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https://github.com/moses-smt/mosesdecoder.git
synced 2024-09-11 11:25:40 +03:00
move options out of Hypothesis
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73ab44c126
commit
5fea16a9a6
@ -241,7 +241,7 @@ PrintHypothesis() const
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void
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Hypothesis::
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CleanupArcList()
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CleanupArcList(size_t nBestSize, bool distinctNBest)
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{
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// point this hypo's main hypo to itself
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SetWinningHypo(this);
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@ -253,11 +253,6 @@ CleanupArcList()
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* so we'll keep all of arc list if nedd distinct n-best list
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*/
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const StaticData &staticData = StaticData::Instance();
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AllOptions const& opts = m_manager.options();
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size_t nBestSize = opts.nbest.nbest_size;
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bool distinctNBest = opts.NBestDistinct();
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if (!distinctNBest && m_arcList->size() > nBestSize * 5) {
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// prune arc list only if there too many arcs
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NTH_ELEMENT4(m_arcList->begin(), m_arcList->begin() + nBestSize - 1,
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@ -351,7 +346,7 @@ GetTargetPhraseStringRep() const
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void
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Hypothesis::
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OutputAlignment(std::ostream &out) const
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OutputAlignment(std::ostream &out, WordAlignmentSort sortOrder) const
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{
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std::vector<const Hypothesis *> edges;
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const Hypothesis *currentHypo = this;
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@ -360,7 +355,7 @@ OutputAlignment(std::ostream &out) const
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currentHypo = currentHypo->GetPrevHypo();
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}
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OutputAlignment(out, edges, m_manager.options().output.WA_SortOrder);
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OutputAlignment(out, edges, sortOrder);
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}
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@ -426,13 +421,13 @@ OutputInput(std::ostream& os) const
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void
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Hypothesis::
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OutputBestSurface(std::ostream &out, const std::vector<FactorType> &outputFactorOrder,
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char reportSegmentation, bool reportAllFactors) const
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const ReportingOptions &options) const
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{
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if (m_prevHypo) {
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// recursively retrace this best path through the lattice, starting from the end of the hypothesis sentence
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m_prevHypo->OutputBestSurface(out, outputFactorOrder, reportSegmentation, reportAllFactors);
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m_prevHypo->OutputBestSurface(out, outputFactorOrder, options);
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}
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OutputSurface(out, *this, outputFactorOrder, reportSegmentation, reportAllFactors);
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OutputSurface(out, *this, outputFactorOrder, options);
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}
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//////////////////////////////////////////////////////////////////////////
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@ -443,14 +438,15 @@ void
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Hypothesis::
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OutputSurface(std::ostream &out, const Hypothesis &edge,
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const std::vector<FactorType> &outputFactorOrder,
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char reportSegmentation, bool reportAllFactors) const
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const ReportingOptions &options) const
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{
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UTIL_THROW_IF2(outputFactorOrder.size() == 0,
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"Must specific at least 1 output factor");
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const TargetPhrase& phrase = edge.GetCurrTargetPhrase();
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// TODO: slay the rest of StaticData here and move stuff into ReportingOptions
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bool markUnknown = GetManager().options().unk.mark;
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// = StaticData::Instance().GetMarkUnknown();
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if (reportAllFactors == true) {
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bool featureLabels = StaticData::Instance().options().nbest.include_feature_labels;
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if (options.ReportAllFactors == true) {
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out << phrase;
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} else {
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FactorType placeholderFactor
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@ -498,23 +494,21 @@ OutputSurface(std::ostream &out, const Hypothesis &edge,
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}
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// trace ("report segmentation") option "-t" / "-tt"
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if (reportSegmentation > 0 && phrase.GetSize() > 0) {
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if (options.ReportSegmentation > 0 && phrase.GetSize() > 0) {
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const Range &sourceRange = edge.GetCurrSourceWordsRange();
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const int sourceStart = sourceRange.GetStartPos();
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const int sourceEnd = sourceRange.GetEndPos();
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out << "|" << sourceStart << "-" << sourceEnd; // enriched "-tt"
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if (reportSegmentation == 2) {
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WordAlignmentSort waso = m_manager.options().output.WA_SortOrder;
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if (options.ReportSegmentation == 2) {
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out << ",wa=";
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const AlignmentInfo &ai = edge.GetCurrTargetPhrase().GetAlignTerm();
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Hypothesis::OutputAlignment(out, ai, 0, 0, waso);
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Hypothesis::OutputAlignment(out, ai, 0, 0, options.WA_SortOrder);
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out << ",total=";
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out << edge.GetScore() - edge.GetPrevHypo()->GetScore();
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out << ",";
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ScoreComponentCollection scoreBreakdown(edge.GetScoreBreakdown());
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scoreBreakdown.MinusEquals(edge.GetPrevHypo()->GetScoreBreakdown());
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bool with_labels = m_manager.options().nbest.include_feature_labels;
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scoreBreakdown.OutputAllFeatureScores(out, with_labels);
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scoreBreakdown.OutputAllFeatureScores(out, featureLabels);
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}
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out << "| ";
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}
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@ -50,6 +50,7 @@ class FFState;
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class StatelessFeatureFunction;
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class StatefulFeatureFunction;
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class Manager;
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class ReportingOptions;
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typedef std::vector<Hypothesis*> ArcList;
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@ -201,7 +202,7 @@ public:
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}
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void AddArc(Hypothesis *loserHypo);
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void CleanupArcList();
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void CleanupArcList(size_t nBestSize, bool distinctNBest);
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//! returns a list alternative previous hypotheses (or NULL if n-best support is disabled)
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inline const ArcList* GetArcList() const {
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@ -239,7 +240,7 @@ public:
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}
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void
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OutputAlignment(std::ostream &out) const;
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OutputAlignment(std::ostream &out, WordAlignmentSort sortOrder) const;
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static void
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OutputAlignment(std::ostream &out,
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@ -254,9 +255,9 @@ public:
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void OutputInput(std::ostream& os) const;
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static void OutputInput(std::vector<const Phrase*>& map, const Hypothesis* hypo);
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void OutputBestSurface(std::ostream &out, const std::vector<Moses::FactorType> &outputFactorOrder, char reportSegmentation, bool reportAllFactors) const;
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void OutputBestSurface(std::ostream &out, const std::vector<Moses::FactorType> &outputFactorOrder, const ReportingOptions &options) const;
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void OutputSurface(std::ostream &out, const Hypothesis &edge, const std::vector<FactorType> &outputFactorOrder,
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char reportSegmentation, bool reportAllFactors) const;
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const ReportingOptions &options) const;
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// creates a map of TARGET positions which should be replaced by word using placeholder
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std::map<size_t, const Moses::Factor*> GetPlaceholders(const Moses::Hypothesis &hypo, Moses::FactorType placeholderFactor) const;
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@ -267,8 +268,8 @@ public:
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#ifdef HAVE_XMLRPC_C
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// these are implemented in moses/server/Hypothesis_4server.cpp !
