum](); c5MapDt = new float[c5UnitNum](); s5MapDt = new float[s5UnitNum](); f1MapDt = new float[f1UnitNum](); f2MapDt = new float[f2UnitNum](); f3MapDt = new float[f3UnitNum](); c1ConvDt = new float[c1ConvUNum](); s1PoolDt = new float[s1MapNum](); c2ConvDt = new float[c2ConvUNum](); s2PoolDt = new float[s2MapNum](); c3ConvDt = new float[c3ConvUNum](); c4ConvDt = new float[c4ConvUNum](); c5ConvDt = new float[c5ConvUNum](); s5PoolDt = new float[s5MapNum](); f1ConnDt = new float[f1ConnNum](); f2ConnDt = new float[f2ConnNum](); f3ConnDt = new float[f3ConnNum](); c1BiasDt = new float[c1MapNum](); s1BiasDt = new float[s1MapNum](); c2BiasDt = new float[c2MapNum](); s2BiasDt = new float[s2MapNum](); c3BiasDt = new float[c3MapNum](); c4BiasDt = new float[c4MapNum](); c5BiasDt = new float[c5MapNum](); s5BiasDt = new float[s5MapNum](); f1BiasDt = new float[f1UnitNum](); f2BiasDt = new float[f2UnitNum](); f3BiasDt = new float[f3UnitNum](); c1ConvEDt = new float[c1ConvUNum](); s1PoolEDt = new float[s1MapNum](); c2ConvEDt = new float[c2ConvUNum](); s2PoolEDt = new float[s2MapNum](); c3ConvEDt = new float[c3ConvUNum](); c4ConvEDt = new float[c4ConvUNum](); c5ConvEDt = new float[c5ConvUNum](); s5PoolEDt = new float[s5MapNum](); f1ConnEDt = new float[f1ConnNum](); f2ConnEDt = new float[f2ConnNum](); f3ConnEDt = new float[f3ConnNum](); c1BiasEDt = new float[c1MapNum](); s1BiasEDt = new float[s1MapNum](); c2BiasEDt = new float[c2MapNum](); s2BiasEDt = new float[s2MapNum](); c3BiasEDt = new float[c3MapNum](); c4BiasEDt = new float[c4MapNum](); c5BiasEDt = new float[c5MapNum](); s5BiasEDt = new float[s5MapNum](); f1BiasEDt = new float[f1UnitNum](); f2BiasEDt = new float[f2UnitNum](); f3BiasEDt = new float[f3UnitNum](); } void slqAlexNet::UpgradeNetwork() { UpdateParameters(c1ConvDt, c1ConvEDt, c1Conv, c1ConvUNum); UpdateParameters(c1BiasDt, c1BiasEDt, c1Bias, c1MapNum); UpdateParameters(s1PoolDt, s1PoolEDt, s1Pool, s1MapNum); UpdateParameters(s1BiasDt, s1BiasEDt, s1Bias, s1MapNum); UpdateParameters(c2ConvDt, c2ConvEDt, c2Conv, c2ConvUNum); UpdateParameters(c2BiasDt, c2BiasEDt, c2Bias, c2MapNum); UpdateParameters(s2PoolDt, s2PoolEDt, s2Pool, s2MapNum); UpdateParameters(s2BiasDt, s2BiasEDt, s2Bias, s2MapNum); UpdateParameters(c3ConvDt, c3ConvEDt, c3Conv, c3ConvUNum); UpdateParameters(c3BiasDt, c3BiasEDt, c3Bias, c3MapNum); UpdateParameters(c4ConvDt, c4ConvEDt, c4Conv, c4ConvUNum); UpdateParameters(c4BiasDt, c4BiasEDt, c4Bias, c4MapNum); UpdateParameters(c5ConvDt, c5ConvEDt, c5Conv, c5ConvUNum); UpdateParameters(c5BiasDt, c5BiasEDt, c5Bias, c5MapNum); UpdateParameters(s5PoolDt, s5PoolEDt, s5Pool, s5MapNum); UpdateParameters(s5BiasDt, s5BiasEDt, s5Bias, s5MapNum); UpdateParameters(f1ConnDt, f1ConnEDt, f1Conn, f1ConnNum); UpdateParameters(f1BiasDt, f1BiasEDt, f1Bias, f1UnitNum); UpdateParameters(f2ConnDt, f2ConnEDt, f2Conn, f2ConnNum); UpdateParameters(f2BiasDt, f2BiasEDt, f2Bias, f2UnitNum); UpdateParameters(f3ConnDt, f3ConnEDt, f3Conn, f3ConnNum); UpdateParameters(f3BiasDt, f3BiasEDt, f3Bias, f3UnitNum); } void slqAlexNet::UpdateParameters(float *delta, float *Edelta, float *para, int len) { for (int lIdx = 0; lIdx < len; lIdx++) { Edelta[lIdx] = 0.9f * Edelta[lIdx] - 0.0005 * Alpha * delta[lIdx]; para[lIdx] += Edelta[lIdx]; } } void slqAlexNet::ConvolutionOpt(float *inPtr, float *outPtr, float *convPtr, float *biPtr, int param[]) { int inMapNo = param[0]; int outMapNo = param[1]; int inMapH = param[2]; int inMapW = param[3]; int outMapH = param[4]; int outMapW = param[5]; int convH = param[6]; int convW = param[7]; int convStride = param[8]; int expand = param[9]; int odeepIdx; int ideepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; int svh; int insize = inMapH * inMapW; int convsize = inMapNo * convH * convW; int convtsor = convH * convW; for (odeepIdx = 0; odeepIdx < outMapNo; odeepIdx++) { for (ohIdx = expand; ohIdx < outMapH - expand; ohIdx++) { iod = odeepIdx * outMapH * outMapW + ohIdx * outMapW; for (owIdx = expand; owIdx < outMapW - expand; owIdx++) { float *curmap = outPtr + iod + owIdx; float cur = 0.f; for (ideepIdx = 0; ideepIdx < inMapNo; ideepIdx++) { if ((inMapNo == s2MapNum) && (outMapNo == c3MapNum) && (!CONV3Table[odeepIdx][ideepIdx])) continue; vod = odeepIdx * convsize + ideepIdx * convtsor; svh = ideepIdx * insize + (ohIdx - expand) * convStride * inMapW + (owIdx - expand) * convStride; float *curcv = convPtr + vod; float *curin = inPtr + svh; for (phIdx = 0; phIdx < convH; phIdx++) { for (pwIdx = 0; pwIdx < convW; pwIdx++) { cur += *(curcv + phIdx * convW + pwIdx) * (*(curin + phIdx * inMapW + pwIdx)); } } } *curmap = cur + *(biPtr + odeepIdx); *curmap = ACTIVATION(*curmap); } } } } void slqAlexNet::PoolingOpt(float *inPtr, float *outPtr, float *poolPtr, float *biPtr, int param[]) { int mapNo = param[0]; int imapH = param[1]; int imapW = param[2]; int omapH = param[3]; int omapW = param[4]; int poolspace = param[5]; int poolstride = param[6]; int expand = param[7]; int deepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; for(deepIdx = 0; deepIdx < mapNo; deepIdx++) { for (ohIdx = expand; ohIdx < omapH - expand; ohIdx++) { iod = deepIdx * omapH * omapW + ohIdx * omapW; for (owIdx = expand; owIdx < omapW - expand; owIdx++) { vod = deepIdx * imapH * imapW + (ohIdx - expand) * poolstride * imapW + (owIdx - expand) * poolstride; float *curmap = outPtr + iod + owIdx; float *curin = inPtr + vod; float cur = FLT_MIN; for (phIdx = 0; phIdx < poolspace; phIdx++) { for (pwIdx = 0; pwIdx < poolspace; pwIdx++) { //cur += *(curin + phIdx * imapW + pwIdx); cur = cur >(*(curin + phIdx * imapW + pwIdx)) ? cur : (*(curin + phIdx * imapW + pwIdx)); } } //*curmap = cur / (poolspace * poolspace) + *(biPtr + deepIdx); *curmap = cur + *(biPtr + deepIdx); *curmap = ACTIVATION(*curmap); } } } } void slqAlexNet::SaveParameters() { ofstream fileStream; fileStream.open("alexParams", ofstream::out | ofstream::binary); if (!fileStream) { cout << "Error to create Parameters file" << endl; return; } fileStream.write((char*)c1Conv, c1ConvUNum * sizeof(float)); fileStream.write((char*)c1BiasDt, c1MapNum * sizeof(float)); fileStream.write((char*)s1PoolDt, s1MapNum * sizeof(float)); fileStream.write((char*)s1BiasDt, s1MapNum * sizeof(float)); fileStream.write((char*)c2ConvDt, c2ConvUNum * sizeof(float)); fileStream.write((char*)c2BiasDt, c2MapNum * sizeof(float)); fileStream.write((char*)s2PoolDt, s2MapNum * sizeof(float)); fileStream.write((char*)s2BiasDt, s2MapNum * sizeof(float)); fileStream.write((char*)c3ConvDt, c3ConvUNum * sizeof(float)); fileStream.write((char*)c3BiasDt, c3MapNum * sizeof(float)); fileStream.write((char*)c4ConvDt, c4ConvUNum * sizeof(float)); fileStream.write((char*)c4BiasDt, c4MapNum * sizeof(float)); fileStream.write((char*)c5ConvDt, c5ConvUNum * sizeof(float)); fileStream.write((char*)c5BiasDt, c5MapNum * sizeof(float)); fileStream.write((char*)s5PoolDt, s5MapNum * sizeof(float)); fileStream.write((char*)s5BiasDt, s5MapNum * sizeof(float)); fileStream.write((char*)f1ConnDt, f1ConnNum * sizeof(float)); fileStream.write((char*)f1BiasDt, f1UnitNum * sizeof(float)); fileStream.write((char*)f2ConnDt, f2ConnNum * sizeof(float)); fileStream.write((char*)f2BiasDt, f2UnitNum * sizeof(float)); fileStream.write((char*)f3ConnDt, f3ConnNum * sizeof(float)); fileStream.write((char*)f3BiasDt, f3UnitNum * sizeof(float)); } void slqAlexNet::ReadParameters() { ifstream fileStream; fileStream.open("alexParams", ifstream::in | ifstream::binary); if (!fileStream) { cout << "Error to Open Params file" << endl; return; } fileStream.read((char*)c1Conv, c1ConvUNum * sizeof(float)); fileStream.read((char*)c1BiasDt, c1MapNum * sizeof(float)); fileStream.read((char*)s1PoolDt, s1MapNum * sizeof(float)); fileStream.read((char*)s1BiasDt, s1MapNum * sizeof(float)); fileStream.read((char*)c2ConvDt, c2ConvUNum * sizeof(float)); fileStream.read((char*)c2BiasDt, c2MapNum * sizeof(float)); fileStream.read((char*)s2PoolDt, s2MapNum * sizeof(float)); fileStream.read((char*)s2BiasDt, s2MapNum * sizeof(float)); fileStream.read((char*)c3ConvDt, c3ConvUNum * sizeof(float)); fileStream.read((char*)c3BiasDt, c3MapNum * sizeof(float)); fileStream.read((char*)c4ConvDt, c4ConvUNum * sizeof(float)); fileStream.read((char*)c4BiasDt, c4MapNum * sizeof(float)); fileStream.read((char*)c5ConvDt, c5ConvUNum * sizeof(float)); fileStream.read((char*)c5BiasDt, c5MapNum * sizeof(float)); fileStream.read((char*)s5PoolDt, s5MapNum * sizeof(float)); fileStream.read((char*)s5BiasDt, s5MapNum * sizeof(float)); fileStream.read((char*)f1ConnDt, f1ConnNum * sizeof(float)); fileStream.read((char*)f1BiasDt, f1UnitNum * sizeof(float)); fileStream.read((char*)f2ConnDt, f2ConnNum * sizeof(float)); fileStream.read((char*)f2BiasDt, f2UnitNum * sizeof(float)); fileStream.read((char*)f3ConnDt, f3ConnNum * sizeof(float)); fileStream.read((char*)f3BiasDt, f3UnitNum * sizeof(float)); } void slqAlexNet::RandomBias(float *randVector, int vLen) {} void slqAlexNet::ProduceLabel() { int lIdx; for (lIdx = 0; lIdx < f3UnitNum; lIdx++) { if (curLabl == lIdx) { mlabel[lIdx] = 