qiaohaijun/desm-diff.txt

## desm-diff.txt
``` bash
[@nmyjs_176_98 web.web_dnn.20170601.a.qhj_desm]# svn diff http://svn.sogou-inc.com/svn/websearch4/web/web_dnn/branches/desm2opt http://svn.sogou-inc.com/svn/websearch4/web/web_dnn/trunk
Authentication realm: <http://svn.sogou-inc.com:80> Sogou SVN
Password for 'qiaohaijun':
Index: src/gpu_server.cfg
===================================================================
--- src/gpu_server.cfg	(.../branches/desm2opt)	(revision 593977)
+++ src/gpu_server.cfg	(.../trunk)	(revision 593977)
@@ -10,7 +10,6 @@
 "DnnModelPath"="data/base/dnn.model"
 "CnnDicPath"="data/base/word2vec.v2"
 "CnnModelPath"="data/base/model.online.30yi.72.28"
-"DesmDicPath"="data/base/word2vec.mul"
 "dump_request_num"="20000000" #dumpµòequest¸
 "dump_request_file"="Dump_test" #dumpµ½´ƅ̵òequestτ¼þµٖ·
 "dump_request_interval"="1"  #dumpȫȳµļ乴£¬}ɧÿ¸𯰸󈬇򣴭pһ¸
Index: src/GPUPredictOnline.cu
===================================================================
--- src/GPUPredictOnline.cu	(.../branches/desm2opt)	(revision 593977)
+++ src/GPUPredictOnline.cu	(.../trunk)	(revision 593977)
@@ -3,11 +3,9 @@
 #include <vector>
 #include <assert.h>
 #include <stdio.h>
-#include <math.h>
 #include <iostream>
 #include <fstream>
-#include <pthread.h>
-#include <omp.h>
+#include <pthread.h>
 #include <cuda_runtime.h>
 #include <cublas_v2.h>
 #include <thrust/for_each.h>
@@ -157,22 +155,12 @@
 {
 public:
     int m_size;
-    int m_sense;
     std::string m_unknownword;
-    std::string m_unknownword_dnn;

     typedef __gnu_cxx::hash_map<std::string, std::vector<float>, str_hash, str_equal> StrVecMap;
     typedef StrVecMap::value_type StrVecMapType;
     typedef StrVecMap::iterator hashmapiter;

-
-	//For DESM
-    StrVecMap m_word2vec_dict_Vg;//single meaning words
-    StrVecMap m_word2vec_dict_Vs;//muti meaning words
-    hashmapiter m_endit_tst_Vg;
-    hashmapiter m_endit_tst_Vs;
-    std::vector<float> m_mulunk;
-    std::vector<float> m_dnnunk;
 	// For DNN.
     StrVecMap m_fastMapDict;
     thrust::host_vector<float>   m_padmat0;
@@ -265,100 +253,6 @@
 		}
 		return 0;
     }
-
-    int FastReadMulDict(const char* dictpath)
-    {
-	/**
-	For Mul_EM(emb.txt.fine.07200)
-	load pro and vec (1+100=101)
-	*/
-		long long words;
-		long long veclinenum;
-		//ifstream infile(dictpath,ios::in|ios::binary);
-		std::ifstream infile(dictpath);
-		if(!infile){
-			_INFO("load word2vec_mul fail");
-			return -1;
-		}
-
-		infile >> words;
-		infile >> veclinenum;
-		infile >> m_size;
-		m_sense = 3;
-
-		m_word2vec_dict_Vg.resize(words);
-		m_word2vec_dict_Vs.resize(words);
-		//float fea100;
-		//float fea300;
-		char cwords[512];
-		//float *feas = new float[m_size];
-		float *feas100 = new float[m_size+1];
-		_INFO("m_sense = %d", m_sense);
-		float *feas300 = new float[(m_size+1) * m_sense];
-		m_unknownword="</s>";
-		m_unknownword_dnn="</dnn_unk>";
-		//int len;
-		int w_sense;
-		//_INFO("VAL words = %lld", words);
-		//_INFO("VAL veclinenum = %lld", veclinenum);
-		//_INFO("VAL m_size = %d", m_size);
-		for(int i=0; i< words; ++i){
-			infile >> cwords;
-			infile >> w_sense;
-			//infile.read((char*)&len,sizeof(int));//len==length(termid) + 1?
