move methods for PDAimp into .cpp file

1 files changed, 463 insertions, 0 deletions

diff --git a/moses/PDTAimp.cpp b/moses/PDTAimp.cpp
new file mode 100644
index 000000000..1645a0cce
--- /dev/null
+++ b/moses/PDTAimp.cpp
@@ -0,0 +1,463 @@
+#include "PDTAimp.h"
+
+namespace Moses
+{
+
+PDTAimp::PDTAimp(PhraseDictionaryTreeAdaptor *p)
+  : m_dict(0),
+    m_obj(p),
+    useCache(1),
+    totalE(0),
+    distinctE(0) {
+  m_numInputScores = 0;
+  const StaticData &staticData = StaticData::Instance();
+  m_inputFeature = &InputFeature::Instance();
+
+  if (m_inputFeature) {
+    const PhraseDictionary *firstPt = PhraseDictionary::GetColl()[0];
+    if (firstPt == m_obj) {
+      m_numInputScores = m_inputFeature->GetNumScoreComponents();
+    }
+  }
+}
+
+PDTAimp::~PDTAimp() {
+  CleanUp();
+  delete m_dict;
+
+  if (StaticData::Instance().GetVerboseLevel() >= 2) {
+
+    TRACE_ERR("tgt candidates stats:  total="<<totalE<<";  distinct="
+              <<distinctE<<" ("<<distinctE/(0.01*totalE)<<");  duplicates="
+              <<totalE-distinctE<<" ("<<(totalE-distinctE)/(0.01*totalE)
+              <<")\n");
+
+    TRACE_ERR("\npath statistics\n");
+
+    if(path1Best.size()) {
+      TRACE_ERR("1-best:        ");
+      std::copy(path1Best.begin()+1,path1Best.end(),
+                std::ostream_iterator<size_t>(std::cerr," \t"));
+      TRACE_ERR("\n");
+    }
+    if(pathCN.size()) {
+      TRACE_ERR("CN (full):     ");
+      std::transform(pathCN.begin()+1
+                     ,pathCN.end()
+                     ,std::ostream_iterator<double>(std::cerr," \t")
+                     ,Exp);
+      TRACE_ERR("\n");
+    }
+    if(pathExplored.size()) {
+      TRACE_ERR("CN (explored): ");
+      std::copy(pathExplored.begin()+1,pathExplored.end(),
+                std::ostream_iterator<size_t>(std::cerr," \t"));
+      TRACE_ERR("\n");
+    }
+  }
+
+}
+
+void PDTAimp::CleanUp() {
+  assert(m_dict);
+  m_dict->FreeMemory();
+  for(size_t i=0; i<m_tgtColls.size(); ++i) delete m_tgtColls[i];
+  m_tgtColls.clear();
+  m_cache.clear();
+  m_rangeCache.clear();
+  uniqSrcPhr.clear();
+}
+
+TargetPhraseCollectionWithSourcePhrase const*
+PDTAimp::GetTargetPhraseCollection(Phrase const &src) const {
+
+	assert(m_dict);
+  if(src.GetSize()==0) return 0;
+
+  std::pair<MapSrc2Tgt::iterator,bool> piter;
+  if(useCache) {
+    piter=m_cache.insert(std::make_pair(src,static_cast<TargetPhraseCollectionWithSourcePhrase const*>(0)));
+    if(!piter.second) return piter.first->second;
+  } else if (m_cache.size()) {
+    MapSrc2Tgt::const_iterator i=m_cache.find(src);
+    return (i!=m_cache.end() ? i->second : 0);
+  }
+
+  std::vector<std::string> srcString(src.GetSize());
+  // convert source Phrase into vector of strings
+  for(size_t i=0; i<srcString.size(); ++i) {
+    Factors2String(src.GetWord(i),srcString[i]);
+  }
+
+  // get target phrases in string representation
+  std::vector<StringTgtCand> cands;
+  std::vector<std::string> wacands;
+  m_dict->GetTargetCandidates(srcString,cands,wacands);
+  if(cands.empty()) {
+    return 0;
+  }
+
+  //TODO: Multiple models broken here
+  std::vector<float> weights = StaticData::Instance().GetWeights(m_obj);
+
+  std::vector<TargetPhrase> tCands;
+  tCands.reserve(cands.size());
+
+  std::vector<std::pair<float,size_t> > costs;
+  costs.reserve(cands.size());
+
+  std::vector<Phrase> sourcePhrases;
+  sourcePhrases.reserve(cands.size());
+
+
+  // convert into TargetPhrases
+  for(size_t i=0; i<cands.size(); ++i) {
+    TargetPhrase targetPhrase;
+
+    StringTgtCand::Tokens const& factorStrings=cands[i].tokens;
+    Scores const& probVector=cands[i].scores;
+
+    std::vector<float> scoreVector(probVector.size());
+    std::transform(probVector.begin(),probVector.end(),scoreVector.begin(),
+                   TransformScore);
+    std::transform(scoreVector.begin(),scoreVector.end(),scoreVector.begin(),
+                   FloorScore);
+
+    //sparse features.
