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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,77 @@ | ||
| #define _GLIBCXX_USE_CXX11_ABI 1 | ||
| #include "../src/model/SkewOPT.h" | ||
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| int ArgPos(char *str, int argc, char **argv) { | ||
| int a; | ||
| for (a = 1; a < argc; a++) if (!strcmp(str, argv[a])) { | ||
| if (a == argc - 1) { | ||
| printf("Argument missing for %s\n", str); | ||
| exit(1); | ||
| } | ||
| return a; | ||
| } | ||
| return -1; | ||
| } | ||
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| int main(int argc, char **argv){ | ||
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| int i; | ||
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| if (argc == 1) { | ||
| printf("[proNet-core]\n"); | ||
| printf("\tcommand spr interface for proNet-core\n\n"); | ||
| printf("Options Description:\n"); | ||
| printf("\t-train <string>\n"); | ||
| printf("\t\tTrain the Network data\n"); | ||
| printf("\t-save <string>\n"); | ||
| printf("\t\tSave the representation data\n"); | ||
| printf("\t-dimensions <int>\n"); | ||
| printf("\t\tDimension of vertex representation; default is 64\n"); | ||
| printf("\t-sample_times <int>\n"); | ||
| printf("\t\tNumber of training samples *Million; default is 10\n"); | ||
| printf("\t-threads <int>\n"); | ||
| printf("\t\tNumber of training threads; default is 1\n"); | ||
| printf("\t-reg <float>\n"); | ||
| printf("\t\tThe regularization term; default is 0.01\n"); | ||
| printf("\t-xi <float>\n"); | ||
| printf("\t\tThe xi term; default is 10.0\n"); | ||
| printf("\t-omega <float>\n"); | ||
| printf("\t\tThe omega term; default is 3.0\n"); | ||
| printf("\t-eta <float>\n"); | ||
| printf("\t\tThe eta term; default is 3.0\n"); | ||
| printf("\t-alpha <float>\n"); | ||
| printf("\t\tInit learning rate; default is 0.025\n"); | ||
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| printf("Usage:\n"); | ||
| printf("\n[SkewOPT]\n"); | ||
| printf("./spr -train net.txt -save rep.txt -dimensions 64 -sample_times 10 -alpha 0.025 -threads 1\n"); | ||
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| return 0; | ||
| } | ||
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| char network_file[100], rep_file[100]; | ||
| int dimensions=64, negative_samples=5, sample_times=10, threads=1, eta=3; | ||
| double init_alpha=0.025, reg=0.01, xi=10.0, omega=3.0; | ||
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| if ((i = ArgPos((char *)"-train", argc, argv)) > 0) strcpy(network_file, argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-save", argc, argv)) > 0) strcpy(rep_file, argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-dimensions", argc, argv)) > 0) dimensions = atoi(argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-sample_times", argc, argv)) > 0) sample_times = atoi(argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-reg", argc, argv)) > 0) reg = atof(argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-xi", argc, argv)) > 0) xi = atof(argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-omega", argc, argv)) > 0) omega = atof(argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-eta", argc, argv)) > 0) eta = atoi(argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-alpha", argc, argv)) > 0) init_alpha = atof(argv[i + 1]); | ||
| if ((i = ArgPos((char *)"-threads", argc, argv)) > 0) threads = atoi(argv[i + 1]); | ||
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| SPR *spr; | ||
| spr = new SPR(); | ||
| spr->LoadEdgeList(network_file, 0); | ||
| spr->Init(dimensions); | ||
| spr->Train(sample_times, negative_samples, init_alpha, reg, xi, omega, eta, threads); | ||
| spr->SaveWeights(rep_file); | ||
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| return 0; | ||
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| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,111 @@ | ||
| #include "SkewOPT.h" | ||
| #include <omp.h> | ||
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| SPR::SPR() { | ||
| char negative_method[15] = "no_degrees"; | ||
| pnet.SetNegativeMethod(negative_method); | ||
| } | ||
| SPR::~SPR() { | ||
| } | ||
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| void SPR::LoadEdgeList(string filename, bool undirect) { | ||
| pnet.LoadEdgeList(filename, undirect); | ||
| } | ||
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| void SPR::SaveWeights(string model_name){ | ||
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| cout << "Save Model:" << endl; | ||
| ofstream model(model_name); | ||
| if (model) | ||
| { | ||
| model << pnet.MAX_vid << " " << dim << endl; | ||
| for (long vid=0; vid!=pnet.MAX_vid; vid++) | ||
| { | ||
| model << pnet.vertex_hash.keys[vid]; | ||