-			//infile.read(cwords,len);
-			std::string cword(cwords);
-			if (w_sense == 1){
-				for (int dim=0;dim<m_size+1;dim++){
-					infile >> feas100[dim];
-				}
-				m_word2vec_dict_Vg.insert(StrVecMapType(cword, std::vector<float>(feas100, feas100 + m_size+1)));
-				//if(i<10){
-					//_INFO("VAL %d:%s feas100[0] = %f feas100[1] = %f", i, cwords, feas100[0], feas100[1]);
-				//}
-			}
-			else if (w_sense == 3){
-				for (int s=0;s<w_sense;s++){
-					for (int dim=0;dim<m_size+1;dim++){
-						infile >> feas300[(m_size+1)*s + dim];
-					}
-				}
-				m_word2vec_dict_Vs.insert(StrVecMapType(cword, std::vector<float>(feas300, feas300 + (m_size+1)*w_sense)));
-				//if(i<10){
-					//_INFO("VAL %d:%s feas300[0] = %f feas300[1] = %f", i, cwords, feas300[0], feas300[1]);
-				//}
-			}
-			else{
-				_INFO("read word2vec_mul error", m_size);
-				return -1;
-			}
-		}
-
-		m_mulunk = m_word2vec_dict_Vg[m_unknownword];
-		m_mulunk.erase(m_mulunk.begin());//erase the prob
-		//_INFO("m_mulunk.size() = %d", m_mulunk.size());
-
-		m_dnnunk = m_word2vec_dict_Vg[m_unknownword_dnn];
-		m_dnnunk.erase(m_dnnunk.begin());//erase the prob
-		//_INFO("m_dnnunk.size() = %d", m_dnnunk.size());
-
-		m_endit_tst_Vg = m_word2vec_dict_Vg.end();
-		m_endit_tst_Vs = m_word2vec_dict_Vs.end();
-
-		//_INFO("word2vec_dict_mul load words = %d + %d = %d", m_word2vec_dict_Vg.size(), m_word2vec_dict_Vs.size(), m_word2vec_dict_Vg.size()+m_word2vec_dict_Vs.size());
-		//cout<<"word2vec_dict load words = "<<m_word2vec_dict_Vg.size() + m_word2vec_dict_Vs.size()<<endl;
-		//SS_DEBUG((LM_DEBUG,"xn0: before infile closed\n"));
-		infile.close();
-		//delete [] feas;
-		//SS_DEBUG((LM_DEBUG,"xn1: before delete fea100\n"));
-		delete [] feas100;
-		feas100 = NULL;
-		//SS_DEBUG((LM_DEBUG,"xn2: before delete fea300\n"));
-		delete [] feas300;
-		feas300 = NULL;
-		//SS_DEBUG((LM_DEBUG,"xn3: after delete fea100\n"));
-		return 0;
-    }

 	void LoadDicToGPUMemory(int deviceId)
 	{
@@ -712,227 +606,8 @@
 	}
 };

-class DESMPredict {
-public:
-	std::vector<float> m_scores;
-	static int m_size;
-	static int m_sense;
-	typedef __gnu_cxx::hash_map<std::string, std::vector<float>, str_hash, str_equal> StrVecMap;
-	typedef StrVecMap::value_type StrVecMapType;
-	typedef StrVecMap::iterator hashmapiter;

-	bool CalculateScores (WordDictionary &wordDic, std::vector< std::vector< std::string > > &words){
-		std::vector<std::vector<std::vector<float> > > sentsWordsVecs;
-		Words2Vecs(wordDic, words, sentsWordsVecs);
-
-		std::vector<std::vector<float> > Tfeature;
-		GetTitlesCentroid(sentsWordsVecs, Tfeature);

-		QtDESMSim(sentsWordsVecs.back(), Tfeature, m_scores);
-
-		Tfeature.clear();
-		std::vector <std::vector<float> > (Tfeature).swap(Tfeature);
-		sentsWordsVecs.clear();
-		std::vector<std::vector<std::vector<float> > > (sentsWordsVecs).swap(sentsWordsVecs);
-		return true;
-	}
-
-private:
-
-	void Words2Vecs(WordDictionary &desmWordsDic, const std::vector< std::vector< std::string > > &words, std::vector<std::vector<std::vector<float> > > &sentsWordsVecs){
-		for(int sentIndex=0; sentIndex<words.size(); sentIndex++){
