From 20587ac550cfcb2d7b3d6ec16e46ba1a8d0af869 Mon Sep 17 00:00:00 2001
From: Joe Zhao <ztuowen@gmail.com>
Date: Wed, 13 May 2015 13:35:03 +0800
Subject: added split

---
 train.cpp | 147 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 147 insertions(+)
 create mode 100644 train.cpp

(limited to 'train.cpp')

diff --git a/train.cpp b/train.cpp
new file mode 100644
index 0000000..a0c62a9
--- /dev/null
+++ b/train.cpp
@@ -0,0 +1,147 @@
+#include <iostream>
+#include <Eigen/Dense>
+#include <boost/program_options.hpp>
+#include <list>
+#include "tools/easylogging++.h"
+#include "model/ranksvmtn.h"
+#include "tools/fileDataProvider.h"
+#include "model/rankaccu.h"
+
+INITIALIZE_EASYLOGGINGPP
+
+using namespace Eigen;
+using namespace std;
+namespace po = boost::program_options;
+
+po::variables_map vm;
+
+typedef int (*mainFunc)(DataProvider &dp);
+
+int train(DataProvider &dp) {
+    RSVM *rsvm;
+    rsvm = RSVM::loadModel(vm["model"].as<string>());
+
+    dp.open();
+    DataList D;
+
+    LOG(INFO)<<"Training started";
+    dp.getAllDataSet(D);
+    LOG(INFO)<<"Read "<<D.getSize()<<" entries with "<< D.getfSize()<<" features";
+    rsvm->train(D);
+    vector<double> L;
+    rsvm->predict(D,L);
+
+    LOG(INFO)<<"Training finished,saving model";
+
+    dp.close();
+    rsvm->saveModel(vm["output"].as<string>().c_str());
+    delete rsvm;
+    return 0;
+}
+
+int predict(DataProvider &dp) {
+    RSVM *rsvm;
+    rsvm = RSVM::loadModel(vm["model"].as<string>().c_str());
+
+    dp.open();
+    DataList D;
+    vector<double> L;
+    CMC cmc;
+    LOG(INFO)<<"Prediction started";
+
+    ofstream fout;
+
+    ostream* ot;
+
+    if (vm.count("output")) {
+        fout.open(vm["output"].as<string>().c_str());
+        ot=&fout;
+    }
+    else
+        ot=&cout;
+
+    while (!dp.EOFile())
+    {
+        dp.getDataSet(D);
+        LOG(INFO)<<"Read "<<D.getSize()<<" entries with "<< D.getfSize()<<" features";
+        rsvm->predict(D,L);
+
+        if (vm.count("validate"))
+        {
+            rank_accu(D,L);
+            if (vm.count("cmc"))
+                rank_CMC(D,L,cmc);
+        }
+
+        if (vm.count("output") || !vm.count("validate"))
+            for (int i=0; i<L.size();++i)
+                *ot<<L[i]<<endl;
+    }
+
+    LOG(INFO)<<"Finished";
+    if (vm.count("cmc"))
+    {
+        LOG(INFO)<< "CMC accounted over " <<cmc.getCount() << " queries";
+        *ot << "CMC"<<endl;
+        vector<double> cur = cmc.getAcc();
+        for (int i = 0;i<CMC_MAX;++i)
+        *ot << cur[i]<<endl;
+    }
+    if (vm.count("output"))
+        fout.close();
+    dp.close();
+    delete rsvm;
+    return 0;
+}
+
+int main(int argc, char **argv) {
+    el::Configurations defaultConf;
+    defaultConf.setToDefault();
+    // Values are always std::string
+    defaultConf.setGlobally(el::ConfigurationType::Format, "%datetime %level %msg");
+
+    // Defining program options
+    po::options_description desc("Allowed options");
+    desc.add_options()
+            ("help,h", "produce help message")
+            ("train,T", "training model")
+            ("validate,V", "validate model")
+            ("predict,P", "use model for prediction")
+            ("cmc,C", "enable cmc auditing")
+            ("debug,d", "show debug messages")
+            ("model,m", po::value<string>(), "set input model file")
+            ("output,o", po::value<string>(), "set output model/prediction file")
+            ("feature,i", po::value<string>(), "set input feature file");
+
+    // Parsing program options
+    po::store(po::parse_command_line(argc, argv, desc), vm);
+    po::notify(vm);
+
+    // Print help if necessary
+    if (vm.count("help") || !(vm.count("train") || vm.count("validate") || vm.count("predict"))) {
+        cout << desc;
+        return 0;
+    }
+
+    if (!vm.count("debug"))
+        defaultConf.setGlobally(el::ConfigurationType::Enabled, "false");
+    // default logger uses default configurations
+    el::Loggers::reconfigureLogger("default", defaultConf);
+
+    mainFunc mainf;
+    if (vm.count("train")) {
+        mainf = &train;
+    }
+    else if (vm.count("validate")||vm.count("predict")) {
+        mainf = &predict;
+    }
+    else return 0;
+    DataProvider* dp;
+    if (vm["feature"].as<string>().find(".rid") == string::npos)
+        dp = new FileDP(vm["feature"].as<string>());
+    else
+        dp = new RidFileDP(vm["feature"].as<string>());
+    mainf(*dp);
+    delete dp;
+    return 0;
+}
-- 
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