/// add phrase alignment information from a Hypothesis
void
TranslationRequest::
add_phrase_aln_info(Hypothesis const& h, vector<xmlrpc_c::value>& aInfo) const
{
if (!m_withAlignInfo) return;
WordsRange const& trg = h.GetCurrTargetWordsRange();
WordsRange const& src = h.GetCurrSourceWordsRange();
std::map<std::string, xmlrpc_c::value> pAlnInfo;
pAlnInfo["tgt-start"] = xmlrpc_c::value_int(trg.GetStartPos());
pAlnInfo["src-start"] = xmlrpc_c::value_int(src.GetStartPos());
pAlnInfo["src-end"] = xmlrpc_c::value_int(src.GetEndPos());
aInfo.push_back(xmlrpc_c::value_struct(pAlnInfo));
}
void KENLM<Model>::EvaluateWhenApplied(const ManagerBase &mgr,
const Hypothesis &hypo, const FFState &prevState, Scores &scores,
FFState &state) const
{
KenLMState &stateCast = static_cast<KenLMState&>(state);
const System &system = mgr.system;
const lm::ngram::State &in_state =
static_cast<const KenLMState&>(prevState).state;
if (!hypo.GetTargetPhrase().GetSize()) {
stateCast.state = in_state;
return;
}
const std::size_t begin = hypo.GetCurrTargetWordsRange().GetStartPos();
//[begin, end) in STL-like fashion.
const std::size_t end = hypo.GetCurrTargetWordsRange().GetEndPos() + 1;
const std::size_t adjust_end = std::min(end, begin + m_ngram->Order() - 1);
std::size_t position = begin;
typename Model::State aux_state;
typename Model::State *state0 = &stateCast.state, *state1 = &aux_state;
float score = m_ngram->Score(in_state, TranslateID(hypo.GetWord(position)),
*state0);
++position;
for (; position < adjust_end; ++position) {
score += m_ngram->Score(*state0, TranslateID(hypo.GetWord(position)),
*state1);
std::swap(state0, state1);
}
if (hypo.GetBitmap().IsComplete()) {
// Score end of sentence.
std::vector<lm::WordIndex> indices(m_ngram->Order() - 1);
const lm::WordIndex *last = LastIDs(hypo, &indices.front());
score += m_ngram->FullScoreForgotState(&indices.front(), last,
m_ngram->GetVocabulary().EndSentence(), stateCast.state).prob;
} else if (adjust_end < end) {
// Get state after adding a long phrase.
std::vector<lm::WordIndex> indices(m_ngram->Order() - 1);
const lm::WordIndex *last = LastIDs(hypo, &indices.front());
m_ngram->GetState(&indices.front(), last, stateCast.state);
} else if (state0 != &stateCast.state) {
// Short enough phrase that we can just reuse the state.
stateCast.state = *state0;
}
score = TransformLMScore(score);
bool OOVFeatureEnabled = false;
if (OOVFeatureEnabled) {
std::vector<float> scoresVec(2);
scoresVec[0] = score;
scoresVec[1] = 0.0;
scores.PlusEquals(system, *this, scoresVec);
} else {
scores.PlusEquals(system, *this, score);
}
}