-			std::vector<std::vector<float> > wordsVecs;
-			int istrlen=words[sentIndex].size();
-			if (istrlen==0)
-			{
-				wordsVecs.push_back(desmWordsDic.m_dnnunk);
-				sentsWordsVecs.push_back(wordsVecs);
-				continue;
-			}
-
-			//<compute Vcontext
-			//for simple: context window == sentence length, and not skip the current word
-			std::vector<float> Vcontext;
-			Vcontext.resize(m_size);
-			int Rt = 0;
-
-			#pragma omp parallel for
-			for (int i = 0; i < istrlen; i++)
-			{
-				hashmapiter it = desmWordsDic.m_word2vec_dict_Vg.find(words[sentIndex][i]);
-				if ( it != desmWordsDic.m_endit_tst_Vg )
-				{
-					//xn_cuda:vec add
-					#pragma omp parallel for
-					for(int ii=0;ii<100;ii++)
-					{
-						Vcontext[ii] += (it->second)[ii+1];
-					}
-					Rt++;
-				}
-				else
-				{
-					hashmapiter it_Vs = desmWordsDic.m_word2vec_dict_Vs.find(words[sentIndex][i]);
-					if ( it_Vs != desmWordsDic.m_endit_tst_Vs ){
-						float maxprob = 0.0;
-						int maxprob_sense;
-						for (int s=0; s<m_sense; s++){
-							if ((it_Vs->second)[s*(m_size+1)] > maxprob){
-								maxprob = (it_Vs->second)[s*(m_size+1)];
-								maxprob_sense = s;
-							}
-						}
-						//xn_cuda:vec add
-						#pragma omp parallel for
-						for(int ii=0;ii<100;ii++){
-							Vcontext[ii] += (it_Vs->second)[maxprob_sense*(m_size+1)+(ii+1)];
-						}
-						Rt++;
-					}
-				}
-			}
-			if (Rt!=0){
-				//xn_cuda:vec/alpha
-				#pragma omp parallel for
-				for(int ii=0;ii<100;ii++){
-					Vcontext[ii] /= Rt;
-				}
-			}
-			//compute Vcontext>
-
-			#pragma omp parallel for
-			for(int i=0; i < istrlen;i++)
-			{
-				//<choose max_s(sense)
-				int max_s = 0;
-				float max_sim = -1;
-
-				std::vector<float> tmp;
-				tmp.resize(100);
-				hashmapiter it = desmWordsDic.m_word2vec_dict_Vg.find(words[sentIndex][i]);
-				if ( it != desmWordsDic.m_endit_tst_Vg )
-				{
-					#pragma omp parallel for
-					for(int ii=0;ii<100;ii++)
-					{
-						tmp[ii] = (it->second)[ii+1];
-					}
-					wordsVecs.push_back(tmp);
-				}
-				else
-				{
-					hashmapiter it_Vs = desmWordsDic.m_word2vec_dict_Vs.find(words[sentIndex][i]);
-					if ( it_Vs != desmWordsDic.m_endit_tst_Vs ){
-						#pragma omp parallel for
-						for (int s = 0; s < m_sense; s++){
-							float cos = -1, dot_product = 0, l_context = 0, l_u = 0;
-							//xn_cuda:vec mul
-							#pragma omp parallel for
-							for(int ii=0;ii<100;ii++){
-								dot_product += Vcontext[ii] * (it_Vs->second)[(ii+1)+s*(m_size+1)];
-								l_context += Vcontext[ii] * Vcontext[ii];
-								l_u += (it_Vs->second)[(ii+1)+s*(m_size+1)] * (it_Vs->second)[(ii+1)+s*(m_size+1)];
-							}
-							cos = dot_product / (sqrt(l_context)*sqrt(l_u));
-							if ( cos > max_sim) {
-								max_sim = cos;
-								max_s = s;
-							}
-						}
-						#pragma omp parallel for
-						for(int ii=0;ii<100;ii++)
-						{
-							tmp[ii] = (it_Vs->second)[(ii+1)+max_s*(m_size+1)];
-						}
-						wordsVecs.push_back(tmp);
-					}
-				}
-				tmp.clear();
-				std::vector<float>(tmp).swap(tmp);
-				//choose max_s(sense)>
-			}
-			if (wordsVecs.size()==0)
-			{
-				wordsVecs.push_back(desmWordsDic.m_dnnunk);