+    //These are already in log-space
+    for (size_t j = 0; j < cands[i].fnames.size(); ++j) {
+      targetPhrase.GetScoreBreakdown().Assign(m_obj, *cands[i].fnames[j], cands[i].fvalues[j]);
+    }
+
+    CreateTargetPhrase(targetPhrase,factorStrings,scoreVector, Scores(0), &wacands[i], &src);
+
+    costs.push_back(std::make_pair(-targetPhrase.GetFutureScore(),tCands.size()));
+    tCands.push_back(targetPhrase);
+
+    sourcePhrases.push_back(src);
+  }
+
+  TargetPhraseCollectionWithSourcePhrase *rv;
+  rv=PruneTargetCandidates(tCands,costs, sourcePhrases);
+  if(rv->IsEmpty()) {
+    delete rv;
+    return 0;
+  } else {
+    if(useCache) piter.first->second=rv;
+    m_tgtColls.push_back(rv);
+    return rv;
+  }
+
+}
+
+void PDTAimp::Create(const std::vector<FactorType> &input
+            , const std::vector<FactorType> &output
+            , const std::string &filePath
+            , const std::vector<float> &weight
+           ) {
+
+  // set my members
+  m_dict=new PhraseDictionaryTree();
+  m_input=input;
+  m_output=output;
+
+  const StaticData &staticData = StaticData::Instance();
+  m_dict->NeedAlignmentInfo(staticData.NeedAlignmentInfo());
+
+  std::string binFname=filePath+".binphr.idx";
+  if(!FileExists(binFname.c_str())) {
+    UTIL_THROW2( "bin ttable does not exist");
+    //TRACE_ERR( "bin ttable does not exist -> create it\n");
+    //InputFileStream in(filePath);
+    //m_dict->Create(in,filePath);
+  }
+  VERBOSE(1,"reading bin ttable\n");
+//		m_dict->Read(filePath);
+  bool res=m_dict->Read(filePath);
+  if (!res) {
+    std::stringstream strme;
+    strme << "bin ttable was read in a wrong way\n";
+    UserMessage::Add(strme.str());
+    exit(1);
+  }
+}
+
+
+void PDTAimp::CacheSource(ConfusionNet const& src) {
+	assert(m_dict);
+  const size_t srcSize=src.GetSize();
+
+  std::vector<size_t> exploredPaths(srcSize+1,0);
+  std::vector<double> exPathsD(srcSize+1,-1.0);
+
+  // collect some statistics
+  std::vector<size_t> cnDepths(srcSize,0);
+  for(size_t i=0; i<srcSize; ++i) cnDepths[i]=src[i].size();
+
+  for(size_t len=1; len<=srcSize; ++len)
+    for(size_t i=0; i<=srcSize-len; ++i) {
+      double pd=0.0;
+      for(size_t k=i; k<i+len; ++k)	pd+=log(1.0*cnDepths[k]);
+      exPathsD[len]=(exPathsD[len]>=0.0 ? addLogScale(pd,exPathsD[len]) : pd);
+    }
+
+  // update global statistics
+  if(pathCN.size()<=srcSize) pathCN.resize(srcSize+1,-1.0);
+  for(size_t len=1; len<=srcSize; ++len)
+    pathCN[len]=pathCN[len]>=0.0 ? addLogScale(pathCN[len],exPathsD[len]) : exPathsD[len];
+
+  if(path1Best.size()<=srcSize) path1Best.resize(srcSize+1,0);
+  for(size_t len=1; len<=srcSize; ++len) path1Best[len]+=srcSize-len+1;
+
+
+  if (StaticData::Instance().GetVerboseLevel() >= 2 && exPathsD.size()) {
