1 files changed, 32 insertions, 45 deletions

diff --git a/dtrain/dtrain.cc b/dtrain/dtrain.cc
index 35e6cc46..622cd01e 100644
--- a/dtrain/dtrain.cc
+++ b/dtrain/dtrain.cc
@@ -95,38 +95,32 @@ main(int argc, char** argv)
     cerr << setw(25) << "cdec cfg " << "'" << cfg["decoder_config"].as<string>() << "'" << endl;
   Decoder decoder(ini_rf.stream());
 
-  MT19937 rng; // random number generator
-  // setup decoder observer
-  HypSampler* observer;
-  if (sample_from == "kbest") {
-    observer = dynamic_cast<KBestGetter*>(new KBestGetter(k, filter_type));
-  } else {
-    observer = dynamic_cast<KSampler*>(new KSampler(k, &rng));
-  }
-
   // scoring metric/scorer
   string scorer_str = cfg["scorer"].as<string>();
-  /*score_t (*scorer)(NgramCounts&, const unsigned, const unsigned, unsigned, vector<score_t>);
+  LocalScorer* scorer;
   if (scorer_str == "bleu") {
-    scorer = &bleu;
   } else if (scorer_str == "stupid_bleu") {
-    scorer = &stupid_bleu;
+    scorer = dynamic_cast<StupidBleuScorer*>(new StupidBleuScorer);
   } else if (scorer_str == "smooth_bleu") {
-    scorer = &smooth_bleu;
+      scorer = dynamic_cast<SmoothBleuScorer*>(new SmoothBleuScorer);
   } else if (scorer_str == "approx_bleu") {
-    scorer = &approx_bleu;
+      scorer = dynamic_cast<StupidBleuScorer*>(new StupidBleuScorer); // FIXME
   } else {
     cerr << "Don't know scoring metric: '" << scorer_str << "', exiting." << endl;
     exit(1);
   }
-  NgramCounts global_counts(N); // counts for 1 best translations
-  unsigned global_hyp_len = 0;    // sum hypothesis lengths
-  unsigned global_ref_len = 0;    // sum reference lengths
-  // ^^^ global_* for approx_bleu*/
-  vector<score_t> bleu_weights;   // we leave this empty -> 1/N 
-  //if (!quiet) cerr << setw(26) << "scorer '" << scorer_str << "'" << endl << endl;
-  StupidBleuScorer scorer;
-  scorer.Init(N, bleu_weights);
+  vector<score_t> bleu_weights;
+  scorer->Init(N, bleu_weights);
+  if (!quiet) cerr << setw(26) << "scorer '" << scorer_str << "'" << endl << endl;
+
+  // setup decoder observer
+  MT19937 rng; // random number generator
+  HypSampler* observer;
+  if (sample_from == "kbest")
+    observer = dynamic_cast<KBestGetter*>(new KBestGetter(k, filter_type));
+  else
+    observer = dynamic_cast<KSampler*>(new KSampler(k, &rng));
+  observer->SetScorer(scorer);
 
   // init weights
   Weights weights;
@@ -240,10 +234,10 @@ main(int argc, char** argv)
     vector<WordID> ref_ids;  // reference as vector<WordID>
     if (t == 0) {
       // handling input
-      strsplit(in, in_split, '\t', 4);
+      boost::split(in_split, in, boost::is_any_of("\t"));
       // getting reference
       vector<string> ref_tok;
-      strsplit(in_split[2], ref_tok, ' ');
+      boost::split(ref_tok, in_split[2], boost::is_any_of(" "));
       register_and_convert(ref_tok, ref_ids);
       ref_ids_buf.push_back(ref_ids);
       // process and set grammar
@@ -259,8 +253,9 @@ main(int argc, char** argv)
       in_split[3] += "\n";
       grammar_buf_out << in_split[3] << DTRAIN_GRAMMAR_DELIM << " " << in_split[0] << endl;
       decoder.SetSentenceGrammarFromString(in_split[3]);
-      // decode
       src_str_buf.push_back(in_split[1]);
+      // decode
+      observer->SetRef(ref_ids);
       decoder.Decode(in_split[1], observer);
     } else {
       // get buffered grammar
@@ -273,32 +268,24 @@ main(int argc, char** argv)
       }
       decoder.SetSentenceGrammarFromString(grammar_str);
       // decode
+      observer->SetRef(ref_ids_buf[ii]);
       decoder.Decode(src_str_buf[ii], observer);
     }
 
+    // get (scored) samples 
     vector<ScoredHyp>* samples = observer->GetSamples();
 
-    // (local) scoring
-    if (t > 0) ref_ids = ref_ids_buf[ii];
-    for (unsigned i = 0; i < samples->size(); i++) {
-        //cout << ii << " " << i << endl;
-
-        cout << _p9;
-      (*samples)[i].score = scorer.Score((*samples)[i], ref_ids, ii);
-      if (i == 0) {
-        score_sum += (*samples)[i].score;
-        model_sum += (*samples)[i].model;
-      }
-
-      if (verbose) {
-        if (i == 0) cerr << "'" << TD::GetString(ref_ids) << "' [ref]" << endl;
-        cerr << _p5 << _np << "[hyp " << i << "] " << "'" << TD::GetString((*samples)[i].w) << "'";
-        cerr << " [SCORE=" << (*samples)[i].score << ",model="<< (*samples)[i].model << "]" << endl;
-        cerr << (*samples)[i].f << endl;
-      }
+    if (verbose) {
+      cout << "[ref: '";
+      if (t > 0) cout << ref_ids_buf[ii];
+      else cout << ref_ids;
+      cout << endl;
+      cout << _p5 << _np << "1best: " << "'" << (*samples)[0].w << "'" << endl;
+      cout << "SCORE=" << (*samples)[0].score << ",model="<< (*samples)[0].model << endl;
+      cout << "F{" << (*samples)[0].f << "} ]" << endl << endl;
     }
-
-    if (verbose) cerr << endl;
+    score_sum += (*samples)[0].score;
+    model_sum += (*samples)[0].model;
 
 //////////////////////////////////////////////////////////
     // UPDATE WEIGHTS