-				//return;
-			}
-			Vcontext.clear();
-			std::vector<float>(Vcontext).swap(Vcontext);
-			sentsWordsVecs.push_back(wordsVecs);
-			wordsVecs.clear();
-			std::vector<std::vector<float> >(wordsVecs).swap(wordsVecs);
-		}
-	}
-	void GetTitlesCentroid(const std::vector<std::vector<std::vector<float> > > sentsWordsVecs, std::vector<std::vector<float> > &titlesCentroid){
-		for(int titleIndex=0; titleIndex<sentsWordsVecs.size(); titleIndex++){
-			std::vector<float> vec_sum;
-			vec_sum.resize(m_size);
-
-			for(int i=0; i<sentsWordsVecs[titleIndex].size();i++){
-				//fmat vec_norm = arma::sum(wordsVecs[i]%wordsVecs[i], 0);//fmat default is col vec
-				//vec_norm = arma::sqrt(vec_norm);
-				//vec_sum += (wordsVecs[i]/vec_norm(0));
-
-				float vec_norm = 0.0f;
-				//xn_cuda:vec mul
-				#pragma omp parallel for
-				for(int j=0; j<m_size; j++){
-					vec_norm += sentsWordsVecs[titleIndex][i][j] * sentsWordsVecs[titleIndex][i][j];
-				}
-				vec_norm = sqrt(vec_norm);
-				//xn_cuda:vec/alpha
-				#pragma omp parallel for
-				for(int j=0; j<m_size; j++){
-					vec_sum[j] += sentsWordsVecs[titleIndex][i][j]/vec_norm;
-				}
-			}
-			//SS_DEBUG((LM_DEBUG,"xnMul:before compute titleCentroid <getTitleCentroidMul>"));
-			//titleCentroid = vec_sum/wordsVecs.size();
-			//xn_cuda:vec/alpha
-			#pragma omp parallel for
-			for(int i=0; i<m_size; i++){
-				vec_sum[i] /= sentsWordsVecs[titleIndex].size();
-			}
-			titlesCentroid.push_back(vec_sum);
-			//SS_DEBUG((LM_DEBUG,"xnMul:Outof getTitleCentroidMul"));
-			vec_sum.clear();
-			std::vector<float> (vec_sum).swap(vec_sum);
-		}
-	}
-	void QtDESMSim(const std::vector <std::vector<float> > wordsVecs, const std::vector<std::vector<float> > Tfeature,std::vector<float> & qtscore){
-		//SS_DEBUG((LM_DEBUG,"Tfeature.n_cols=%d",Tfeature.n_cols));
-		//qtscore.set_size(Tfeature.n_cols,1);
-		qtscore.resize(Tfeature.size());
-
-		for (int titleIndex=0;titleIndex<Tfeature.size();titleIndex++){
-				//SS_DEBUG((LM_DEBUG,"Tfeature %d",i));
-				float desm = 0.0f;
-				#pragma omp parallel for
-				for(int i=0;i<wordsVecs.size();i++){
-					float vec_dot = 0.0f, vec1_norm = 0.0f, vec2_norm = 0.0f, cosin = 0.0f;
-					//xn_cuda:vec mul
-					#pragma omp parallel for
-					for(int j=0;j<Tfeature[titleIndex].size();j++){
-						vec_dot += wordsVecs[i][j] * Tfeature[titleIndex][j];
-						vec1_norm += wordsVecs[i][j] * wordsVecs[i][j];
-						vec2_norm += Tfeature[titleIndex][j] * Tfeature[titleIndex][j];
-					}
-					vec1_norm = sqrt(vec1_norm);
-					vec2_norm = sqrt(vec2_norm);
-					cosin = vec_dot/(vec1_norm*vec2_norm);
-					desm += cosin;
-				}
-				desm /= wordsVecs.size();
-				//float cosin = DESM(wordsVecs, Tfeature[i]);
-				//qtscore(i,0) = cosin;
-				qtscore[titleIndex] = desm;
-				//SS_DEBUG((LM_DEBUG,"xnMul:i:%d cosin:%f", i, cosin));
-		}
-	}
-
-};
-int DESMPredict::m_size = 100;
-int DESMPredict::m_sense = 3;
 ////////////////////////////////////////////////////////////////
 // DNNCore
 ////////////////////////////////////////////////////////////////
@@ -2085,7 +1760,6 @@

 WordDictionary wordDic;
