Remove reference counts now that we can use boost

git-svn-id: https://mosesdecoder.svn.sourceforge.net/svnroot/mosesdecoder/trunk@4380 1f5c12ca-751b-0410-a591-d2e778427230

2 files changed, 26 insertions, 91 deletions

diff --git a/moses/src/LM/Implementation.h b/moses/src/LM/Implementation.h
index e0551f759..1ea59b6b3 100644
--- a/moses/src/LM/Implementation.h
+++ b/moses/src/LM/Implementation.h
@@ -31,9 +31,7 @@ Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
 #include "Word.h"
 #include "LM/Base.h"
 
-#ifdef WITH_THREADS
 #include <boost/shared_ptr.hpp>
-#endif
 
 namespace Moses
 {
@@ -54,18 +52,8 @@ struct LMResult {
 //! Abstract base class which represent a language model on a contiguous phrase
 class LanguageModelImplementation
 {
-#ifndef WITH_THREADS
-protected:
-  /** constructor to be called by inherited class
-   */
-  LanguageModelImplementation() : m_referenceCount(0) {}
-
-private:
-  // ref counting handled by boost if we have threads
-  unsigned int m_referenceCount;
-#else
   // default constructor is ok
-#endif
+
   void ShiftOrPush(std::vector<const Word*> &contextFactor, const Word &word) const;
 
 protected:
@@ -136,35 +124,14 @@ public:
   //! overrideable funtions for IRST LM to cleanup. Maybe something to do with on demand/cache loading/unloading
   virtual void InitializeBeforeSentenceProcessing() {};
   virtual void CleanUpAfterSentenceProcessing() {};
-
-#ifndef WITH_THREADS
-  // ref counting handled by boost otherwise
-
-  unsigned int IncrementReferenceCount() {
-    return ++m_referenceCount;
-  }
-
-  unsigned int DecrementReferenceCount() {
-    return --m_referenceCount;
-  }
-#endif
 };
 
 class LMRefCount : public LanguageModel {
   public:
     LMRefCount(ScoreIndexManager &scoreIndexManager, LanguageModelImplementation *impl) : m_impl(impl) {
-#ifndef WITH_THREADS
-      impl->IncrementReferenceCount();
-#endif
       Init(scoreIndexManager);
     }
 
-    ~LMRefCount() {
-#ifndef WITH_THREADS
-      if (!m_impl->DecrementReferenceCount()) delete m_impl;
-#endif
-    }
-
     LanguageModel *Duplicate(ScoreIndexManager &scoreIndexManager) const {
       return new LMRefCount(scoreIndexManager, *this);
     }
@@ -203,17 +170,10 @@ class LMRefCount : public LanguageModel {
 
   private:
     LMRefCount(ScoreIndexManager &scoreIndexManager, const LMRefCount &copy_from) : m_impl(copy_from.m_impl) {
-#ifndef WITH_THREADS
-      m_impl->IncrementReferenceCount();
-#endif
       Init(scoreIndexManager);
     }
 
-#ifdef WITH_THREADS
     boost::shared_ptr<LanguageModelImplementation> m_impl;
-#else
-    LanguageModelImplementation *m_impl;
-#endif
 };
 
 }
diff --git a/moses/src/LM/Ken.cpp b/moses/src/LM/Ken.cpp
index 22b390c19..678cbfe83 100644
--- a/moses/src/LM/Ken.cpp
+++ b/moses/src/LM/Ken.cpp
@@ -40,9 +40,7 @@ Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
 #include "StaticData.h"
 #include "ChartHypothesis.h"
 
-#ifdef WITH_THREADS
-#include <boost/scoped_ptr.hpp>
-#endif
+#include <boost/shared_ptr.hpp>
 
 using namespace std;
 
@@ -66,15 +64,6 @@ template <class Model> class LanguageModelKen : public LanguageModel {
   public:
     LanguageModelKen(const std::string &file, ScoreIndexManager &manager, FactorType factorType, bool lazy);
 
-    ~LanguageModelKen() {
-#ifndef WITH_THREADS
-      if (!--*m_refcount) {
-        delete m_ngram;
-        delete m_refcount;
-      }
-#endif
-    }
-
     LanguageModel *Duplicate(ScoreIndexManager &scoreIndexManager) const;
 
     bool Useable(const Phrase &phrase) const {
@@ -122,12 +111,8 @@ template <class Model> class LanguageModelKen : public LanguageModel {
       }
     }
 