| for (int d=0; d<dim; ++d) | ||
| model << " " << w_vertex[vid][d]; | ||
| model << endl; | ||
| } | ||
| cout << "\tSave to <" << model_name << ">" << endl; | ||
| } | ||
| else | ||
| { | ||
| cout << "\tfail to open file" << endl; | ||
| } | ||
| } | ||
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| void SPR::Init(int dim) { | ||
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| this->dim = dim; | ||
| cout << "Model Setting:" << endl; | ||
| cout << "\tdimension:\t\t" << dim << endl; | ||
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| w_vertex.resize(pnet.MAX_vid); | ||
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| for (long vid=0; vid<pnet.MAX_vid; ++vid) | ||
| { | ||
| w_vertex[vid].resize(dim); | ||
| for (int d=0; d<dim;++d) | ||
| w_vertex[vid][d] = (rand()/(double)RAND_MAX - 0.5) / dim + 0.01; | ||
| } | ||
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| } | ||
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| void SPR::Train(int sample_times, int negative_samples, double alpha, double reg, double xi, double omega, int eta, int workers){ | ||
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| omp_set_num_threads(workers); | ||
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| cout << "Model:" << endl; | ||
| cout << "\t[Skew-OPT]" << endl; | ||
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| cout << "Learning Parameters:" << endl; | ||
| cout << "\tsample_times:\t\t" << sample_times << endl; | ||
| cout << "\talpha:\t\t\t" << alpha << endl; | ||
| cout << "\tregularization:\t\t" << reg << endl; | ||
| cout << "\txi:\t\t\t" << xi << endl; | ||
| cout << "\tomega:\t\t\t" << omega << endl; | ||
| cout << "\teta:\t\t\t" << eta << endl; | ||
| cout << "\tworkers:\t\t" << workers << endl; | ||
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| cout << "Start Training:" << endl; | ||
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| unsigned long long total_sample_times = (unsigned long long)sample_times*1000000; | ||
| double alpha_min = alpha * 0.0001; | ||
| double alpha_last; | ||
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| unsigned long long current_sample = 0; | ||
| unsigned long long jobs = total_sample_times/workers; | ||
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| #pragma omp parallel for | ||
| for (int worker=0; worker<workers; ++worker) | ||
| { | ||
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| long v1, v2, v3; | ||
| unsigned long long count = 0; | ||
| double _alpha = alpha; | ||
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| while (count<jobs) | ||
| { | ||
| v1 = pnet.SourceSample(); | ||
| v2 = pnet.TargetSample(v1); | ||
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| pnet.UpdateSBPRPair(w_vertex, w_vertex, v1, v2, dim, reg, xi, omega, eta, _alpha); | ||
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| count ++; | ||
| if (count % MONITOR == 0) | ||
| { | ||
| _alpha = alpha* ( 1.0 - (double)(current_sample)/total_sample_times ); | ||
| current_sample += MONITOR; | ||
| if (_alpha < alpha_min) _alpha = alpha_min; | ||
| alpha_last = _alpha; | ||
| printf("\tAlpha: %.6f\tProgress: %.3f %%%c", _alpha, (double)(current_sample)/total_sample_times * 100, 13); | ||
| fflush(stdout); | ||
| } | ||
| } | ||
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| } | ||
| printf("\tAlpha: %.6f\tProgress: 100.00 %%\n", alpha_last); | ||
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| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,34 @@ | ||
| #ifndef SPR_H | ||
| #define SPR_H | ||
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| #include "../proNet.h" | ||
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| /***** | ||
| * SkewOPT | ||
| * **************************************************************/ | ||
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| class SPR { | ||
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| public: | ||
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| SPR(); | ||
| ~SPR(); | ||
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| proNet pnet; | ||
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| // parameters | ||
| int dim; // representation dimensions | ||
| vector< vector<double> > w_vertex; | ||
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| // data function | ||
| void LoadEdgeList(string, bool); | ||
| void SaveWeights(string); | ||
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| // model function | ||
| void Init(int); | ||
| void Train(int, int, double, double, double, double, int, int); | ||
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| }; | ||
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| #endif |
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