Update incremental search

1 files changed, 26 insertions, 26 deletions

diff --git a/search/rule.cc b/search/rule.cc
index 5b00207ef..0244a09f7 100644
--- a/search/rule.cc
+++ b/search/rule.cc
@@ -1,7 +1,7 @@
 #include "search/rule.hh"
 
+#include "lm/model.hh"
 #include "search/context.hh"
-#include "search/final.hh"
 
 #include <ostream>
 
@@ -9,35 +9,35 @@
 
 namespace search {
 
-template <class Model> float ScoreRule(const Context<Model> &context, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing) {
-  unsigned int oov_count = 0;
-  float prob = 0.0;
-  const Model &model = context.LanguageModel();
-  const lm::WordIndex oov = model.GetVocabulary().NotFound();
-  for (std::vector<lm::WordIndex>::const_iterator word = words.begin(); ; ++word) {
-    lm::ngram::RuleScore<Model> scorer(model, *(writing++));
-    // TODO: optimize
-    if (prepend_bos && (word == words.begin())) {
-      scorer.BeginSentence();
-    }
-    for (; ; ++word) {
-      if (word == words.end()) {
-        prob += scorer.Finish();
-        return static_cast<float>(oov_count) * context.GetWeights().OOV() + prob * context.GetWeights().LM();
-      }
-      if (*word == kNonTerminal) break;
-      if (*word == oov) ++oov_count;
+template <class Model> ScoreRuleRet ScoreRule(const Model &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing) {
+  ScoreRuleRet ret;
+  ret.prob = 0.0;
+  ret.oov = 0;
+  const lm::WordIndex oov = model.GetVocabulary().NotFound(), bos = model.GetVocabulary().BeginSentence();
+  lm::ngram::RuleScore<Model> scorer(model, *(writing++));
+  std::vector<lm::WordIndex>::const_iterator word = words.begin();
+  if (word != words.end() && *word == bos) {
+    scorer.BeginSentence();
+    ++word;
+  }
+  for (; word != words.end(); ++word) {
+    if (*word == kNonTerminal) {
+      ret.prob += scorer.Finish();
+      scorer.Reset(*(writing++));
+    } else {
+      if (*word == oov) ++ret.oov;
       scorer.Terminal(*word);
     }
-    prob += scorer.Finish();
   }
+  ret.prob += scorer.Finish();
+  return ret;
 }
 
-template float ScoreRule(const Context<lm::ngram::RestProbingModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::ProbingModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::TrieModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::QuantTrieModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::ArrayTrieModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::QuantArrayTrieModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::RestProbingModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::ProbingModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::TrieModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::QuantTrieModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::ArrayTrieModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::QuantArrayTrieModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
 
 } // namespace search