oracle bleu refactor

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@259 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 47 insertions, 120 deletions

diff --git a/decoder/cdec.cc b/decoder/cdec.cc
index c15408b5..bec342ef 100644
--- a/decoder/cdec.cc
+++ b/decoder/cdec.cc
@@ -7,6 +7,7 @@
 #include <boost/program_options.hpp>
 #include <boost/program_options/variables_map.hpp>
 
+#include "oracle_bleu.h"
 #include "timing_stats.h"
 #include "translator.h"
 #include "phrasebased_translator.h"
@@ -146,11 +147,11 @@ void InitCommandLine(int argc, char** argv, po::variables_map* confp) {
         ("crf_uniform_empirical", "If there are multple references use (i.e., lattice) a uniform distribution rather than posterior weighting a la EM")
     ("get_oracle_forest,o", "Calculate rescored hypregraph using approximate BLEU scoring of rules")
     ("feature_expectations","Write feature expectations for all features in chart (**OBJ** will be the partition)")
-    ("references,R", po::value<vector<string> >(), "Translation reference files")    
         ("vector_format",po::value<string>()->default_value("b64"), "Sparse vector serialization format for feature expectations or gradients, includes (text or b64)")
         ("combine_size,C",po::value<int>()->default_value(1), "When option -G is used, process this many sentence pairs before writing the gradient (1=emit after every sentence pair)")
         ("forest_output,O",po::value<string>(),"Directory to write forests to")
         ("minimal_forests,m","Write minimal forests (excludes Rule information). Such forests can be used for ML/MAP training, but not rescoring, etc.");
+  OracleBleu::AddOptions(&opts);
   po::options_description clo("Command line options");
   clo.add_options()
         ("config,c", po::value<string>(), "Configuration file")
@@ -260,14 +261,14 @@ void MaxTranslationSample(Hypergraph* hg, const int samples, const int k) {
   }
 }
 
-// TODO decoder output should probably be moved to another file
-void DumpKBest(const int sent_id, const Hypergraph& forest, const int k, const bool unique, const char *kbest_out_filename_, float doc_src_length, float tmp_src_length, const DocScorer &ds, Score* doc_score) {
+// TODO decoder output should probably be moved to another file - how about oracle_bleu.h
+void DumpKBest(const int sent_id, const Hypergraph& forest, const int k, const bool unique, std::string const&kbest_out_filename_, float doc_src_length, float tmp_src_length, const DocScorer &ds, shared_ptr<Score> doc_score) {
 cerr << "In kbest\n";
 
  ofstream kbest_out;
- kbest_out.open(kbest_out_filename_);
+ kbest_out.open(kbest_out_filename_.c_str());
  cerr << "Output kbest to " << kbest_out_filename_;
- 
+
  //add length (f side) src length of this sentence to the psuedo-doc src length count
  float curr_src_length = doc_src_length + tmp_src_length;
 
@@ -298,6 +299,15 @@ cerr << "In kbest\n";
   }
 }
 
+void DumpKBest(po::variables_map const& conf,string const& suffix,const int sent_id, const Hypergraph& forest, const int k, const bool unique, float doc_src_length, float tmp_src_length, const DocScorer &ds, shared_ptr<Score> doc_score)
+{
+  ostringstream kbest_string_stream;
+  kbest_string_stream << conf["forest_output"].as<string>() << "/kbest_"<<suffix<< "." << sent_id;
+  DumpKBest(sent_id, forest, k, unique, kbest_string_stream.str(), doc_src_length, tmp_src_length, ds, doc_score);
+
+}
+
+
 struct ELengthWeightFunction {
   double operator()(const Hypergraph::Edge& e) const {
     return e.rule_->ELength() - e.rule_->Arity();
@@ -517,45 +527,9 @@ int main(int argc, char** argv) {
   const bool crf_uniform_empirical = conf.count("crf_uniform_empirical");
   const bool get_oracle_forest = conf.count("get_oracle_forest");
 
