added iteration selection param

1 files changed, 55 insertions, 27 deletions

diff --git a/dtrain/dtrain.cc b/dtrain/dtrain.cc
index 9b1bbe68..69f83633 100644
--- a/dtrain/dtrain.cc
+++ b/dtrain/dtrain.cc
@@ -23,6 +23,7 @@ dtrain_init(int argc, char** argv, po::variables_map* cfg)
     ("learning_rate",  po::value<double>()->default_value(0.0005),                      "learning rate")
     ("gamma",          po::value<double>()->default_value(0.),       "gamma for SVM (0 for perceptron)")
     ("tmp",            po::value<string>()->default_value("/tmp"),                    "temp dir to use")
+    ("select_weights", po::value<string>()->default_value("last"),    "output 'best' or 'last' weights")
     ("noup",           po::value<bool>()->zero_tokens(),                        "do not update weights");
   po::options_description cl("Command Line Options");
   cl.add_options()
@@ -56,6 +57,10 @@ dtrain_init(int argc, char** argv, po::variables_map* cfg)
        && (*cfg)["sample_from"].as<string>() != "forest") {
     cerr << "Wrong 'sample_from' param: '" << (*cfg)["sample_from"].as<string>() << "', use 'kbest' or 'forest'." << endl;
   }
+  if ((*cfg)["select_weights"].as<string>() != "last"
+       && (*cfg)["select_weights"].as<string>() != "best") {
+    cerr << "Wrong 'select_weights' param: '" << (*cfg)["select_weights"].as<string>() << "', use 'last' or 'best'." << endl;
+  }
   return true;
 }
 
@@ -83,6 +88,7 @@ main(int argc, char** argv)
   const string filter_type = cfg["filter"].as<string>();
   const string sample_from = cfg["sample_from"].as<string>();
   const string pair_sampling = cfg["pair_sampling"].as<string>();
+  const string select_weights = cfg["select_weights"].as<string>();
   vector<string> print_weights;
   if (cfg.count("print_weights"))
     boost::split(print_weights, cfg["print_weights"].as<string>(), boost::is_any_of(" "));
@@ -140,13 +146,11 @@ main(int argc, char** argv)
     // buffer input for t > 0
   vector<string> src_str_buf;          // source strings
   vector<vector<WordID> > ref_ids_buf; // references as WordID vecs
-  // this is for writing the grammar buffer file
-  char grammar_buf_fn[1024];
-  strcpy(grammar_buf_fn, cfg["tmp"].as<string>().c_str());
-  strcat(grammar_buf_fn, "/dtrain-grammars-XXXXXX");
-  mkstemp(grammar_buf_fn);
+  vector<string> weights_files;        // remember weights for each iteration
+  string tmp_path = cfg["tmp"].as<string>();
+  string grammar_buf_fn = gettmpf(tmp_path, "dtrain-grammars");
   ogzstream grammar_buf_out;
-  grammar_buf_out.open(grammar_buf_fn);
+  grammar_buf_out.open(grammar_buf_fn.c_str());
   
   unsigned in_sz = 999999999; // input index, input size
   vector<pair<score_t,score_t> > all_scores;
@@ -173,6 +177,7 @@ main(int argc, char** argv)
     cerr << setw(25) << "gamma " << gamma << endl;
     cerr << setw(25) << "sample from " << "'" << sample_from << "'" << endl;
     cerr << setw(25) << "pairs " << "'" << pair_sampling << "'" << endl;
+    cerr << setw(25) << "select weights " << "'" << select_weights << "'" << endl;
     if (!verbose) cerr << "(a dot represents " << DTRAIN_DOTS << " lines of input)" << endl;
   }
 
@@ -183,7 +188,7 @@ main(int argc, char** argv)
   time_t start, end;  
   time(&start);
   igzstream grammar_buf_in;
-  if (t > 0) grammar_buf_in.open(grammar_buf_fn);
+  if (t > 0) grammar_buf_in.open(grammar_buf_fn.c_str());
   score_t score_sum = 0., model_sum = 0.;
   unsigned ii = 0;
   if (!quiet) cerr << "Iteration #" << t+1 << " of " << T << "." << endl;
@@ -221,7 +226,7 @@ main(int argc, char** argv)
         }
       }
     }
-    
+   
     // next iteration
     if (next || stop) break;
 