0.8f; } else { mlabel[lIdx] = -0.8f; } } } void slqAlexNet::RegularMap(char *cmap, float *mapdata) { int mIdx; float maxv = -10.f; float minv = 256.f; char *curc = cmap; float *curmap = mapdata; for (mIdx = 0; mIdx < inMapSize; mIdx++) { float cur = curc[mIdx] < 0 ? (curc[mIdx] + 256.f) : curc[mIdx]; maxv = cur > maxv ? cur : maxv; minv = cur < minv ? cur : minv; } for (mIdx = 0; mIdx < inMapSize; mIdx++) { float cur = curc[mIdx] < 0 ? (curc[mIdx] + 256.f) : curc[mIdx]; curmap[mIdx] = (cur - minv) / (maxv - minv) * 2.f - 1.f; } maxv = -10.f; minv = 256.f; curc = cmap + inMapSize; curmap = mapdata + inMapSize; for (mIdx = 0; mIdx < inMapSize; mIdx++) { float cur = curc[mIdx] < 0 ? (curc[mIdx] + 256.f) : curc[mIdx]; maxv = cur > maxv ? cur : maxv; minv = cur < minv ? cur : minv; } for (mIdx = 0; mIdx < inMapSize; mIdx++) { float cur = curc[mIdx] < 0 ? (curc[mIdx] + 256.f) : curc[mIdx]; curmap[mIdx] = (cur - minv) / (maxv - minv) * 2.f - 1.f; } maxv = -10.f; minv = 256.f; curc = cmap + inMapSize*2; curmap = mapdata + inMapSize*2; for (mIdx = 0; mIdx < inMapSize; mIdx++) { float cur = curc[mIdx] < 0 ? (curc[mIdx] + 256.f) : curc[mIdx]; maxv = cur > maxv ? cur : maxv; minv = cur < minv ? cur : minv; } for (mIdx = 0; mIdx < inMapSize; mIdx++) { float cur = curc[mIdx] < 0 ? (curc[mIdx] + 256.f) : curc[mIdx]; curmap[mIdx] = (cur - minv) / (maxv - minv) * 2.f - 1.f; } } void slqAlexNet::uniform_rand(float* src, int len, float min, float max) { int rIdx = 0; for (; rIdx < len; rIdx++) { src[rIdx] = uniform_rand(min, max); } } float slqAlexNet::uniform_rand(float min, float max) { static float U, V; static int phase = 0; float gaussz = 0; if (0 == phase) { U = (rand() + EspCNN) / (RAND_MAX + 1.0f); V = (rand() + EspCNN) / (RAND_MAX + 1.0f); gaussz = 0.01f * std::sqrt(-2.0f * log(U)) * sin(2.0f * CV_PI * V); } else { gaussz = 0.01f * std::sqrt(-2.0f * log(U)) * cos(2.0f * CV_PI * V); } phase = 1 - phase; return gaussz; }训练接口：
void slqAlexNet::train() { int epo; int ipo = 0; float acc = 0.0f; ifstream trainStream; ifstream trainlabel; for (epo = 0; epo < EpochLoop; epo++) { trainStream.open("imgTrainArray", ifstream::in | ifstream::binary); trainlabel.open("imgTrainLabel", ifstream::in | ifstream::binary); if ((!trainStream) || (!trainlabel)) { if (trainStream) trainStream.close(); if (trainlabel) trainlabel.close(); cout << "There does not exist train data" << endl; return; } while (EOF != trainStream.peek()) { trainStream.read(inRaw, sizeof(char)*inUnitNum); trainlabel.read(&curLabl, sizeof(char)); //Mat img(227, 227, CV_8UC1); //memcpy((char*)img.data, inRaw, 227*227); //cv::namedWindow("inRaw"); //cv::imshow("inRaw", img); //cv::waitKey(0); //memcpy((char*)img.data, inRaw + 227*227, 227 * 227); //cv::namedWindow("inRaw"); //cv::imshow("inRaw", img); //cv::waitKey(0); //memcpy((char*)img.data, inRaw + 227*227*2, 227 * 227); //cv::namedWindow("inRaw"); //cv::imshow("inRaw", img); //cv::waitKey(0); ProduceLabel(); RegularMap(inRaw, inMap); ForwardC1(); ForwardS1(); ForwardC2(); ForwardS2(); ForwardC3(); ForwardC4(); ForwardC5(); ForwardS5(); ForwardF1(); ForwardF2(); ForwardF3(); BackwardF3(); BackwardF2(); BackwardF1(); BackwardS5(); BackwardC5(); BackwardC4(); BackwardC3(); BackwardS2(); BackwardC2(); BackwardS1(); BackwardC1(); UpgradeNetwork(); ipo++; } trainlabel.close(); trainStream.close(); acc = test(); cout << "epoch " << epo << " accuracy " << acc << endl; if (acc >= AccuracyRate) { cout << "Save Params ..." << endl; SaveParameters(); } else if (acc < 0) { return; } } if (EpochLoop == epo) { cout << "End loop, Save Params" << endl; SaveParameters(); } }验证接口：
float slqAlexNet::test() { float acc = 0.f; float prc = 0.f; float maxv = -10.f; int maxI; char tlabl; int mIdx; int count = 0; ifstream testStream; ifstream testlabl; testStream.open("imgTestArray", ifstream::in | ifstream::binary); testlabl.open("imgTestLabel", ifstream::in | ifstream::binary); if ((!testStream) || !testlabl) { if (testStream) testStream.close(); if (testlabl) testlabl.close(); cout << "There does not exist test data" << endl; return -1.f; } while (EOF != testStream.peek()) { count++; testStream.read(inRaw, sizeof(char)* inUnitNum); testlabl.read(&tlabl, sizeof(char)); RegularMap(inRaw, inMap); ForwardC1(); ForwardS1(); ForwardC2(); ForwardS2(); ForwardC3(); ForwardC4(); ForwardC5(); ForwardS5(); ForwardF1(); ForwardF2(); ForwardF3(); for (mIdx = 0; mIdx < f3UnitNum; mIdx++) { maxI = f3Map[mIdx] > maxv ? mIdx : maxI; maxv = f3Map[mIdx] > maxv ? f3Map[mIdx] : maxv; } if (maxI == tlabl) prc += 1; } testStream.close(); testlabl.close(); return (prc / count); }前向运算：
