From d7d59c4bb81262f1dfece384ec68fa2c25096843 Mon Sep 17 00:00:00 2001
From: graehl <graehl@ec762483-ff6d-05da-a07a-a48fb63a330f>
Date: Fri, 16 Jul 2010 01:56:34 +0000
Subject: oracle directions

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@276 ec762483-ff6d-05da-a07a-a48fb63a330f
---
 decoder/oracle_bleu.h | 79 +++++++++++++++++++++++++++++++++++++++++++--------
 1 file changed, 67 insertions(+), 12 deletions(-)

(limited to 'decoder/oracle_bleu.h')

diff --git a/decoder/oracle_bleu.h b/decoder/oracle_bleu.h
index 5fef53fd..550f438f 100755
--- a/decoder/oracle_bleu.h
+++ b/decoder/oracle_bleu.h
@@ -37,7 +37,31 @@ struct Translation {
     out<<pre<<"Viterbi: "<<TD::GetString(sentence)<<"\n";
     out<<pre<<"features: "<<features<<std::endl;
   }
+  bool is_null() {
+    return features.size()==0 /* && sentence.size()==0 */;
+  }
+
+};
+
+struct Oracles {
+  bool is_null() {
+    return model.is_null() /* && fear.is_null() && hope.is_null() */;
+  }
 
+  Translation model,fear,hope;
+  // feature 0 will be the error rate in fear and hope
+  // move toward hope
+  WeightVector ModelHopeGradient() {
+    WeightVector r=hope-model;
+    r[0]=0;
+    return r;
+  }
+  // move toward hope from fear
+  WeightVector FearHopeGradient() {
+    Weightvector r=hope-fear;
+    r[0]=0;
+    return r;
+  }
 };
 
 
@@ -53,6 +77,7 @@ struct OracleBleu {
     opts->add_options()
       ("references,R", value<Refs >(), "Translation reference files")
       ("oracle_loss", value<string>(), "IBM_BLEU_3 (default), IBM_BLEU etc")
+      ("bleu_weight", value<double>()->default_value(1.), "weight to give the hope/fear loss function vs. model score")
       ;
   }
   int order;
@@ -66,17 +91,20 @@ struct OracleBleu {
   double doc_src_length;
   void set_oracle_doc_size(int size) {
     oracle_doc_size=size;
-    scale_oracle=  1-1./oracle_doc_size;\
+    scale_oracle=  1-1./oracle_doc_size;
     doc_src_length=0;
   }
   OracleBleu(int doc_size=10) {
     set_oracle_doc_size(doc_size);
   }
 
-  boost::shared_ptr<Score> doc_score,sentscore; // made from factory, so we delete them
+  typedef boost::shared_ptr<Score> ScoreP;
+  ScoreP doc_score,sentscore; // made from factory, so we delete them
 
+  double bleu_weight;
   void UseConf(boost::program_options::variables_map const& conf) {
     using namespace std;
+    bleu_weight=conf["bleu_weight"].as<double>();
     set_loss(conf["oracle_loss"].as<string>());
     set_refs(conf["references"].as<Refs>());
   }
@@ -108,21 +136,48 @@ struct OracleBleu {
     ViterbiFSentence(forest,&srcsent);
     SentenceMetadata sm(sent_id,Lattice()); //TODO: make reference from refs?
     sm.SetSourceLength(srcsent.size());
+	smeta.SetScore(doc_score.get());
+	smeta.SetDocScorer(&ds);
+	smeta.SetDocLen(doc_src_length);
     return sm;
   }
 
-  void Rescore(SentenceMetadata & smeta,Hypergraph const& forest,Hypergraph *dest_forest,WeightVector const& feature_weights,double bleu_weight=1.0) {
-    Translation model_trans(forest);
-    sentscore.reset(ds[smeta.GetSentenceID()]->ScoreCandidate(model_trans.sentence));
+  Oracles ComputeOracles(SentenceMetadata & smeta,Hypergraph const& forest,WeightVector const& feature_weights,std::ostream *log=0,unsigned kbest=0,std::string const& forest_output="") {
+    Oracles r;
+    int sent_id=smeta.GetSentenceID();
+    r.model=Translation(forest);
+
+    if (kbest) DumpKBest("model",sent_id, forest, kbest, true, forest_output);
+    {
+      Timer t("Forest Oracle rescoring:");
+      Hypergraph oracle_forest;
+      Rescore(smeta,forest,&oracle_forest,feature_weights,blue_weight,log);
+      forest.swap(oracle_forest);
+    }
+    r.hope=Translation(forest);
+    if (kbest) DumpKBest("oracle",sent_id, forest, kbest, true, forest_output);
+    oracle.ReweightBleu(&forest,-blue_weight);
+    r.fear=Translation(forest);
+    if (kbest) DumpKBest("negative",sent_id, forest, kbest, true, forest_output);
+    return r;
+  }
+
+  ScoreP Score(Sentence const& sentence,int sent_id) {
+    return ds[sent_id]->ScoreCandidate(sentence);
+  }
+  ScoreP Score(Hypergraph const& forest,int sent_id) {
+    return Score(model_trans(forest).translation,sent_id);
+  }
+
+  void Rescore(SentenceMetadata & smeta,Hypergraph const& forest,Hypergraph *dest_forest,WeightVector const& feature_weights,double bleu_weight=1.0,std::ostream *log=&std::cerr) {
+    // the sentence bleu stats will get added to doc only if you call IncludeLastScore
+    sentscore=Score(forest,smeta.GetSentenceID());
 	if (!doc_score) { doc_score.reset(sentscore->GetOne()); }
 	tmp_src_length = smeta.GetSourceLength(); //TODO: where does this come from?
-	smeta.SetScore(doc_score.get());
-	smeta.SetDocLen(doc_src_length);
-	smeta.SetDocScorer(&ds);
     using namespace std;
-    ModelSet oracle_models(FeatureWeights(bleu_weight,1),vector<FeatureFunction const*>(1,pff.get()));
+    ModelSet oracle_models(WeightVector(bleu_weight,1),vector<FeatureFunction const*>(1,pff.get()));
     const IntersectionConfiguration inter_conf_oracle(0, 0);
-	cerr << "Going to call Apply Model " << endl;
+	if (log) *log << "Going to call Apply Model " << endl;
 	ApplyModelSet(forest,
                   smeta,
                   oracle_models,
@@ -190,10 +245,10 @@ struct OracleBleu {
     }
   }
 
-  void DumpKBest(boost::program_options::variables_map const& conf,std::string const& suffix,const int sent_id, const Hypergraph& forest, const int k, const bool unique)
+void DumpKBest(boost::program_options::variables_map const& conf,std::string const& suffix,const int sent_id, const Hypergraph& forest, const int k, const bool unique, std::string const& forest_output)
   {
     std::ostringstream kbest_string_stream;
-    kbest_string_stream << conf["forest_output"].as<std::string>() << "/kbest_"<<suffix<< "." << sent_id;
+    kbest_string_stream << forest_output << "/kbest_"<<suffix<< "." << sent_id;
     DumpKBest(sent_id, forest, k, unique, kbest_string_stream.str());
   }
 
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