+    TRACE_ERR("path stats for current CN: \nCN (full):     ");
+    std::transform(exPathsD.begin()+1
+                   ,exPathsD.end()
+                   ,std::ostream_iterator<double>(std::cerr," ")
+                   ,Exp);
+    TRACE_ERR("\n");
+  }
+
+  typedef StringTgtCand::Tokens sPhrase;
+  typedef std::map<StringTgtCand::Tokens,TScores> E2Costs;
+
+  std::map<Range,E2Costs> cov2cand;
+  std::vector<State> stack;
+  for(Position i=0 ; i < srcSize ; ++i)
+    stack.push_back(State(i, i, m_dict->GetRoot(), std::vector<float>(m_numInputScores,0.0)));
+
+  std::vector<float> weightTrans = StaticData::Instance().GetWeights(m_obj);
+  std::vector<float> weightInput = StaticData::Instance().GetWeights(m_inputFeature);
+  float weightWP = StaticData::Instance().GetWeightWordPenalty();
+
+  while(!stack.empty()) {
+    State curr(stack.back());
+    stack.pop_back();
+
+    UTIL_THROW_IF2(curr.end() >= srcSize, "Error");
+    const ConfusionNet::Column &currCol=src[curr.end()];
+    // in a given column, loop over all possibilities
+    for(size_t colidx=0; colidx<currCol.size(); ++colidx) {
+      const Word& w=currCol[colidx].first; // w=the i^th possibility in column colidx
+      std::string s;
+      Factors2String(w,s);
+      bool isEpsilon=(s=="" || s==EPSILON);
+
+      //assert that we have the right number of link params in this CN option
+      UTIL_THROW_IF2(currCol[colidx].second.denseScores.size() < m_numInputScores,
+      		"Incorrect number of input scores");
+
+      // do not start with epsilon (except at first position)
+      if(isEpsilon && curr.begin()==curr.end() && curr.begin()>0) continue;
+
+      // At a given node in the prefix tree, look to see if w defines an edge to
+      // another node (Extend).  Stay at the same node if w==EPSILON
+      PPtr nextP = (isEpsilon ? curr.ptr : m_dict->Extend(curr.ptr,s));
+
+      if(nextP) { // w is a word that should be considered
+        Range newRange(curr.begin(),curr.end()+src.GetColumnIncrement(curr.end(),colidx));
+
+        //add together the link scores from the current state and the new arc
+        float inputScoreSum = 0;
+        std::vector<float> newInputScores(m_numInputScores,0.0);
+        if (m_numInputScores) {
+          std::transform(currCol[colidx].second.denseScores.begin(), currCol[colidx].second.denseScores.end(),
+                         curr.GetScores().begin(),
+                         newInputScores.begin(),
+                         std::plus<float>());
+
+
+          //we need to sum up link weights (excluding realWordCount, which isn't in numLinkParams)
+          //if the sum is too low, then we won't expand this.
+          //TODO: dodgy! shouldn't we consider weights here? what about zero-weight params?