 WordDictionary cnnWordsDic;
-WordDictionary desmWordsDic;

 float* CNNConvDic::FindWord(const std::string& word) {
 	__gnu_cxx::hash_map<std::string, ConvMapKV*, str_hash, str_equal>::iterator it = proc_map.find(word);
@@ -2401,7 +2075,6 @@
     int m_threadId;
     DNNPredict m_dnn;
     CNNPredict m_cnn;
-	DESMPredict m_desm;
     WordDictionaryGPU m_wordDicGPUForDNN;
     WordDictionaryGPU m_wordDicGPUForCNN;
 };
@@ -2412,8 +2085,7 @@
         const char *dnnDicPath,
         const char *dnnModelPath,
         const char *cnnDicPath,
-        const char *cnnModelPath,
-        const char *desmDicPath
+        const char *cnnModelPath
 		)
 {
 	DataMembers *pDataMembers = new DataMembers();
@@ -2422,7 +2094,6 @@
 	m_dnnModelPath = dnnModelPath;
 	m_cnnDicPath = cnnDicPath;
 	m_cnnModelPath = cnnModelPath;
-	m_desmDicPath = desmDicPath;

 	ThreadArg *pArg = (ThreadArg*)arg;
 	pDataMembers->m_threadId = pArg->threadId;
@@ -2456,8 +2127,6 @@
 		cnnWordsDic.FastReadBinaryDict(m_cnnDicPath, false);
 		cnnWordsDic.PrepareForCNN(pDataMembers->m_cnn.m_CovMat);
 		cnn_conv_dict.GenHash(pDataMembers->m_cnn.m_CovMat, pArg->threadNum, pDataMembers->m_cnn.getMaxCols());
-
-		desmWordsDic.FastReadMulDict(m_desmDicPath);

 		_INFO("Load dictionarys into main memory finish.");
 	}
@@ -2489,16 +2158,13 @@
 GPUPredictOnline::RtnCode GPUPredictOnline::ProcessRequest(
         std::vector<std::vector<std::string> > &dnn_words_vec,
         std::vector<std::vector<std::string> > &cnn_words_vec,
-        std::vector<std::vector<std::string> > &desm_words_vec,
         std::vector<DnnScore> &dnnScores,
-        std::vector<CnnScore> &cnnScores,
-        std::vector<DesmScore> &desmScores
+        std::vector<CnnScore> &cnnScores
 		)
 {
 	DataMembers *pDataMembers = (DataMembers*)m_pDataMembers;
 	int dnn_sentence_count = dnn_words_vec.size();
 	int cnn_sentence_count = cnn_words_vec.size();
-	int desm_sentence_count = desm_words_vec.size();

 	{// 1. DNN
         int sentence_count = dnn_words_vec.size();
@@ -2537,12 +2203,10 @@
 			{
 				dnnScores[startId + i].score_5002 = pDataMembers->m_dnn.m_scores_FirstLayer[i];
 				dnnScores[startId + i].score_5003 = pDataMembers->m_dnn.m_scores[i];
-				//_INFO("DNN:%d:score_5002:%f score_5003:%f",i,dnnScores[startId + i].score_5002,dnnScores[startId + i].score_5003);
 			}
 			// Query-self score.
 			dnnScores[sentence_count - 1].score_5002 = pDataMembers->m_dnn.m_scores_FirstLayer[curBatchSize - 1];
-			dnnScores[sentence_count - 1].score_5003 = pDataMembers->m_dnn.m_scores[curBatchSize - 1];
-			//_INFO("DNN:Query-self:score_5002:%f score_5003:%f",dnnScores[sentence_count - 1].score_5002,dnnScores[sentence_count - 1].score_5003);
+			dnnScores[sentence_count - 1].score_5003 = pDataMembers->m_dnn.m_scores[curBatchSize - 1];
 		}
 	}
 #ifdef CHECK_CNN_CORRECTION
@@ -2603,67 +2267,13 @@
 			{
 				cnnScores[startId + i].score_5000 = pDataMembers->m_cnn.m_scores_FirstLayer[i];
 				cnnScores[startId + i].score_5001 = pDataMembers->m_cnn.m_scores[i];
-				//_INFO("CNN:%d:score_5000:%f score_5001:%f",i,cnnScores[i].score_5000,cnnScores[i].score_5001);
 			}
 			// Query-self score.