-  /*Oracle Extraction Prep*/
-  vector<const FeatureFunction*> oracle_model_ffs;
-  vector<double> oracle_feature_weights;
-  shared_ptr<FeatureFunction> oracle_pff;
-  if(get_oracle_forest)      {
-    
-    /*Add feature for oracle rescoring */
-    string ff, param;
-    ff="BLEUModel";
-    //pass the location of the references file via param to BLEUModel
-    for(int kk=0;kk < conf["references"].as<vector<string> >().size();kk++)
-      {
-	param =  param + " " + conf["references"].as<vector<string> >()[kk];
-      }       
-    cerr << "Feature: " << ff << "->" << param << endl;
-    oracle_pff = global_ff_registry->Create(ff,param);
-    if (!oracle_pff) { exit(1); }
-    oracle_model_ffs.push_back(oracle_pff.get());	
-    oracle_feature_weights.push_back(1.0);
-
-  }
-
-  ModelSet oracle_models(oracle_feature_weights, oracle_model_ffs); 
-
-  const string loss_function3 = "IBM_BLEU_3";
-  ScoreType type3 = ScoreTypeFromString(loss_function3);
-  const DocScorer ds(type3, conf["references"].as<vector<string> >(), "");
-  cerr << "Loaded " << ds.size() << " references for scoring with " << loss_function3 << endl;
-  
-    
-  std::ostringstream kbest_string_stream;
-  Score* doc_score=NULL;
-  float doc_src_length=0;
-  float tmp_src_length=0; 
-  int oracle_doc_size= 10;   //used for scaling/weighting oracle doc
-  float scale_oracle=  1-float(1)/oracle_doc_size;
-
-  /*End Oracle Extraction Prep*/
-
+  OracleBleu oracle;
+  if (get_oracle_forest)
+    oracle.UseConf(conf);
 
   shared_ptr<WriteFile> extract_file;
   if (conf.count("extract_rules"))
@@ -671,83 +645,37 @@ int main(int argc, char** argv) {
 
