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port PhraseDictionaryMultiModelCounts to new format. Runs but doesn't pass regression test

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This commit is contained in:
Hieu Hoang 2013-05-15 14:34:31 +01:00
parent 02099a9d73
commit b2488f83c3
1 changed files with 27 additions and 5 deletions
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32
moses/TranslationModel/PhraseDictionaryMultiModelCounts.cpp
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@ -25,6 +25,15 @@ Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
using namespace std;
template<typename T>
void outVec(const vector<T> &vec)
{
for (size_t i = 0; i < vec.size(); ++i) {
cerr << vec[i] << " " << flush;
}
cerr << endl;
}
// from phrase-extract/tables-core.cpp
vector<string> tokenize( const char* input )
{
@ -62,11 +71,12 @@ PhraseDictionaryMultiModelCounts::PhraseDictionaryMultiModelCounts(const std::st
for (size_t i = 0; i < m_args.size(); ++i) {
const vector<string> &args = m_args[i];
if (args[0] == "mode") {
m_mode =args[1];
m_mode = args[1];
if (m_mode == "instance_weighting")
m_combineFunction = InstanceWeighting;
else if (m_mode == "interpolate")
else if (m_mode == "interpolate") {
m_combineFunction = LinearInterpolationFromCounts;
}
else {
ostringstream msg;
msg << "combination mode unknown: " << m_mode;
@ -285,6 +295,8 @@ void PhraseDictionaryMultiModelCounts::CollectSufficientStatistics(const Phrase&
statistics->ft[i] = UntransformScore(raw_scores[1]);
fs[i] = UntransformScore(raw_scores[2]);
(*allStats)[targetString] = statistics;
outVec(statistics->ft);
}
}
}
@ -298,10 +310,10 @@ void PhraseDictionaryMultiModelCounts::CollectSufficientStatistics(const Phrase&
statistics->ft[i] = GetTargetCount(static_cast<const Phrase&>(*statistics->targetPhrase), i);
}
}
outVec(statistics->ft);
}
}
TargetPhraseCollection* PhraseDictionaryMultiModelCounts::CreateTargetPhraseCollectionCounts(const Phrase &src, vector<float> &fs, map<string,multiModelCountsStatistics*>* allStats, vector<vector<float> > &multimodelweights) const
{
TargetPhraseCollection *ret = new TargetPhraseCollection();
@ -332,6 +344,15 @@ TargetPhraseCollection* PhraseDictionaryMultiModelCounts::CreateTargetPhraseColl
cerr << scoreVector[i] << " ";
cerr << endl;
vector<float> a = statistics->fst;
vector<float> b = statistics->ft;
vector<float> c = multimodelweights[0];
float d = m_combineFunction(statistics->fst, statistics->ft, multimodelweights[0]);
outVec(a);
outVec(b);
outVec(c);
cerr << d << endl;
statistics->targetPhrase->GetScoreBreakdown().Assign(this, scoreVector);
}
catch (AlignmentException& e) {
@ -349,12 +370,13 @@ TargetPhraseCollection* PhraseDictionaryMultiModelCounts::CreateTargetPhraseColl
float PhraseDictionaryMultiModelCounts::GetTargetCount(const Phrase &target, size_t modelIndex) const {
TargetPhraseCollection *ret_raw = (TargetPhraseCollection*) m_inverse_pd[modelIndex]->GetTargetPhraseCollection(target);
const PhraseDictionary &pd = *m_inverse_pd[modelIndex];
TargetPhraseCollection *ret_raw = (TargetPhraseCollection*) pd.GetTargetPhraseCollection(target);
// in inverse mode, we want the first score of the first phrase pair (note: if we were to work with truly symmetric models, it would be the third score)
if (ret_raw != NULL) {
TargetPhrase * targetPhrase = *(ret_raw->begin());
return UntransformScore(targetPhrase->GetScoreBreakdown().GetScoresForProducer(this)[0]);
return UntransformScore(targetPhrase->GetScoreBreakdown().GetScoresForProducer(&pd)[0]);
}
// target phrase unknown