void slqAlexNet::ForwardC1() { int params[] = {inMapNum, c1MapNum, inMapHigh, inMapWidth, c1MapHigh, c1MapWidth, c1ConvHigh, c1ConvWidth, c1ConvStride, 0 }; std::fill(c1Map, c1Map + c1UnitNum, 0.f); ConvolutionOpt(inMap, c1Map, c1Conv, c1Bias, params); } void slqAlexNet::ForwardS1() { int params[] = {s1MapNum, c1MapHigh, c1MapWidth, s1MapHigh, s1MapWidth, poolSpace, poolStride, 2}; float tmp[c1UnitNum]; memcpy((char*)tmp, (char*)c1Map, sizeof(float)*c1UnitNum); std::fill(s1Map, s1Map + s1UnitNum, 0.f); PoolingOpt(c1Map, s1Map, s1Pool, s1Bias, params); } void slqAlexNet::ForwardC2() { int params[] = { s1MapNum / 2, c2MapNum / 2, s1MapHigh, s1MapWidth, c2MapHigh, c2MapWidth, c2ConvHigh, c2ConvWidth, c2ConvStride, 0 }; float tmp[s1UnitNum]; memcpy((char*)tmp, (char*)s1Map, sizeof(float)*s1UnitNum); std::fill(c2Map, c2Map + c2UnitNum, 0.f); ConvolutionOpt(s1Map, c2Map, c2Conv, c2Bias, params); ConvolutionOpt(s1Map + s1MapNum / 2 * s1MapSize, c2Map + c2MapNum / 2 * c2MapSize, c2Conv + c2MapNum / 2 * c2ConvSize, c2Bias + c2MapNum / 2, params); } void slqAlexNet::ForwardS2() { int params[] = { s2MapNum, c2MapHigh, c2MapWidth, s2MapHigh, s2MapWidth, poolSpace, poolStride, 1 }; float tmp[c2UnitNum]; memcpy((char*)tmp, (char*)c2Map, sizeof(float)*c2UnitNum); std::fill(s2Map, s2Map + s2UnitNum, 0.f); PoolingOpt(c2Map, s2Map, s2Pool, s2Bias, params); } void slqAlexNet::ForwardC3() { int params[] = { s2MapNum, c3MapNum, s2MapHigh, s2MapWidth, c3MapHigh, c3MapWidth, c3ConvHigh, c3ConvWidth, c3ConvStride, 1 }; float tmp[s2UnitNum]; memcpy((char*)tmp, (char*)s2Map, sizeof(float)*s2UnitNum); std::fill(c3Map, c3Map + c3UnitNum, 0.f); ConvolutionOpt(s2Map, c3Map, c3Conv, c3Bias, params); } void slqAlexNet::ForwardC4() { int params[] = { c3MapNum / 2, c4MapNum / 2, c3MapHigh, c3MapWidth, c4MapHigh, c4MapWidth, c4ConvHigh, c4ConvWidth, c4ConvStride, 1 }; float tmp[c3UnitNum]; memcpy((char*)tmp, (char*)c3Map, sizeof(float)*c3UnitNum); std::fill(c4Map, c4Map + c4UnitNum, 0.f); ConvolutionOpt(c3Map, c4Map, c4Conv, c4Bias, params); ConvolutionOpt(c3Map + c3MapNum / 2 * c3MapSize, c4Map + c4MapNum / 2 * c4MapSize, c4Conv + c4MapNum / 2 * c4ConvSize, c4Bias + c4MapNum / 2, params); } void slqAlexNet::ForwardC5() { int params[] = { c4MapNum / 2, c5MapNum / 2, c4MapHigh, c4MapWidth, c5MapHigh, c5MapWidth, c5ConvHigh, c5ConvWidth, c5ConvStride, 0 }; float tmp[c4UnitNum]; memcpy((char*)tmp, (char*)c4Map, sizeof(float)*c4UnitNum); std::fill(c5Map, c5Map + c5UnitNum, 0.f); ConvolutionOpt(c4Map, c5Map, c5Conv, c5Bias, params); ConvolutionOpt(c4Map + c4MapNum / 2 * c4MapSize, c5Map + c5MapNum / 2 * c5MapSize, c5Conv + c5MapNum / 2 * c5ConvSize, c5Bias + c5MapNum / 2, params); } void slqAlexNet::ForwardS5() { int params[] = { s5MapNum, c5MapHigh, c5MapWidth, s5MapHigh, s5MapWidth, poolSpace, poolStride, 0 }; float tmp[c5UnitNum]; memcpy((char*)tmp, (char*)c5Map, sizeof(float)*c5UnitNum); std::fill(s5Map, s5Map + s5UnitNum, 0.f); PoolingOpt(c5Map, s5Map, s5Pool, s5Bias, params); } void slqAlexNet::ForwardF1() { int oIdx; int iIdx; float tmp[s5UnitNum]; memcpy((char*)tmp, (char*)s5Map, sizeof(float)*s5UnitNum); std::fill(f1Map, f1Map + f1UnitNum, 0.f); for (oIdx = 0; oIdx < f1UnitNum; oIdx++) { float *curmap = f1Map + oIdx; for (iIdx = 0; iIdx < s5UnitNum; iIdx++) { if (!F1Table[iIdx][oIdx]) continue; *curmap += s5Map[iIdx] * f1Conn[iIdx * f1UnitNum + oIdx]; } *curmap += f1Bias[oIdx]; *curmap = ACTIVATION(*curmap); } } void slqAlexNet::ForwardF2() { int oIdx; int iIdx; float tmp[f1UnitNum]; memcpy((char*)tmp, (char*)f1Map, sizeof(float)*f1UnitNum); std::fill(f2Map, f2Map + f2UnitNum, 0.f); for (oIdx = 0; oIdx < f2UnitNum; oIdx++) { float *curmap = f2Map + oIdx; for (iIdx = 0; iIdx < f1UnitNum; iIdx++) { if (!F2Table[iIdx][oIdx]) continue; *curmap += f1Map[iIdx] * f2Conn[iIdx * f2UnitNum + oIdx]; } *curmap += f2Bias[oIdx]; *curmap = ACTIVATION(*curmap); } } void slqAlexNet::ForwardF3() { int oIdx; int iIdx; float tmp[f2UnitNum]; memcpy((char*)tmp, (char*)f2Map, sizeof(float)*f2UnitNum); std::fill(f3Map, f3Map + f3UnitNum, 0.f); for (oIdx = 0; oIdx < f3UnitNum; oIdx++) { float *curmap = f3Map + oIdx; for (iIdx = 0; iIdx < f2UnitNum; iIdx++) { *curmap += f2Map[iIdx] * f3Conn[iIdx * f3UnitNum + oIdx]; } *curmap += f3Bias[oIdx]; *curmap = ACTIVATION(*curmap); } }反馈运算：