     vector<WordID> trans;
     ViterbiESentence(forest, &trans);
-    
+
     /*Oracle Rescoring*/
-    if(get_oracle_forest)
+    if(get_oracle_forest) {
+      Timer t("Forest Oracle rescoring:");
+
+      DumpKBest(conf,"model",sent_id, forest, 10, true, oracle.doc_src_length, oracle.tmp_src_length, oracle.ds, oracle.doc_score);
+
+      Translation best(forest);
       {
-	Timer t("Forest Oracle rescoring:");
-	vector<WordID> model_trans;
-	model_trans = trans;
-
-	trans=model_trans;
-	Score* sentscore = ds[sent_id]->ScoreCandidate(model_trans);
-	//initilize psuedo-doc vector to 1 counts
-	if (!doc_score) { doc_score = sentscore->GetOne(); }
-	double bleu_scale_ = doc_src_length * doc_score->ComputeScore();
-	tmp_src_length = smeta.GetSourceLength();
-	smeta.SetScore(doc_score);
-	smeta.SetDocLen(doc_src_length);
-	smeta.SetDocScorer(&ds); 
-	
-	feature_weights[0]=1.0;	
-
-	kbest_string_stream << conf["forest_output"].as<string>() << "/kbest_model" << "." << sent_id;
-	DumpKBest(sent_id, forest, 10, true, kbest_string_stream.str().c_str(), doc_src_length, tmp_src_length, ds, doc_score);
-	kbest_string_stream.str("");
-
-
-	forest.SortInEdgesByEdgeWeights();
-	Hypergraph lm_forest;
-	const IntersectionConfiguration inter_conf_oracle(0, 0);
-	cerr << "Going to call Apply Model " << endl;
-	ApplyModelSet(forest,
-		      smeta,
-		      oracle_models,
-		      inter_conf_oracle,
-		      &lm_forest);
-	
-	forest.swap(lm_forest);
-	forest.Reweight(feature_weights);
-	forest.SortInEdgesByEdgeWeights();
-	vector<WordID> oracle_trans;
-
-	ViterbiESentence(forest, &oracle_trans);
-	cerr << "  +Oracle BLEU forest (nodes/edges): " << forest.nodes_.size() << '/' << forest.edges_.size() << endl;
-	cerr << "  +Oracle BLEU (paths): " << forest.NumberOfPaths() << endl;
-	cerr << "  +Oracle BLEU Viterbi: " << TD::GetString(oracle_trans) << endl;  
-      
-	//compute kbest for oracle
-	kbest_string_stream << conf["forest_output"].as<string>() <<"/kbest_oracle" << "." << sent_id;
-	DumpKBest(sent_id, forest, 10, true, kbest_string_stream.str().c_str(), doc_src_length, tmp_src_length, ds, doc_score);
-	kbest_string_stream.str("");
-	
-	
-	//reweight the model with -1 for the BLEU feature to compute k-best list for negative examples
-	feature_weights[0]=-1.0;
-	forest.Reweight(feature_weights);
-	forest.SortInEdgesByEdgeWeights();
-	vector<WordID> neg_trans;
-	ViterbiESentence(forest, &neg_trans);
-	cerr << "  -Oracle BLEU forest (nodes/edges): " << forest.nodes_.size() << '/' << forest.edges_.size() << endl;
-	cerr << "  -Oracle BLEU (paths): " << forest.NumberOfPaths() << endl;
-	cerr << "  -Oracle BLEU Viterbi: " << TD::GetString(neg_trans) << endl;  
-	
-	//compute kbest for negative
-	kbest_string_stream << conf["forest_output"].as<string>() << "/kbest_negative" << "." << sent_id;
-	DumpKBest(sent_id, forest, 10, true, kbest_string_stream.str().c_str(), doc_src_length, tmp_src_length,ds,  doc_score);
-	kbest_string_stream.str("");
-		
-	//Add 1-best translation (trans) to psuedo-doc vectors
-	doc_score->PlusEquals(*sentscore, scale_oracle);
-	delete sentscore;
-	
-	doc_src_length = (doc_src_length + tmp_src_length) * scale_oracle;
-	
-	
-	string details;
-	doc_score->ScoreDetails(&details);
-	cerr << "SCALED SCORE: " << bleu_scale_ << "DOC BLEU " << doc_score->ComputeScore() << " " <<details << endl;
+        Hypergraph oracle_forest;
+        oracle.Rescore(smeta,forest,&oracle_forest,feature_weights,1.0);
+        forest.swap(oracle_forest);
       }
+      Translation oracle_trans(forest);
+
+      cerr << "  +Oracle BLEU forest (nodes/edges): " << forest.nodes_.size() << '/' << forest.edges_.size() << endl;
+      cerr << "  +Oracle BLEU (paths): " << forest.NumberOfPaths() << endl;
+      oracle_trans.Print(cerr,"  +Oracle BLEU");
+      //compute kbest for oracle
+      DumpKBest(conf,"oracle",sent_id, forest, 10, true, oracle.doc_src_length, oracle.tmp_src_length, oracle.ds, oracle.doc_score);
+
+      //reweight the model with -1 for the BLEU feature to compute k-best list for negative examples
+      oracle.ReweightBleu(&forest,-1.0);
+      Translation neg_trans(forest);
+      neg_trans.Print(cerr,"  -Oracle BLEU");
+      //compute kbest for negative
+      DumpKBest(conf,"negative",sent_id, forest, 10, true, oracle.doc_src_length, oracle.tmp_src_length,oracle.ds,oracle.doc_score);
+
+      //Add 1-best translation (trans) to psuedo-doc vectors
+      oracle.IncludeLastScore(&cerr);
+    }
 
 
     if (conf.count("forest_output") && !has_ref) {
@@ -772,9 +700,8 @@ int main(int argc, char** argv) {
     if (sample_max_trans) {
       MaxTranslationSample(&forest, sample_max_trans, conf.count("k_best") ? conf["k_best"].as<int>() : 0);
     } else {
-      
       if (kbest) {
-        DumpKBest(sent_id, forest, conf["k_best"].as<int>(), unique_kbest,"", doc_src_length, tmp_src_length, ds,  doc_score);
+        DumpKBest(sent_id, forest, conf["k_best"].as<int>(), unique_kbest,"", oracle.doc_src_length,oracle.tmp_src_length, oracle.ds,oracle.doc_score);
       } else if (csplit_output_plf) {
         cout << HypergraphIO::AsPLF(forest, false) << endl;
       } else {