Updated incremental, updated kenlm. Incremental assumes <s>

1 files changed, 22 insertions, 22 deletions

diff --git a/decoder/incremental.cc b/decoder/incremental.cc
index 46615b0b..85647a44 100644
--- a/decoder/incremental.cc
+++ b/decoder/incremental.cc
@@ -6,6 +6,7 @@
 
 #include "lm/enumerate_vocab.hh"
 #include "lm/model.hh"
+#include "search/applied.hh"
 #include "search/config.hh"
 #include "search/context.hh"
 #include "search/edge.hh"
@@ -48,16 +49,16 @@ template <class Model> class Incremental : public IncrementalBase {
     Incremental(const char *model_file, const std::vector<weight_t> &weights) :
       IncrementalBase(weights), 
       m_(model_file, GetConfig()),
-      weights_(
-          weights[FD::Convert("KLanguageModel")],
-          weights[FD::Convert("KLanguageModel_OOV")],
-          weights[FD::Convert("WordPenalty")]) {
-      std::cerr << "Weights KLanguageModel " << weights_.LM() << " KLanguageModel_OOV " << weights_.OOV() << " WordPenalty " << weights_.WordPenalty() << std::endl;
+      lm_(weights[FD::Convert("KLanguageModel")]),
+      oov_(weights[FD::Convert("KLanguageModel_OOV")]),
+      word_penalty_(weights[FD::Convert("WordPenalty")]) {
+      std::cerr << "Weights KLanguageModel " << lm_ << " KLanguageModel_OOV " << oov_ << " WordPenalty " << word_penalty_ << std::endl;
     }
+
     void Search(unsigned int pop_limit, const Hypergraph &hg) const;
 
   private:
-    void ConvertEdge(const search::Context<Model> &context, bool final, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const;
+    void ConvertEdge(const search::Context<Model> &context, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const;
 
     lm::ngram::Config GetConfig() {
       lm::ngram::Config ret;
@@ -69,46 +70,47 @@ template <class Model> class Incremental : public IncrementalBase {
 
     const Model m_;
 
-    const search::Weights weights_;
+    const float lm_, oov_, word_penalty_;
 };
 
-void PrintFinal(const Hypergraph &hg, const search::Final final) {
+void PrintApplied(const Hypergraph &hg, const search::Applied final) {
   const std::vector<WordID> &words = static_cast<const Hypergraph::Edge*>(final.GetNote().vp)->rule_->e();
-  const search::Final *child(final.Children());
+  const search::Applied *child(final.Children());
   for (std::vector<WordID>::const_iterator i = words.begin(); i != words.end(); ++i) {
     if (*i > 0) {
       std::cout << TD::Convert(*i) << ' ';
     } else {
-      PrintFinal(hg, *child++);
+      PrintApplied(hg, *child++);
     }
   }
 }
 
 template <class Model> void Incremental<Model>::Search(unsigned int pop_limit, const Hypergraph &hg) const {
   boost::scoped_array<search::Vertex> out_vertices(new search::Vertex[hg.nodes_.size()]);
-  search::Config config(weights_, pop_limit);
+  search::Config config(lm_, pop_limit, search::NBestConfig(1));
   search::Context<Model> context(config, m_);
+  search::SingleBest best;
 
   for (unsigned int i = 0; i < hg.nodes_.size() - 1; ++i) {
     search::EdgeGenerator gen;
     const Hypergraph::EdgesVector &down_edges = hg.nodes_[i].in_edges_;
     for (unsigned int j = 0; j < down_edges.size(); ++j) {
       unsigned int edge_index = down_edges[j];
-      ConvertEdge(context, i == hg.nodes_.size() - 2, out_vertices.get(), hg.edges_[edge_index], gen);
+      ConvertEdge(context, out_vertices.get(), hg.edges_[edge_index], gen);
     }
-    search::VertexGenerator vertex_gen(context, out_vertices[i]);
+    search::VertexGenerator<search::SingleBest> vertex_gen(context, out_vertices[i], best);
     gen.Search(context, vertex_gen);
   }
-  const search::Final top = out_vertices[hg.nodes_.size() - 2].BestChild();
+  const search::Applied top = out_vertices[hg.nodes_.size() - 2].BestChild();
   if (!top.Valid()) {
     std::cout << "NO PATH FOUND" << std::endl;
   } else {
-    PrintFinal(hg, top);
+    PrintApplied(hg, top);
     std::cout << "||| " << top.GetScore() << std::endl;
   }
 }
 
-template <class Model> void Incremental<Model>::ConvertEdge(const search::Context<Model> &context, bool final, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const {
+template <class Model> void Incremental<Model>::ConvertEdge(const search::Context<Model> &context, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const {
   const std::vector<WordID> &e = in.rule_->e();
   std::vector<lm::WordIndex> words;
   words.reserve(e.size());
@@ -127,10 +129,6 @@ template <class Model> void Incremental<Model>::ConvertEdge(const search::Contex
     }
   }
 
-  if (final) {
-    words.push_back(m_.GetVocabulary().EndSentence());
-  }
-
   search::PartialEdge out(gen.AllocateEdge(nts.size()));
 
   memcpy(out.NT(), &nts[0], sizeof(search::PartialVertex) * nts.size());
@@ -140,8 +138,10 @@ template <class Model> void Incremental<Model>::ConvertEdge(const search::Contex
   out.SetNote(note);
 
   score += in.rule_->GetFeatureValues().dot(cdec_weights_);
-  score -= static_cast<float>(terminals) * context.GetWeights().WordPenalty() / M_LN10;
-  score += search::ScoreRule(context, words, final, out.Between());
+  score -= static_cast<float>(terminals) * word_penalty_ / M_LN10;
+  search::ScoreRuleRet res(search::ScoreRule(context.LanguageModel(), words, out.Between()));
+  score += res.prob * lm_ + static_cast<float>(res.oov) * oov_;
+
   out.SetScore(score);
 
   gen.AddEdge(out);