@@ -244,8 +249,8 @@ main(int argc, char** argv)
       ref_ids_buf.push_back(ref_ids);
       // process and set grammar
       bool broken_grammar = true;
-      for (string::iterator ti = in_split[3].begin(); ti != in_split[3].end(); ti++) {
-        if (!isspace(*ti)) {
+      for (string::iterator it = in_split[3].begin(); it != in_split[3].end(); it++) {
+        if (!isspace(*it)) {
           broken_grammar = false;
           break;
         }
@@ -300,14 +305,14 @@ main(int argc, char** argv)
       if (pair_sampling == "108010")
         sample108010(samples, pairs);
        
-      for (vector<pair<ScoredHyp,ScoredHyp> >::iterator ti = pairs.begin();
-            ti != pairs.end(); ti++) {
+      for (vector<pair<ScoredHyp,ScoredHyp> >::iterator it = pairs.begin();
+           it != pairs.end(); it++) {
 
         SparseVector<double> dv;
-        if (ti->first.score - ti->second.score < 0) {
-          dv = ti->second.f - ti->first.f;
+        if (it->first.score - it->second.score < 0) {
+          dv = it->second.f - it->first.f;
       //} else {
-        //dv = ti->first - ti->second;
+        //dv = it->first - it->second;
       //}
           dv.add_value(FD::Convert("__bias"), -1);
         
@@ -317,7 +322,7 @@ main(int argc, char** argv)
           lambdas += dv * eta;
 
           if (verbose) {
-            /*cerr << "{{ f("<< ti->first_rank <<") > f(" << ti->second_rank << ") but g(i)="<< ti->first_score <<" < g(j)="<< ti->second_score << " so update" << endl;
+            /*cerr << "{{ f("<< it->first_rank <<") > f(" << it->second_rank << ") but g(i)="<< it->first_score <<" < g(j)="<< it->second_score << " so update" << endl;
             cerr << " i  " << TD::GetString(samples->sents[ti->first_rank]) << endl;
             cerr << "    " << samples->feats[ti->first_rank] << endl;
             cerr << " j  " << TD::GetString(samples->sents[ti->second_rank]) << endl;
@@ -393,23 +398,46 @@ main(int argc, char** argv)
 
   if (noup) break;
 
+  // write weights to file
+  if (select_weights == "best") {
+    weights.InitFromVector(lambdas);
+    string infix = "dtrain-weights-" + boost::lexical_cast<string>(t);
+    string w_fn = gettmpf(tmp_path, infix, "gz");
+    weights.WriteToFile(w_fn, true); 
+    weights_files.push_back(w_fn);
+  }
+
   } // outer loop
 
-  unlink(grammar_buf_fn);
+  unlink(grammar_buf_fn.c_str());
 
   if (!noup) {
-    if (!quiet) cerr << endl << "writing weights file '" << cfg["output"].as<string>() << "' ...";
-    if (cfg["output"].as<string>() == "-") {
-      cout << _p9;
-      for (SparseVector<double>::const_iterator ti = lambdas.begin();
-            ti != lambdas.end(); ++ti) {
-	if (ti->second == 0) continue;
-        cout << _np << FD::Convert(ti->first) << "\t" << ti->second << endl;
+    if (!quiet) cerr << endl << "writing weights file to '" << cfg["output"].as<string>() << "' ...";
+    if (select_weights == "last") { // last
+      WriteFile out(cfg["output"].as<string>());
+      ostream& o = *out.stream();
+      o.precision(17);
+      o << _np;
+      for (SparseVector<double>::const_iterator it = lambdas.begin(); it != lambdas.end(); ++it) {
+	    if (it->second == 0) continue;
+        o << FD::Convert(it->first) << '\t' << it->second << endl;
       }
       if (hstreaming) cout << "__SHARD_COUNT__\t1" << endl;
-    } else if (cfg["output"].as<string>() != "VOID") {
-      weights.InitFromVector(lambdas);
-      weights.WriteToFile(cfg["output"].as<string>(), true);
+    } else { // best
+      if (cfg["output"].as<string>() != "-") {
+        CopyFile(weights_files[best_it], cfg["output"].as<string>()); 
+      } else {
+        ReadFile(weights_files[best_it]);
+        string o;
+        cout.precision(17);
+        cout << _np;
+        while(getline(*input, o)) cout << o << endl; 
+      }
+      for (vector<string>::iterator it = weights_files.begin(); it != weights_files.end(); ++it) {
+        unlink(it->c_str());
+        it->erase(it->end()-3, it->end());
+        unlink(it->c_str());
+      }
     }
     if (!quiet) cerr << "done" << endl;
   }