+          inputScoreSum = std::accumulate(newInputScores.begin(),newInputScores.begin()+m_numInputScores,0.0);
+        }
+
+        Phrase newSrc(curr.src);
+        if(!isEpsilon) newSrc.AddWord(w);
+        if(newRange.second<srcSize && inputScoreSum>LOWEST_SCORE) {
+          // if there is more room to grow, add a new state onto the queue
+          // to be explored that represents [begin, curEnd+)
+          stack.push_back(State(newRange,nextP,newInputScores));
+          stack.back().src=newSrc;
+        }
+
+        std::vector<StringTgtCand> tcands;
+        // now, look up the target candidates (aprx. TargetPhraseCollection) for
+        // the current path through the CN
+        m_dict->GetTargetCandidates(nextP,tcands);
+
+        if(newRange.second>=exploredPaths.size()+newRange.first)
+          exploredPaths.resize(newRange.second-newRange.first+1,0);
+        ++exploredPaths[newRange.second-newRange.first];
+
+        totalE+=tcands.size();
+
+        if(tcands.size()) {
+          E2Costs& e2costs=cov2cand[newRange];
+          Phrase const* srcPtr=uniqSrcPhr(newSrc);
+          for(size_t i=0; i<tcands.size(); ++i) {
+            //put input scores in first - already logged, just drop in directly
+            std::vector<float> transcores(m_obj->GetNumScoreComponents());
+            UTIL_THROW_IF2(transcores.size() != weightTrans.size(),
+          		  "Incorrect number of translation scores");
+
+            //put in phrase table scores, logging as we insert
+            std::transform(tcands[i].scores.begin()
+                           ,tcands[i].scores.end()
+                           ,transcores.begin()
+                           ,TransformScore);
+
+
+            //tally up
+            float score=std::inner_product(transcores.begin(), transcores.end(), weightTrans.begin(), 0.0f);
+
+            // input feature
+            score +=std::inner_product(newInputScores.begin(), newInputScores.end(), weightInput.begin(), 0.0f);
+
+            //count word penalty
+            score-=tcands[i].tokens.size() * weightWP;
+
+            std::pair<E2Costs::iterator,bool> p=e2costs.insert(std::make_pair(tcands[i].tokens,TScores()));
+
+            if(p.second) ++distinctE;
+
+            TScores & scores=p.first->second;
+            if(p.second || scores.total<score) {
+              scores.total=score;
+              scores.transScore=transcores;
+              scores.inputScores=newInputScores;
+              scores.src=srcPtr;
+            }
+          }
+        }
+      }
+    }
+  } // end while(!stack.empty())
+
+
+  if (StaticData::Instance().GetVerboseLevel() >= 2 && exploredPaths.size()) {
+    TRACE_ERR("CN (explored): ");
+    std::copy(exploredPaths.begin()+1,exploredPaths.end(),
+              std::ostream_iterator<size_t>(std::cerr," "));
+    TRACE_ERR("\n");
+  }
+
+  if(pathExplored.size()<exploredPaths.size())
+    pathExplored.resize(exploredPaths.size(),0);
+  for(size_t len=1; len<=srcSize; ++len)
+    pathExplored[len]+=exploredPaths[len];
+
+
+  m_rangeCache.resize(src.GetSize(),vTPC(src.GetSize(),0));
+
+  for(std::map<Range,E2Costs>::const_iterator i=cov2cand.begin(); i!=cov2cand.end(); ++i) {
+    assert(i->first.first<m_rangeCache.size());
+    assert(i->first.second>0);
+    assert(static_cast<size_t>(i->first.second-1)<m_rangeCache[i->first.first].size());
+    assert(m_rangeCache[i->first.first][i->first.second-1]==0);
+
+    std::vector<TargetPhrase> tCands;
+    tCands.reserve(i->second.size());
+