void slqAlexNet::BackwardF3() { int oIdx; int iIdx; float tmpf3[f3UnitNum]; memcpy((char*)tmpf3, (char*)f3Map, sizeof(float)*f3UnitNum); for (oIdx = 0; oIdx < f3UnitNum; oIdx++) { f3MapDt[oIdx] = (f3Map[oIdx] - mlabel[oIdx]) * ACTDEVICE(f3Map[oIdx]); f3BiasDt[oIdx] = f3MapDt[oIdx]; for (iIdx = 0; iIdx < f2UnitNum; iIdx++) { f3ConnDt[iIdx*f3UnitNum + oIdx] = f3MapDt[oIdx] * f2Map[iIdx]; } } } void slqAlexNet::BackwardF2() { int oIdx; int iIdx; for (oIdx = 0; oIdx < f2UnitNum; oIdx++) { float curdt = 0.f; for (iIdx = 0; iIdx < f3UnitNum; iIdx++) { curdt += f3MapDt[iIdx] * f3Conn[oIdx * f3UnitNum + iIdx]; } f2MapDt[oIdx] = ACTDEVICE(f2Map[oIdx]) * curdt; f2BiasDt[oIdx] = f2MapDt[oIdx]; for (iIdx = 0; iIdx < f1UnitNum; iIdx++) { if (!F2Table[iIdx][oIdx]) continue; f2ConnDt[iIdx * f2UnitNum + oIdx] = f2MapDt[oIdx] * f1Map[iIdx]; } } } void slqAlexNet::BackwardF1() { int oIdx; int iIdx; for (oIdx = 0; oIdx < f1UnitNum; oIdx++) { float curdt = 0.f; for (iIdx = 0; iIdx < f2UnitNum; iIdx++) { if (!F2Table[oIdx][iIdx]) continue; curdt += f2MapDt[iIdx] * f2Conn[oIdx * f2UnitNum + iIdx]; } f1MapDt[oIdx] = ACTDEVICE(f1Map[oIdx]) * curdt; f1BiasDt[oIdx] = f1MapDt[oIdx]; for (iIdx = 0; iIdx < s5UnitNum; iIdx++) { if (!F1Table[iIdx][oIdx]) continue; f1ConnDt[iIdx * f1UnitNum + oIdx] = f1MapDt[oIdx] * s5Map[iIdx]; } } } void slqAlexNet::BackwardS5() { int iIdx; int iod; int odeepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; std::fill(s5BiasDt, s5BiasDt + s5MapNum, 0.f); std::fill(s5PoolDt, s5PoolDt + s5MapNum, 0.f); for (odeepIdx = 0; odeepIdx < s5MapNum; odeepIdx++) { for (ohIdx = 0; ohIdx < s5MapHigh; ohIdx++) { iod = odeepIdx*s5MapSize + ohIdx * s5MapWidth; for (owIdx = 0; owIdx < s5MapWidth; owIdx++) { float curdt = 0.f; for (iIdx = 0; iIdx < f1UnitNum; iIdx++) { if (!F1Table[iod + owIdx][iIdx]) continue; curdt += f1MapDt[iIdx] * f1Conn[(iod + owIdx)*f1UnitNum + iIdx]; } s5MapDt[iod + owIdx] = ACTDEVICE(s5Map[iod + owIdx]) * curdt; s5BiasDt[odeepIdx] += s5MapDt[iod + owIdx]; float *curin = c5Map + odeepIdx * c5MapSize + ohIdx * poolStride * c5MapWidth + owIdx * poolStride; curdt = FLT_MIN; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { curdt = curdt > (*(curin + phIdx * c5MapWidth + pwIdx)) ? curdt : (*(curin + phIdx * c5MapWidth + pwIdx)); } } s5PoolDt[odeepIdx] += curdt * s5MapDt[iod + owIdx]; } } } } void slqAlexNet::BackwardC5() { int odeepIdx; int ideepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; int svh; std::fill(c5MapDt, c5MapDt + c5UnitNum, 0.f); std::fill(c5BiasDt, c5BiasDt + c5MapNum, 0.f); std::fill(c5ConvDt, c5ConvDt + c5ConvUNum, 0.f); for (odeepIdx = 0; odeepIdx < c5MapNum; odeepIdx++) { for (ohIdx = 0; ohIdx < s5MapHigh; ohIdx++) { for (owIdx = 0; owIdx < s5MapWidth; owIdx++) { iod = odeepIdx * c5MapSize + ohIdx * poolStride * c5MapWidth + owIdx * poolStride; vod = odeepIdx * s5MapSize + ohIdx * s5MapWidth + owIdx; float curmax = FLT_MIN; int hmax = 0; int wmax = 0; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { hmax = curmax > c5Map[iod + phIdx * c5MapWidth + pwIdx] ? hmax : phIdx; wmax = curmax > c5Map[iod + phIdx * c5MapWidth + pwIdx] ? wmax : pwIdx; curmax = curmax > c5Map[iod + phIdx * c5MapWidth + pwIdx] ? curmax : c5Map[iod + phIdx * c5MapWidth + pwIdx]; } } c5MapDt[iod + hmax * c5MapWidth + wmax] += ACTDEVICE(c5Map[iod + hmax * c5MapWidth + wmax]) * s5Pool[odeepIdx] * s5MapDt[vod]; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { c5BiasDt[odeepIdx] += c5MapDt[iod + phIdx * c5MapWidth + pwIdx]; } } } } } for (odeepIdx = 0; odeepIdx < c5MapNum / 2; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c5ConvDeep; ideepIdx++) { for (phIdx = 0; phIdx < c5ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c5ConvWidth; pwIdx++) { iod = odeepIdx * c5ConvSize + ideepIdx * c5ConvTensor + phIdx * c5ConvWidth + pwIdx; float *curconv = c5ConvDt + iod; for (ohIdx = 0; ohIdx < c5MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c5MapWidth; owIdx++) { svh = ideepIdx * c4MapSize + (phIdx + ohIdx * c5ConvStride)*c4MapWidth + (pwIdx + owIdx * c5ConvStride); vod = odeepIdx * c5MapSize + ohIdx * c5MapWidth + owIdx; *curconv += c4Map[svh] * c5MapDt[vod]; } } } } } } for (odeepIdx = c5MapNum / 2; odeepIdx < c5MapNum; odeepIdx++) { for (ideepIdx = c5ConvDeep; ideepIdx < c4MapNum; ideepIdx++) { for (phIdx = 0; phIdx < c5ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c5ConvWidth; pwIdx++) { iod = odeepIdx * c5ConvSize + (ideepIdx - c5ConvDeep) * c5ConvTensor + phIdx * c5ConvWidth + pwIdx; float *curconv = c5ConvDt + iod; for (ohIdx = 0; ohIdx < c5MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c5MapWidth; owIdx++) { svh = ideepIdx * c4MapSize + (phIdx + ohIdx * c5ConvStride)*c4MapWidth + (pwIdx + owIdx * c5ConvStride); vod = odeepIdx * c5MapSize + ohIdx * c5MapWidth + owIdx; *curconv += c4Map[svh] * c5MapDt[vod]; } } } } } } } void slqAlexNet::BackwardC4() { int odeepIdx; int ideepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; int svh; std::fill(c4MapDt, c4MapDt + c4UnitNum, 0.f); std::fill(c4BiasDt, c4BiasDt + c4MapNum, 0.f); std::fill(c4ConvDt, c4ConvDt + c4ConvUNum, 0.f); for (odeepIdx = 0; odeepIdx < c4MapNum / 2; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c5MapNum / 2; ideepIdx++) { for (phIdx = 0; phIdx < c5ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c5ConvWidth; pwIdx++) { svh = ideepIdx * c5ConvSize + odeepIdx * c5ConvTensor + phIdx * c5ConvWidth + pwIdx; for (ohIdx = 0; ohIdx < c5MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c5MapWidth; owIdx++) { iod = odeepIdx * c4MapSize + (phIdx + ohIdx * c5ConvStride) * c4MapWidth + (pwIdx + owIdx * c5ConvStride); vod = ideepIdx * c5MapSize + ohIdx * c5MapWidth + owIdx; c4MapDt[iod] += ACTDEVICE(c4Map[iod]) * c5Conv[svh] * c5MapDt[vod]; } } } } } } for (odeepIdx = c4MapNum / 2; odeepIdx < c4MapNum; odeepIdx++) { for (ideepIdx = c5MapNum / 2; ideepIdx < c5MapNum; ideepIdx++) { for (phIdx = 0; phIdx < c5ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c5ConvWidth; pwIdx++) { svh = ideepIdx * c5ConvSize + (odeepIdx - c5ConvDeep) * c5ConvTensor + phIdx * c5ConvWidth + pwIdx; for (ohIdx = 0; ohIdx < c5MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c5MapWidth; owIdx++) { iod = odeepIdx * c4MapSize + (phIdx + ohIdx * c5ConvStride) * c4MapWidth + (pwIdx + owIdx * c5ConvStride); vod = ideepIdx * c5MapSize + ohIdx * c5MapWidth + owIdx; c4MapDt[iod] += ACTDEVICE(c4Map[iod]) * c5Conv[svh] * c5MapDt[vod]; } } } } } } for (odeepIdx = 0; odeepIdx < c4MapNum / 2; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c4ConvDeep; ideepIdx++) { for (phIdx = 0; phIdx < c4ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c4ConvWidth; pwIdx++) { iod = odeepIdx * c4ConvSize + ideepIdx * c4ConvTensor + phIdx * c4ConvWidth + pwIdx; for (ohIdx = 1; ohIdx < c4MapHigh - 1; ohIdx++) { for (owIdx = 1; owIdx < c4MapWidth - 1; owIdx++) { vod = odeepIdx * c4MapSize + ohIdx * c4MapWidth + owIdx; svh = ideepIdx * c3MapSize + ((ohIdx - 1) * c4ConvStride + phIdx) * c3MapWidth + ((owIdx - 1) * c4ConvStride + pwIdx); c4BiasDt[odeepIdx] += c4MapDt[vod]; c4ConvDt[iod] += c3Map[svh] * c4MapDt[vod]; } } } } } } for (odeepIdx = c4MapNum / 2; odeepIdx < c4MapNum; odeepIdx++) { for (ideepIdx = c4ConvDeep; ideepIdx < c3MapNum; ideepIdx++) { for (phIdx = 0; phIdx < c4ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c4ConvWidth; pwIdx++) { iod = odeepIdx * c4ConvSize + (ideepIdx - c4ConvDeep) * c4ConvTensor + phIdx * c4ConvWidth + pwIdx; for (ohIdx = 1; ohIdx < c4MapHigh - 1; ohIdx++) { for (owIdx = 1; owIdx < c4MapWidth - 1; owIdx++) { vod = odeepIdx * c4MapSize + ohIdx * c4MapWidth + owIdx; svh = ideepIdx * c3MapSize + ((ohIdx - 1) * c4ConvStride + phIdx) * c3MapWidth + ((owIdx - 1) * c4ConvStride + pwIdx); c4BiasDt[odeepIdx] += c4MapDt[vod]; c4ConvDt[iod] += c3Map[svh] * c4MapDt[vod]; } } } } } } } void slqAlexNet::BackwardC3() { int odeepIdx; int ideepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; int svh; std::fill(c3MapDt, c3MapDt + c3UnitNum, 0.f); std::fill(c3BiasDt, c3BiasDt + c3MapNum, 0.f); std::fill(c3ConvDt, c3ConvDt + c3ConvUNum, 0.f); for (odeepIdx = 0; odeepIdx < c3MapNum / 2; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c4MapNum / 2; ideepIdx++) { for (phIdx = 0; phIdx < c4ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c4ConvWidth; pwIdx++) { svh = ideepIdx * c4ConvSize + odeepIdx * c4ConvTensor + phIdx * c4ConvWidth + pwIdx; for (ohIdx = 1; ohIdx < c4MapHigh - 1; ohIdx++) { for (owIdx = 1; owIdx < c4MapWidth - 1; owIdx++) { iod = odeepIdx * c3MapSize + (phIdx + (ohIdx - 1) * c4ConvStride) * c3MapWidth + (pwIdx + (owIdx - 1) * c4ConvStride); vod = ideepIdx * c4MapSize + ohIdx * c4MapWidth + owIdx; c3MapDt[iod] += ACTDEVICE(c3Map[iod]) * c4Conv[svh] * c4MapDt[vod]; } } } } } } for (odeepIdx = c3MapNum / 2; odeepIdx < c3MapNum; odeepIdx++) { for (ideepIdx = c4MapNum / 2; ideepIdx < c4MapNum; ideepIdx++) { for (phIdx = 0; phIdx < c4ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c4ConvWidth; pwIdx++) { svh = ideepIdx * c4ConvSize + (odeepIdx - c4ConvDeep) * c4ConvTensor + phIdx * c4ConvWidth + pwIdx; for (ohIdx = 1; ohIdx < c4MapHigh - 1; ohIdx++) { for (owIdx = 1; owIdx < c4MapWidth - 1; owIdx++) { iod = odeepIdx * c3MapSize + (phIdx + (ohIdx - 1) * c4ConvStride) * c3MapWidth + (pwIdx + (owIdx - 1) * c4ConvStride); vod = ideepIdx * c4MapSize + ohIdx * c4MapWidth + owIdx; c3MapDt[iod] += ACTDEVICE(c3Map[iod]) * c4Conv[svh] * c4MapDt[vod]; } } } } } } for (odeepIdx = 0; odeepIdx < c3MapNum; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c3ConvDeep; ideepIdx++) { if (!CONV3Table[odeepIdx][ideepIdx]) continue; for (phIdx = 0; phIdx < c3ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c3ConvWidth; pwIdx++) { iod = odeepIdx * c3ConvSize + ideepIdx * c3ConvTensor + phIdx * c3ConvWidth + pwIdx; for (ohIdx = 1; ohIdx < c3MapHigh - 1; ohIdx++) { for (owIdx = 1; owIdx < c3MapWidth - 1; owIdx++) { vod = odeepIdx * c3MapSize + ohIdx * c3MapWidth + owIdx; svh = ideepIdx * s2MapSize + ((ohIdx - 1) * c3ConvStride + phIdx) * s2MapWidth + ((owIdx - 1) * c3ConvStride + pwIdx); c3BiasDt[odeepIdx] += c3MapDt[vod]; c3ConvDt[iod] += c3MapDt[vod] * s2Map[svh]; } } } } } } } void slqAlexNet::BackwardS2() { int odeepIdx; int ideepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; int svh; std::fill(s2MapDt, s2MapDt + s2UnitNum, 0.f); std::fill(s2BiasDt, s2BiasDt + s2MapNum, 0.f); std::fill(s2PoolDt, s2PoolDt + s2MapNum, 0.f); for (odeepIdx = 0; odeepIdx < s2MapNum; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c3MapNum; ideepIdx++) { if (!CONV3Table[ideepIdx][odeepIdx]) continue; for (phIdx = 0; phIdx < c3ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c3ConvWidth; pwIdx++) { svh = ideepIdx * c3ConvSize + odeepIdx * c3ConvTensor + phIdx * c3ConvWidth + pwIdx; for (ohIdx = 1; ohIdx < c3MapHigh - 1; ohIdx++) { for (owIdx = 1; owIdx < c3MapWidth - 1; owIdx++) { iod = odeepIdx * s2MapSize + (phIdx + (ohIdx - 1) * c3ConvStride) * s2MapWidth + (pwIdx + (owIdx - 1) * c3ConvStride); vod = ideepIdx * c3MapSize + ohIdx * c3MapWidth + owIdx; s2MapDt[iod] += ACTDEVICE(s2Map[iod]) * c3Conv[svh] * c3MapDt[vod]; } } } } } } for (odeepIdx = 0; odeepIdx < s2MapNum; odeepIdx++) { for (ohIdx = 1; ohIdx < s2MapHigh - 1; ohIdx++) { iod = odeepIdx*s2MapSize + ohIdx * s2MapWidth; for (owIdx = 1; owIdx < s2MapWidth - 1; owIdx++) { float *curin = c2Map + odeepIdx * c2MapSize + (ohIdx - 1) * poolStride * c2MapWidth + (owIdx - 1) * poolStride; float curdt = FLT_MIN; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { curdt = curdt >(*(curin + phIdx * c2MapWidth + pwIdx)) ? curdt : (*(curin + phIdx * c2MapWidth + pwIdx)); } } s2BiasDt[odeepIdx] += s2MapDt[iod + owIdx]; s2PoolDt[odeepIdx] += curdt * s2MapDt[iod + owIdx]; } } } } void slqAlexNet::BackwardC2() { int odeepIdx; int ideepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; int svh; std::fill(c2MapDt, c2MapDt + c2UnitNum, 0.f); std::fill(c2BiasDt, c2BiasDt + c2MapNum, 0.f); std::fill(c2ConvDt, c2ConvDt + c2ConvUNum, 0.f); for (odeepIdx = 0; odeepIdx < c2MapNum; odeepIdx++) { for (ohIdx = 1; ohIdx < s2MapHigh - 1; ohIdx++) { for (owIdx = 1; owIdx < s2MapWidth - 1; owIdx++) { iod = odeepIdx * c2MapSize + (ohIdx - 1) * poolStride * c2MapWidth + (owIdx - 1) * poolStride; vod = odeepIdx * s2MapSize + ohIdx * s2MapWidth + owIdx; float curmax = FLT_MIN; int hmax = 0; int wmax = 0; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { hmax = curmax > c2Map[iod + phIdx * c2MapWidth + pwIdx] ? hmax : phIdx; wmax = curmax > c2Map[iod + phIdx * c2MapWidth + pwIdx] ? wmax : pwIdx; curmax = curmax > c2Map[iod + phIdx * c2MapWidth + pwIdx] ? curmax : c2Map[iod + phIdx * c2MapWidth + pwIdx]; } } c2MapDt[iod + hmax * c2MapWidth + wmax] += ACTDEVICE(c2Map[iod + phIdx * c2MapWidth + pwIdx]) * s2Pool[odeepIdx] * s2MapDt[vod]; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { c2BiasDt[odeepIdx] += c2MapDt[iod + phIdx * c2MapWidth + pwIdx]; } } } } } for (odeepIdx = 0; odeepIdx < c2MapNum / 2; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c2ConvDeep; ideepIdx++) { for (phIdx = 0; phIdx < c2ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c2ConvWidth; pwIdx++) { iod = odeepIdx * c2ConvSize + ideepIdx * c2ConvTensor + phIdx * c2ConvWidth + pwIdx; for (ohIdx = 0; ohIdx < c2MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c2MapWidth; owIdx++) { vod = odeepIdx * c2MapSize + ohIdx * c2MapWidth + owIdx; svh = ideepIdx * s1MapSize + (ohIdx * c2ConvStride + phIdx) * s1MapWidth + (owIdx * c2ConvStride + pwIdx); c2ConvDt[iod] += c2MapDt[vod] * s1Map[svh]; } } } } } } for (odeepIdx = c2MapNum / 2; odeepIdx < c2MapNum; odeepIdx++) { for (ideepIdx = c2ConvDeep; ideepIdx < s1MapNum; ideepIdx++) { for (phIdx = 0; phIdx < c2ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c2ConvWidth; pwIdx++) { iod = odeepIdx * c2ConvSize + (ideepIdx - c2ConvDeep) * c2ConvTensor + phIdx * c2ConvWidth + pwIdx; for (ohIdx = 0; ohIdx < c2MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c2MapWidth; owIdx++) { vod = odeepIdx * c2MapSize + ohIdx * c2MapWidth + owIdx; svh = ideepIdx * s1MapSize + (ohIdx * c2ConvStride + phIdx) * s1MapWidth + (owIdx * c2ConvStride + pwIdx); c2ConvDt[iod] += c2MapDt[vod] * s1Map[svh]; } } } } } } } void slqAlexNet::BackwardS1() { int odeepIdx; int ideepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; int svh; std::fill(s1MapDt, s1MapDt + s1UnitNum, 0.f); std::fill(s1BiasDt, s1BiasDt + s1MapNum, 0.f); std::fill(s1PoolDt, s1PoolDt + s1MapNum, 0.f); for (odeepIdx = 0; odeepIdx < s1MapNum / 2; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c2ConvDeep; ideepIdx++) { for (phIdx = 0; phIdx < c2ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c2ConvWidth; pwIdx++) { vod = odeepIdx * c2ConvSize + ideepIdx * c2ConvTensor + phIdx * c2ConvHigh + pwIdx; for (ohIdx = 0; ohIdx < c2MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c2MapWidth; owIdx++) { iod = odeepIdx * s1MapSize + (ohIdx * c2ConvStride + phIdx) * s1MapWidth + (owIdx * c2ConvStride + pwIdx); svh = ideepIdx * c2MapSize + ohIdx * c2MapWidth + owIdx; s1MapDt[iod] += ACTDEVICE(s1Map[iod]) * c2Conv[vod] * c2MapDt[svh]; } } } } } } for (odeepIdx = s1MapNum / 2; odeepIdx < s1MapNum; odeepIdx++) { for (ideepIdx = 0; ideepIdx < c2ConvDeep; ideepIdx++) { for (phIdx = 0; phIdx < c2ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c2ConvWidth; pwIdx++) { vod = odeepIdx * c2ConvSize + ideepIdx * c2ConvTensor + phIdx * c2ConvHigh + pwIdx; for (ohIdx = 0; ohIdx < c2MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c2MapWidth; owIdx++) { iod = odeepIdx * s1MapSize + (ohIdx * c2ConvStride + phIdx) * s1MapWidth + (owIdx * c2ConvStride + pwIdx); svh = (ideepIdx + c2ConvDeep) * c2MapSize + ohIdx * c2MapWidth + owIdx; s1MapDt[iod] += ACTDEVICE(s1Map[iod]) * c2Conv[vod] * c2MapDt[svh]; } } } } } } for (odeepIdx = 0; odeepIdx < s1MapNum; odeepIdx++) { for (ohIdx = 2; ohIdx < s1MapHigh - 2; ohIdx++) { iod = odeepIdx*s1MapSize + ohIdx * s1MapWidth; for (owIdx = 2; owIdx < s1MapWidth - 2; owIdx++) { float *curin = c1Map + odeepIdx * c1MapSize + (ohIdx - 2) * poolStride * c1MapWidth + (owIdx - 2) * poolStride; float curdt = FLT_MIN; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { curdt = curdt > (*(curin + phIdx * c1MapWidth + pwIdx)) ? curdt : (*(curin + phIdx * c1MapWidth + pwIdx)); } } s1BiasDt[odeepIdx] += s1MapDt[iod + owIdx]; s1PoolDt[odeepIdx] += curdt * s1MapDt[iod + owIdx]; } } } } void slqAlexNet::BackwardC1() { int odeepIdx; int ideepIdx; int ohIdx; int owIdx; int phIdx; int pwIdx; int iod; int vod; int svh; std::fill(c1MapDt, c1MapDt + c1UnitNum, 0.f); std::fill(c1BiasDt, c1BiasDt + c1MapNum, 0.f); std::fill(c1ConvDt, c1ConvDt + c1ConvUNum, 0.f); for (odeepIdx = 0; odeepIdx < c1MapNum; odeepIdx++) { for (ohIdx = 2; ohIdx < s1MapHigh - 2; ohIdx++) { for (owIdx = 2; owIdx < s1MapWidth - 2; owIdx++) { iod = odeepIdx * c1MapSize + (ohIdx - 2) * poolStride * c1MapWidth + (owIdx - 2) * poolStride; vod = odeepIdx * s1MapSize + ohIdx * s1MapWidth + owIdx; float curmax = FLT_MIN; int hmax = 0; int wmax = 0; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { hmax = curmax > c1Map[iod + phIdx * c1MapWidth + pwIdx] ? hmax : phIdx; wmax = curmax > c1Map[iod + phIdx * c1MapWidth + pwIdx] ? wmax : pwIdx; curmax = curmax > c1Map[iod + phIdx * c1MapWidth + pwIdx] ? curmax : c1Map[iod + phIdx * c1MapWidth + pwIdx]; } } c1MapDt[iod + hmax * c1MapWidth + wmax] += ACTDEVICE(c1Map[iod + hmax * c1MapWidth + wmax]) * s1Pool[odeepIdx] * s1MapDt[vod]; for (phIdx = 0; phIdx < poolSpace; phIdx++) { for (pwIdx = 0; pwIdx < poolSpace; pwIdx++) { c1BiasDt[odeepIdx] += c1MapDt[iod + phIdx * c1MapWidth + pwIdx]; } } } } for (ideepIdx = 0; ideepIdx < c1ConvDeep; ideepIdx++) { for (phIdx = 0; phIdx < c1ConvHigh; phIdx++) { for (pwIdx = 0; pwIdx < c1ConvWidth; pwIdx++) { vod = odeepIdx * c1ConvSize + ideepIdx * c1ConvTensor + phIdx * c1ConvWidth + pwIdx; for (ohIdx = 0; ohIdx < c1MapHigh; ohIdx++) { for (owIdx = 0; owIdx < c1MapWidth; owIdx++) { iod = ideepIdx * inMapSize + (phIdx + ohIdx * c1ConvStride) * inMapWidth + (pwIdx + owIdx * c1ConvStride); svh = odeepIdx * c1MapSize + ohIdx * c1MapWidth + owIdx; c1ConvDt[vod] += inMap[iod] * c1MapDt[svh]; } } } } } } }阅读全文
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