void IOWrapper::OutputNBestList(const ChartTrellisPathList &nBestList, const ChartHypothesis *bestHypo, const TranslationSystem* system, long translationId)
{
std::ostringstream out;
// Check if we're writing to std::cout.
if (m_nBestOutputCollector->OutputIsCout()) {
// Set precision only if we're writing the n-best list to cout. This is to
// preserve existing behaviour, but should probably be done either way.
IOWrapper::FixPrecision(out);
// The output from -output-hypo-score is always written to std::cout.
if (StaticData::Instance().GetOutputHypoScore()) {
if (bestHypo != NULL) {
out << bestHypo->GetTotalScore() << " ";
} else {
out << "0 ";
}
}
}
bool labeledOutput = StaticData::Instance().IsLabeledNBestList();
//bool includeAlignment = StaticData::Instance().NBestIncludesAlignment();
ChartTrellisPathList::const_iterator iter;
for (iter = nBestList.begin() ; iter != nBestList.end() ; ++iter) {
const ChartTrellisPath &path = **iter;
//cerr << path << endl << endl;
Moses::Phrase outputPhrase = path.GetOutputPhrase();
// delete 1st & last
CHECK(outputPhrase.GetSize() >= 2);
outputPhrase.RemoveWord(0);
outputPhrase.RemoveWord(outputPhrase.GetSize() - 1);
// print the surface factor of the translation
out << translationId << " ||| ";
OutputSurface(out, outputPhrase, m_outputFactorOrder, false);
out << " ||| ";
// print the scores in a hardwired order
// before each model type, the corresponding command-line-like name must be emitted
// MERT script relies on this
// lm
const LMList& lml = system->GetLanguageModels();
if (lml.size() > 0) {
if (labeledOutput)
out << "lm:";
LMList::const_iterator lmi = lml.begin();
for (; lmi != lml.end(); ++lmi) {
out << " " << path.GetScoreBreakdown().GetScoreForProducer(*lmi);
}
}
std::string lastName = "";
// output stateful sparse features
const vector<const StatefulFeatureFunction*>& sff = system->GetStatefulFeatureFunctions();
for( size_t i=0; i<sff.size(); i++ )
if (sff[i]->GetNumScoreComponents() == ScoreProducer::unlimited)
OutputSparseFeatureScores( out, path, sff[i], lastName );
// translation components
const vector<PhraseDictionaryFeature*>& pds = system->GetPhraseDictionaries();
if (pds.size() > 0) {
for( size_t i=0; i<pds.size(); i++ ) {
size_t pd_numinputscore = pds[i]->GetNumInputScores();
vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer( pds[i] );
for (size_t j = 0; j<scores.size(); ++j){
if (labeledOutput && (i == 0) ){
if ((j == 0) || (j == pd_numinputscore)){
lastName = pds[i]->GetScoreProducerWeightShortName(j);
out << " " << lastName << ":";
}
}
out << " " << scores[j];
}
}
}
// word penalty
if (labeledOutput)
out << " w:";
out << " " << path.GetScoreBreakdown().GetScoreForProducer(system->GetWordPenaltyProducer());
// generation
const vector<GenerationDictionary*>& gds = system->GetGenerationDictionaries();
if (gds.size() > 0) {
for( size_t i=0; i<gds.size(); i++ ) {
size_t pd_numinputscore = gds[i]->GetNumInputScores();
vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer( gds[i] );
for (size_t j = 0; j<scores.size(); ++j){
if (labeledOutput && (i == 0) ){
if ((j == 0) || (j == pd_numinputscore)){
lastName = gds[i]->GetScoreProducerWeightShortName(j);
out << " " << lastName << ":";
}
}
out << " " << scores[j];
}
}
}
// output stateless sparse features
lastName = "";
const vector<const StatelessFeatureFunction*>& slf = system->GetStatelessFeatureFunctions();
for( size_t i=0; i<slf.size(); i++ ) {
if (slf[i]->GetNumScoreComponents() == ScoreProducer::unlimited) {
OutputSparseFeatureScores( out, path, slf[i], lastName );
}
}
// total
out << " ||| " << path.GetTotalScore();
/*
if (includeAlignment) {
*m_nBestStream << " |||";
for (int currEdge = (int)edges.size() - 2 ; currEdge >= 0 ; currEdge--)
{
const ChartHypothesis &edge = *edges[currEdge];
WordsRange sourceRange = edge.GetCurrSourceWordsRange();
WordsRange targetRange = edge.GetCurrTargetWordsRange();
*m_nBestStream << " " << sourceRange.GetStartPos();
if (sourceRange.GetStartPos() < sourceRange.GetEndPos()) {
*m_nBestStream << "-" << sourceRange.GetEndPos();
}
*m_nBestStream << "=" << targetRange.GetStartPos();
if (targetRange.GetStartPos() < targetRange.GetEndPos()) {
*m_nBestStream << "-" << targetRange.GetEndPos();
}
}
}
*/
out << endl;
}
out <<std::flush;
CHECK(m_nBestOutputCollector);
m_nBestOutputCollector->Write(translationId, out.str());
}
void IOWrapper::OutputNBestList(const MosesChart::TrellisPathList &nBestList, const MosesChart::Hypothesis *bestHypo, const TranslationSystem* system, long translationId)
{
std::ostringstream out;
// Check if we're writing to std::cout.
if (m_surpressSingleBestOutput)
{
// Set precision only if we're writing the n-best list to cout. This is to
// preserve existing behaviour, but should probably be done either way.