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void OutputWordAlignment(std::vector<xmlrpc_c::value>& out) const;
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void OutputLocalWordAlignment(std::vector<xmlrpc_c::value>& dest) const;
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void OutputWordAlignment(std::vector<xmlrpc_c::value>& out, const ReportingOptions &options) const;
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void OutputLocalWordAlignment(std::vector<xmlrpc_c::value>& dest, const ReportingOptions &options) const;
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#endif
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bool beats(Hypothesis const& b) const;
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@ -244,7 +244,7 @@ void HypothesisStackCubePruning::CleanupArcList()
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iterator iter;
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for (iter = m_hypos.begin() ; iter != m_hypos.end() ; ++iter) {
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Hypothesis *mainHypo = *iter;
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mainHypo->CleanupArcList();
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mainHypo->CleanupArcList(this->m_manager.options().nbest.nbest_size, this->m_manager.options().NBestDistinct());
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}
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}
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@ -266,7 +266,7 @@ void HypothesisStackNormal::CleanupArcList()
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iterator iter;
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for (iter = m_hypos.begin() ; iter != m_hypos.end() ; ++iter) {
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Hypothesis *mainHypo = *iter;
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mainHypo->CleanupArcList();
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mainHypo->CleanupArcList(this->m_manager.options().nbest.nbest_size, this->m_manager.options().NBestDistinct());
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}
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}
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@ -1547,11 +1547,10 @@ void Manager::OutputBest(OutputCollector *collector) const
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bestHypo->OutputBestSurface(
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out,
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staticData.GetOutputFactorOrder(),
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options().output.ReportSegmentation,
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options().output.ReportAllFactors);
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options().output);
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if (options().output.PrintAlignmentInfo) {
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out << "||| ";
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bestHypo->OutputAlignment(out);
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bestHypo->OutputAlignment(out, options().output.WA_SortOrder);
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}
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IFVERBOSE(1) {
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@ -5,15 +5,14 @@
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namespace Moses {
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void
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Hypothesis::
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OutputLocalWordAlignment(std::vector<xmlrpc_c::value>& dest) const
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OutputLocalWordAlignment(std::vector<xmlrpc_c::value>& dest, const ReportingOptions &options) const
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{
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using namespace std;
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Range const& src = this->GetCurrSourceWordsRange();
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Range const& trg = this->GetCurrTargetWordsRange();
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WordAlignmentSort waso = m_manager.options().output.WA_SortOrder;
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vector<pair<size_t,size_t> const* > a
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= this->GetCurrTargetPhrase().GetAlignTerm().GetSortedAlignments(waso);
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= this->GetCurrTargetPhrase().GetAlignTerm().GetSortedAlignments(options.WA_SortOrder);
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typedef pair<size_t,size_t> item;
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map<string, xmlrpc_c::value> M;
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BOOST_FOREACH(item const* p, a) {
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@ -25,13 +24,13 @@ namespace Moses {
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void
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Hypothesis::
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OutputWordAlignment(std::vector<xmlrpc_c::value>& out) const
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OutputWordAlignment(std::vector<xmlrpc_c::value>& out, const ReportingOptions &options) const
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{
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std::vector<Hypothesis const*> tmp;
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for (Hypothesis const* h = this; h; h = h->GetPrevHypo())
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tmp.push_back(h);
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for (size_t i = tmp.size(); i-- > 0;)
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tmp[i]->OutputLocalWordAlignment(out);
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tmp[i]->OutputLocalWordAlignment(out, options);
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}
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}
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@ -391,7 +391,7 @@ pack_hypothesis(vector<Hypothesis const* > const& edges, string const& key,
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// word alignment, if requested
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vector<xmlrpc_c::value> w_aln;
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BOOST_FOREACH(Hypothesis const* e, edges)
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e->OutputLocalWordAlignment(w_aln);
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e->OutputLocalWordAlignment(w_aln, m_options.output);
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dest["word-align"] = xmlrpc_c::value_array(w_aln);
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}
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}
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