-#ifdef WITH_THREADS
     boost::shared_ptr<Model> m_ngram;
-#else
-    Model *m_ngram;
-    mutable unsigned int *m_refcount;
-#endif
+    
     std::vector<lm::WordIndex> m_lmIdLookup;
 
     FactorType m_factorType;
@@ -166,18 +151,7 @@ template <class Model> LanguageModelKen<Model>::LanguageModelKen(const std::stri
   config.enumerate_vocab = &builder;
   config.load_method = lazy ? util::LAZY : util::POPULATE_OR_READ;
 
-  try {
-#ifdef WITH_THREADS
-    m_ngram.reset(new Model(file.c_str(), config));
-#else
-    m_ngram = new Model(file.c_str(), config);
-    m_refcount = new unsigned int();
-    *m_refcount = 1;
-#endif
-  } catch (std::exception &e) {
-    std::cerr << e.what() << std::endl;
-    abort();
-  }
+  m_ngram.reset(new Model(file.c_str(), config));
 
   m_beginSentenceFactor = collection.AddFactor(BOS_);
   Init(manager);
@@ -193,10 +167,6 @@ template <class Model> LanguageModelKen<Model>::LanguageModelKen(ScoreIndexManag
     m_lmIdLookup(copy_from.m_lmIdLookup),
     m_factorType(copy_from.m_factorType),
     m_beginSentenceFactor(copy_from.m_beginSentenceFactor) {
-#ifndef WITH_THREADS
-  m_refcount = copy_from.m_refcount;
-  ++*m_refcount;
-#endif
   Init(manager);
 }
 
@@ -349,25 +319,30 @@ template <class Model> FFState *LanguageModelKen<Model>::EvaluateChart(const Cha
 } // namespace
 
 LanguageModel *ConstructKenLM(const std::string &file, ScoreIndexManager &manager, FactorType factorType, bool lazy) {
-  lm::ngram::ModelType model_type;
-  if (lm::ngram::RecognizeBinary(file.c_str(), model_type)) {
-    switch(model_type) {
-    case lm::ngram::HASH_PROBING:
+  try {
+    lm::ngram::ModelType model_type;
+    if (lm::ngram::RecognizeBinary(file.c_str(), model_type)) {
+      switch(model_type) {
+        case lm::ngram::HASH_PROBING:
+          return new LanguageModelKen<lm::ngram::ProbingModel>(file, manager, factorType, lazy);
+        case lm::ngram::TRIE_SORTED:
+          return new LanguageModelKen<lm::ngram::TrieModel>(file, manager, factorType, lazy);
+        case lm::ngram::QUANT_TRIE_SORTED:
+          return new LanguageModelKen<lm::ngram::QuantTrieModel>(file, manager, factorType, lazy);
+        case lm::ngram::ARRAY_TRIE_SORTED:
+          return new LanguageModelKen<lm::ngram::ArrayTrieModel>(file, manager, factorType, lazy);
+        case lm::ngram::QUANT_ARRAY_TRIE_SORTED:
+          return new LanguageModelKen<lm::ngram::QuantArrayTrieModel>(file, manager, factorType, lazy);
+        default:
+          std::cerr << "Unrecognized kenlm model type " << model_type << std::endl;
+          abort();
+      }
+    } else {
       return new LanguageModelKen<lm::ngram::ProbingModel>(file, manager, factorType, lazy);
-    case lm::ngram::TRIE_SORTED:
-      return new LanguageModelKen<lm::ngram::TrieModel>(file, manager, factorType, lazy);
-    case lm::ngram::QUANT_TRIE_SORTED:
-      return new LanguageModelKen<lm::ngram::QuantTrieModel>(file, manager, factorType, lazy);
-    case lm::ngram::ARRAY_TRIE_SORTED:
-      return new LanguageModelKen<lm::ngram::ArrayTrieModel>(file, manager, factorType, lazy);
-    case lm::ngram::QUANT_ARRAY_TRIE_SORTED:
-      return new LanguageModelKen<lm::ngram::QuantArrayTrieModel>(file, manager, factorType, lazy);
-    default:
-      std::cerr << "Unrecognized kenlm model type " << model_type << std::endl;
-      abort();
     }
-  } else {
-    return new LanguageModelKen<lm::ngram::ProbingModel>(file, manager, factorType, lazy);
+  } catch (std::exception &e) {
+    std::cerr << e.what() << std::endl;
+    abort();
   }
 }