 			cnnScores[sentence_count - 1].score_5000 = pDataMembers->m_cnn.m_scores_FirstLayer[curBatchSize - 1];
 			cnnScores[sentence_count - 1].score_5001 = pDataMembers->m_cnn.m_scores[curBatchSize - 1];
-			//_INFO("CNN:Query-self:score_5000:%f score_5001:%f",cnnScores[sentence_count - 1].score_5000,cnnScores[sentence_count - 1].score_5001);
 		}
 	}// End 2. CNN

-	{// 3. DESM
-        int sentence_count = desm_words_vec.size();
-		if (!(sentence_count >= 2 && sentence_count <= MAX_MINIBATCH_SIZE)) // [2, MAX_MINIBATCH_SIZE]
-		{
-			return DesmSentenceCountOutOfRange;
-		}
-		desmScores.resize(sentence_count);
-		for (int startId = 0; startId < sentence_count - 1; startId += (MINIBATCH_BUFFER_SIZE - 1))
-		{
-			int endId = startId + (MINIBATCH_BUFFER_SIZE - 1);
-			if (endId > sentence_count - 1)
-			{
-				endId = sentence_count - 1;
-			}
-			int curBatchSize = endId - startId + 1;
-			std::vector<std::vector<std::string> > desm_words_vec_batch(curBatchSize);
-			for (int i = startId; i < endId; ++i)
-			{
-				desm_words_vec_batch[i - startId] = desm_words_vec[i];
-			}
-			desm_words_vec_batch[endId - startId] = desm_words_vec.back();
-
-			bool isValid;
-			isValid = pDataMembers->m_desm.CalculateScores(desmWordsDic, desm_words_vec_batch);
-			if (!isValid){
-				return DesmException;
-			}
-			/*
-			bool isValid = pDataMembers->m_dnn.MaxPooling(wordDic, pDataMembers->m_wordDicGPUForDNN, dnn_words_vec_batch);
-			if (!isValid)
-			{
-				return DnnWordsOverflow;
-			}
-			pDataMembers->m_dnn.SetMinibatchSize(curBatchSize);
-			pDataMembers->m_dnn.Forward();
-			pDataMembers->m_dnn.CosSim_FirstLayer();
-			pDataMembers->m_dnn.CosSim();
-			*/
-
-			// Query-Title scores.
-			for (int i = 0; i < curBatchSize - 1; ++i)
-			{
-				//dnnScores[startId + i].score_5002 = pDataMembers->m_dnn.m_scores_FirstLayer[i];
-				desmScores[startId + i].score_5004 = pDataMembers->m_desm.m_scores[i];
-				//_INFO("DESM:%d:score_5004:%f",i,desmScores[startId + i].score_5004);
-			}
-			// Query-self score.
-			//dnnScores[sentence_count - 1].score_5002 = pDataMembers->m_dnn.m_scores_FirstLayer[curBatchSize - 1];
-			desmScores[sentence_count - 1].score_5004 = pDataMembers->m_desm.m_scores[curBatchSize - 1];
-			//_INFO("DESM:Query-self:score_5004:%f",desmScores[sentence_count - 1].score_5004);
-		}
-	}
 	return OK;
 }

Index: src/server_configuration.hpp
===================================================================
--- src/server_configuration.hpp	(.../branches/desm2opt)	(revision 593977)
+++ src/server_configuration.hpp	(.../trunk)	(revision 593977)
@@ -27,7 +27,6 @@
         std::string dnn_model_path;
         std::string cnn_dic_path;
         std::string cnn_model_path;
-        std::string desm_dic_path;
         std::string dump_request_file;
         int dump_request_num;
         int dump_request_interval;
Index: src/gpu_calc_handler.cpp
===================================================================
--- src/gpu_calc_handler.cpp	(.../branches/desm2opt)	(revision 593977)
+++ src/gpu_calc_handler.cpp	(.../trunk)	(revision 593977)
@@ -35,13 +35,12 @@
     return server_task::open(DEFAULT_GPU_HANDLER_THREAD_NUM, stack_size);
 }

-int gpu_calc_handler::initialize(const std::string& dnn_dic_path, const std::string& dnn_model_path, const std::string& cnn_dic_path, const std::string& cnn_model_path, const std::string& desm_dic_path, int query_timeout)
+int gpu_calc_handler::initialize(const std::string& dnn_dic_path, const std::string& dnn_model_path, const std::string& cnn_dic_path, const std::string& cnn_model_path, int query_timeout)
 {
     dnn_dic_path_ = dnn_dic_path;
     dnn_model_path_ = dnn_model_path;
     cnn_dic_path_ = cnn_dic_path;
     cnn_model_path_ = cnn_model_path;
-    desm_dic_path_ = desm_dic_path;
     query_timeout_ = query_timeout;
 }

@@ -52,7 +51,7 @@
     return 0;
 }

-int gpu_calc_handler::convertRequest(ProtoContent::GpuRequest* request, std::vector<std::vector<std::string> >& dnn_words_vec, std::vector<std::vector<std::string> >& cnn_words_vec, std::vector<std::vector<std::string> >& desm_words_vec)