+    std::vector<std::pair<float,size_t> > costs;
+    costs.reserve(i->second.size());
+
+    std::vector<Phrase> sourcePhrases;
+    sourcePhrases.reserve(i->second.size());
+
+    for(E2Costs::const_iterator j=i->second.begin(); j!=i->second.end(); ++j) {
+      TScores const & scores=j->second;
+      TargetPhrase targetPhrase;
+      CreateTargetPhrase(targetPhrase
+                         , j ->first
+                         , scores.transScore
+                         , scores.inputScores
+                         , NULL
+                         , scores.src);
+      costs.push_back(std::make_pair(-targetPhrase.GetFutureScore(),tCands.size()));
+      tCands.push_back(targetPhrase);
+
+      sourcePhrases.push_back(*scores.src);
+
+      //std::cerr << i->first.first << "-" << i->first.second << ": " << targetPhrase << std::endl;
+    }
+
+    TargetPhraseCollectionWithSourcePhrase *rv=PruneTargetCandidates(tCands, costs, sourcePhrases);
+
+    if(rv->IsEmpty())
+      delete rv;
+    else {
+      m_rangeCache[i->first.first][i->first.second-1]=rv;
+      m_tgtColls.push_back(rv);
+    }
+  }
+  // free memory
+  m_dict->FreeMemory();
+}
+
+void PDTAimp::CreateTargetPhrase(TargetPhrase& targetPhrase,
+                        StringTgtCand::Tokens const& factorStrings,
+                        Scores const& transVector,
+                        Scores const& inputVector,
+                        const std::string *alignmentString,
+                        Phrase const* srcPtr) const {
+  FactorCollection &factorCollection = FactorCollection::Instance();
+
+  for(size_t k=0; k<factorStrings.size(); ++k) {
+    util::TokenIter<util::MultiCharacter, false> word(*factorStrings[k], StaticData::Instance().GetFactorDelimiter());
+    Word& w=targetPhrase.AddWord();
+    for(size_t l=0; l<m_output.size(); ++l, ++word) {
+      w[m_output[l]]= factorCollection.AddFactor(*word);
+    }
+  }
+
+  if (alignmentString) {
+    targetPhrase.SetAlignmentInfo(*alignmentString);
+  }
+
+  if (m_numInputScores) {
+    targetPhrase.GetScoreBreakdown().Assign(m_inputFeature, inputVector);
+  }
+
+  targetPhrase.GetScoreBreakdown().Assign(m_obj, transVector);
+  targetPhrase.Evaluate(*srcPtr, m_obj->GetFeaturesToApply());
+}
+
+TargetPhraseCollectionWithSourcePhrase* PDTAimp::PruneTargetCandidates
+(const std::vector<TargetPhrase> & tCands,
+ std::vector<std::pair<float,size_t> >& costs,
+ const std::vector<Phrase> &sourcePhrases) const {
+  // convert into TargetPhraseCollection
+  UTIL_THROW_IF2(tCands.size() != sourcePhrases.size(),
+  		"Number of target phrases must equal number of source phrases");
+
+  TargetPhraseCollectionWithSourcePhrase *rv=new TargetPhraseCollectionWithSourcePhrase;
+
+
+  // set limit to tableLimit or actual size, whatever is smaller
+  std::vector<std::pair<float,size_t> >::iterator nth =
+    costs.begin() + ((m_obj->m_tableLimit>0 && // 0 indicates no limit
+                      m_obj->m_tableLimit < costs.size()) ?
+                     m_obj->m_tableLimit : costs.size());
+
+  // find the nth phrase according to future cost
+  NTH_ELEMENT3(costs.begin(),nth ,costs.end());
+
+  // add n top phrases to the return list
+  for(std::vector<std::pair<float,size_t> >::iterator
+      it = costs.begin(); it != nth; ++it) {
+    size_t ind = it->second;
+    TargetPhrase *targetPhrase = new TargetPhrase(tCands[ind]);
+    const Phrase &sourcePhrase = sourcePhrases[ind];
+    rv->Add(targetPhrase, sourcePhrase);
+
+  }
+
+  return rv;
+}
+
+}
+
+