IOWrapper::FixPrecision(out);
// The output from -output-hypo-score is always written to std::cout.
if (StaticData::Instance().GetOutputHypoScore())
{
if (bestHypo != NULL)
{
out << bestHypo->GetTotalScore() << " "
<< MosesChart::Hypothesis::GetHypoCount() << " ";
}
else
{
out << "0 ";
}
}
}
bool labeledOutput = StaticData::Instance().IsLabeledNBestList();
//bool includeAlignment = StaticData::Instance().NBestIncludesAlignment();
MosesChart::TrellisPathList::const_iterator iter;
for (iter = nBestList.begin() ; iter != nBestList.end() ; ++iter)
{
const MosesChart::TrellisPath &path = **iter;
//cerr << path << endl << endl;
Moses::Phrase outputPhrase = path.GetOutputPhrase();
// delete 1st & last
assert(outputPhrase.GetSize() >= 2);
outputPhrase.RemoveWord(0);
outputPhrase.RemoveWord(outputPhrase.GetSize() - 1);
// print the surface factor of the translation
out << translationId << " ||| ";
OutputSurface(out, outputPhrase, m_outputFactorOrder, false);
out << " ||| ";
// print the scores in a hardwired order
// before each model type, the corresponding command-line-like name must be emitted
// MERT script relies on this
// lm
const LMList& lml = system->GetLanguageModels();
if (lml.size() > 0) {
if (labeledOutput)
out << "lm: ";
LMList::const_iterator lmi = lml.begin();
for (; lmi != lml.end(); ++lmi) {
out << path.GetScoreBreakdown().GetScoreForProducer(*lmi) << " ";
}
}
// translation components
if (StaticData::Instance().GetInputType()==SentenceInput){
// translation components for text input
vector<PhraseDictionaryFeature*> pds = system->GetPhraseDictionaries();
if (pds.size() > 0) {
if (labeledOutput)
out << "tm: ";
vector<PhraseDictionaryFeature*>::iterator iter;
for (iter = pds.begin(); iter != pds.end(); ++iter) {
vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer(*iter);
for (size_t j = 0; j<scores.size(); ++j)
out << scores[j] << " ";
}
}
}
else{
// translation components for Confusion Network input
// first translation component has GetNumInputScores() scores from the input Confusion Network
// at the beginning of the vector
vector<PhraseDictionaryFeature*> pds = system->GetPhraseDictionaries();
if (pds.size() > 0) {
vector<PhraseDictionaryFeature*>::iterator iter;
iter = pds.begin();
vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer(*iter);
size_t pd_numinputscore = (*iter)->GetNumInputScores();
if (pd_numinputscore){
if (labeledOutput)
out << "I: ";
for (size_t j = 0; j < pd_numinputscore; ++j)
out << scores[j] << " ";
}
for (iter = pds.begin() ; iter != pds.end(); ++iter) {
vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer(*iter);
size_t pd_numinputscore = (*iter)->GetNumInputScores();
if (iter == pds.begin() && labeledOutput)
out << "tm: ";
for (size_t j = pd_numinputscore; j < scores.size() ; ++j)
out << scores[j] << " ";
}
}
}
// word penalty
if (labeledOutput)
out << "w: ";
out << path.GetScoreBreakdown().GetScoreForProducer(system->GetWordPenaltyProducer()) << " ";
// generation
const vector<GenerationDictionary*> gds = system->GetGenerationDictionaries();
if (gds.size() > 0) {
if (labeledOutput)
out << "g: ";
vector<GenerationDictionary*>::const_iterator iter;
for (iter = gds.begin(); iter != gds.end(); ++iter) {
vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer(*iter);
for (size_t j = 0; j<scores.size(); j++) {
out << scores[j] << " ";
}
}
}
// total
out << "||| " << path.GetTotalScore();
/*
if (includeAlignment) {
*m_nBestStream << " |||";
for (int currEdge = (int)edges.size() - 2 ; currEdge >= 0 ; currEdge--)
{
const MosesChart::Hypothesis &edge = *edges[currEdge];
WordsRange sourceRange = edge.GetCurrSourceWordsRange();
WordsRange targetRange = edge.GetCurrTargetWordsRange();
*m_nBestStream << " " << sourceRange.GetStartPos();
if (sourceRange.GetStartPos() < sourceRange.GetEndPos()) {
*m_nBestStream << "-" << sourceRange.GetEndPos();
}
*m_nBestStream << "=" << targetRange.GetStartPos();
if (targetRange.GetStartPos() < targetRange.GetEndPos()) {
*m_nBestStream << "-" << targetRange.GetEndPos();
}
}
}
*/
out << endl;
}
out <<std::flush;
assert(m_nBestOutputCollector);
m_nBestOutputCollector->Write(translationId, out.str());
}
