1 files changed, 106 insertions, 0 deletions
diff --git a/dtrain/updater.h b/dtrain/updater.h
new file mode 100644
index 00000000..6307a005
--- /dev/null
+++ b/dtrain/updater.h
@@ -0,0 +1,106 @@
+#ifndef _DTRAIN_LEARNER_H_
+#define _DTRAIN_LEARNER_H_
+
+#include <string>
+#include <vector>
+#include <map>
+
+#include "sparse_vector.h"
+#include "score.h"
+
+
+namespace dtrain
+{
+
+
+class Updater
+{
+  public:
+    virtual void Init( const vector<SparseVector<double> >& kbest, const Scores& scores,
+                       const bool invert_score = false ) {};
+    virtual void Update( SparseVector<double>& lambdas ) {};
+};
+
+
+class SofiaUpdater : public Updater
+{
+  public:
+    void
+    Init( const size_t sid, const vector<SparseVector<double> >& kbest, /*const FIXME operator[]*/ Scores& scores,
+          const bool invert_score = false )
+    {
+      assert( kbest.size() == scores.size() );
+      ofstream o;
+      char tmp[] = DTRAIN_TMP_DIR"/dtrain-sofia-data-XXXXXX";
+      mkstemp( tmp );
+      tmp_data_fn = tmp;
+      o.open( tmp_data_fn.c_str(), ios::trunc );
+      int fid = 0;
+      map<int,int>::iterator ff;
+      double score;
+      for ( size_t k = 0; k < kbest.size(); ++k ) {
+        map<int,double> m;
+        SparseVector<double>::const_iterator it = kbest[k].begin();
+        score = scores[k].GetScore();
+        if ( invert_score ) score = -score;
+        o << score;
+        for ( ; it != kbest[k].end(); ++it ) {
+          ff = fmap.find( it->first );
+          if ( ff == fmap.end() ) {
+            fmap.insert( pair<int,int>(it->first, fid) );
+            fmap1.insert( pair<int,int>(fid, it->first) );
+            fid++;
+          }
+          m.insert( pair<int,double>(fmap[it->first], it->second) );
+        }
+        map<int,double>::iterator ti = m.begin();
+        for ( ; ti != m.end(); ++ti ) {
+          o << " " << ti->first << ":" << ti->second;
+        }
+        o << endl;
+      }
+      o.close();
+    }
+
+    void
+    Update(SparseVector<double>& lambdas)
+    {
+      char tmp[] = DTRAIN_TMP_DIR"/dtrain-sofia-model-XXXXXX";
+      mkstemp(tmp);
+      tmp_model_fn = tmp;
+      string call = "./sofia-ml --training_file " + tmp_data_fn;
+      call += " --model_out " + tmp_model_fn;
+      call += " --loop_type stochastic --lambda 100 --dimensionality ";
+      std::stringstream out;
+      out << fmap.size();
+      call += out.str();
+      call += " &>/dev/null";
+      system ( call.c_str() );
+      ifstream i;
+      i.open( tmp_model_fn.c_str(), ios::in );
+      string model;
+      getline( i, model );
+      vector<string> strs;
+      boost::split( strs, model, boost::is_any_of(" ") );
+      int j = 0;
+      for ( vector<string>::iterator it = strs.begin(); it != strs.end(); ++it ) {
+        lambdas.set_value(fmap1[j], atof( it->c_str() ) );
+        j++;
+      }
+      i.close();
+      unlink( tmp_data_fn.c_str() );
+      unlink( tmp_model_fn.c_str() );
+    }
+
+  private:
+    string tmp_data_fn;
+    string tmp_model_fn;
+    map<int,int> fmap;
+    map<int,int> fmap1;
+};
+
+
+} // namespace
+
+#endif
+