+int gpu_calc_handler::convertRequest(ProtoContent::GpuRequest* request, std::vector<std::vector<std::string> >& dnn_words_vec, std::vector<std::vector<std::string> >& cnn_words_vec)
 {
     dnn_words_vec.resize( request->dnn_words_size());
     for (int i = 0; i < request->dnn_words_size(); i++) {
@@ -70,18 +69,10 @@
 		    cnn_words_vec[i].push_back(cnn_words->words(j));
 	    }
     }
-    desm_words_vec.resize( request->dnn_words_size());//xn:cnn desm
-    for (int i = 0; i < request->dnn_words_size(); i++) {
-	    ProtoContent::TitleTerms* dnn_words = request->mutable_dnn_words(i);
-	    for (int j=0;j<dnn_words->words_size();j++)
-	    {
-		    desm_words_vec[i].push_back(dnn_words->words(j));
-	    }
-    }
     return 0;
 }

-int gpu_calc_handler::convertResult(ProtoContent::GpuResult* result, std::vector<DnnScore>& dnnScores, std::vector<CnnScore>& cnnScores, std::vector<DesmScore>& desmScores)
+int gpu_calc_handler::convertResult(ProtoContent::GpuResult* result, std::vector<DnnScore>& dnnScores, std::vector<CnnScore>& cnnScores)
 {
     if (dnnScores.size() != cnnScores.size()) {
         return -1;
@@ -92,7 +83,6 @@
         doc->set_dnn_5001(cnnScores[i].score_5001);
         doc->set_dnn_5002(dnnScores[i].score_5002);
         doc->set_dnn_5003(dnnScores[i].score_5003);
-		doc->set_dnn_5004(desmScores[i].score_5004);//xn:
     }
     const int default_dnn_cnn_version = 11;
     result->set_dnn_version(default_dnn_cnn_version);
@@ -115,7 +105,7 @@
     threadArg.p_predict_mutex = &predict_mutex_;
     pthread_mutex_unlock(&thread_mutex_);

-    predict.Initialize(&threadArg, dnn_dic_path_.c_str(), dnn_model_path_.c_str(), cnn_dic_path_.c_str(), cnn_model_path_.c_str(), desm_dic_path_.c_str());
+    predict.Initialize(&threadArg, dnn_dic_path_.c_str(), dnn_model_path_.c_str(), cnn_dic_path_.c_str(), cnn_model_path_.c_str());
     pthread_barrier_wait(&init_barr_);

     while ((worker = m_task_list.get()) != NULL)
@@ -133,8 +123,7 @@

         std::vector<std::vector<std::string> > dnn_words_vec;
         std::vector<std::vector<std::string> > cnn_words_vec;
-		std::vector<std::vector<std::string> > desm_words_vec;
-        if (convertRequest(worker->request, dnn_words_vec, cnn_words_vec, desm_words_vec))
+        if (convertRequest(worker->request, dnn_words_vec, cnn_words_vec))
         {
             _INFO("convertRequest Failed, req(%08x)", worker->request_id);
             m_manager->dispatch_worker(worker, this);
@@ -143,9 +132,8 @@

         std::vector<DnnScore> dnnScores;
         std::vector<CnnScore> cnnScores;
-		std::vector<DesmScore> desmScores;
         ACE_Time_Value t1 = ACE_OS::gettimeofday();
-        GPUPredictOnline::RtnCode rtn = predict.ProcessRequest(dnn_words_vec, cnn_words_vec, desm_words_vec, dnnScores, cnnScores, desmScores);
+        GPUPredictOnline::RtnCode rtn = predict.ProcessRequest(dnn_words_vec, cnn_words_vec, dnnScores, cnnScores);
         ACE_Time_Value t2 = ACE_OS::gettimeofday();
         if (rtn != GPUPredictOnline::OK)
         {
@@ -153,7 +141,7 @@
             m_manager->dispatch_worker(worker, this);
             continue;
         }
-        convertResult(worker->result, dnnScores, cnnScores, desmScores);
+        convertResult(worker->result, dnnScores, cnnScores);

         m_manager->dispatch_worker(worker, this);
     }
Index: src/gpu_calc_handler.hpp
===================================================================
--- src/gpu_calc_handler.hpp	(.../branches/desm2opt)	(revision 593977)
+++ src/gpu_calc_handler.hpp	(.../trunk)	(revision 593977)
@@ -11,13 +11,13 @@

     virtual int open(size_t thread_num, size_t stack_size);
     void wait_init_finish();
-    virtual int initialize(const std::string& dnn_dic_path, const std::string& dnn_model_path, const std::string& cnn_dic_path, const std::string& cnn_model_path, const std::string& desm_dic_path, int query_timeout);
+    virtual int initialize(const std::string& dnn_dic_path, const std::string& dnn_model_path, const std::string& cnn_dic_path, const std::string& cnn_model_path, int query_timeout);
     virtual int stop();
     virtual int svc();

 private:
-    int convertRequest(ProtoContent::GpuRequest* request, std::vector<std::vector<std::string> >& dnn_words_vec, std::vector<std::vector<std::string> >& cnn_words_vec, std::vector<std::vector<std::string> >& desm_words_vec);
-    int convertResult(ProtoContent::GpuResult* result, std::vector<DnnScore>& dnnScores, std::vector<CnnScore>& cnnScores, std::vector<DesmScore>& desmScores);
+    int convertRequest(ProtoContent::GpuRequest* request, std::vector<std::vector<std::string> >& dnn_words_vec, std::vector<std::vector<std::string> >& cnn_words_vec);
+    int convertResult(ProtoContent::GpuResult* result, std::vector<DnnScore>& dnnScores, std::vector<CnnScore>& cnnScores);

 private:
     int thread_index_;
@@ -29,7 +29,6 @@
     std::string dnn_model_path_;
     std::string cnn_dic_path_;
     std::string cnn_model_path_;
-    std::string desm_dic_path_;
     int query_timeout_;
 };

Index: src/ProtoContent.proto
===================================================================
--- src/ProtoContent.proto	(.../branches/desm2opt)	(revision 593977)
+++ src/ProtoContent.proto	(.../trunk)	(revision 593977)
@@ -21,7 +21,6 @@
 	required float dnn_5001 = 3;
 	required float dnn_5002 = 4;
 	required float dnn_5003 = 5;
-	optional float dnn_5004 = 6;
 }

 message GpuResult
Index: src/GPUPredictOnline.h
===================================================================
--- src/GPUPredictOnline.h	(.../branches/desm2opt)	(revision 593977)
+++ src/GPUPredictOnline.h	(.../trunk)	(revision 593977)
@@ -18,10 +18,6 @@
     float score_5000;
     float score_5001;
 };
-struct DesmScore
-{
-    float score_5004;
-};

 class GPUPredictOnline
 {
@@ -33,8 +29,6 @@
         DnnWordsOverflow,
         CnnSentenceCountOutOfRange,
         CnnWordsOverflow,
-        DesmSentenceCountOutOfRange,
-        DesmException,
     };
 public:
     void Initialize(
@@ -42,16 +36,13 @@
         const char *dnnDicPath,
         const char *dnnModelPath,
         const char *cnnDicPath,
-        const char *cnnModelPath,
-        const char *desmDicPath
+        const char *cnnModelPath
         );
     RtnCode ProcessRequest(
         std::vector<std::vector<std::string> > &dnn_words_vec,
         std::vector<std::vector<std::string> > &cnn_words_vec,
-        std::vector<std::vector<std::string> > &desm_words_vec,
         std::vector<DnnScore> &dnnScores,
-        std::vector<CnnScore> &cnnScores,
-        std::vector<DesmScore> &desmScores
+        std::vector<CnnScore> &cnnScores
         );
 private:
     void* m_pDataMembers;
@@ -59,5 +50,4 @@
     const char *m_dnnModelPath;
     const char *m_cnnDicPath;
     const char *m_cnnModelPath;
-    const char *m_desmDicPath;
 };
Index: src/main.cpp
===================================================================
--- src/main.cpp	(.../branches/desm2opt)	(revision 593977)
+++ src/main.cpp	(.../trunk)	(revision 593977)
@@ -93,7 +93,7 @@
 	manager.register_task(&task_reply);

 	task_receive.addr(config.listen_port);
-    task_gpu_calc.initialize(config.dnn_dic_path, config.dnn_model_path, config.cnn_dic_path, config.cnn_model_path, config.desm_dic_path, config.query_timeout);
+    task_gpu_calc.initialize(config.dnn_dic_path, config.dnn_model_path, config.cnn_dic_path, config.cnn_model_path, config.query_timeout);

     task_receive.set_dump_params(config.dump_request_file, config.dump_request_num, config.dump_request_interval);

Index: src/server_configuration.cpp
===================================================================
--- src/server_configuration.cpp	(.../branches/desm2opt)	(revision 593977)
+++ src/server_configuration.cpp	(.../trunk)	(revision 593977)
@@ -64,11 +64,7 @@
             return -1;
     cnn_model_path.assign(value);

-    if (config.get_value("DesmDicPath", value))
-            return -1;
-    desm_dic_path.assign(value);

-
     dump_request_num = 0;
     if(config.get_value("dump_request_num",value) == 0)
 	    dump_request_num = atoi(value);


```