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Diffstat (limited to 'decoder/incremental.cc')
| -rw-r--r-- | decoder/incremental.cc | 184 |
1 files changed, 184 insertions, 0 deletions
diff --git a/decoder/incremental.cc b/decoder/incremental.cc new file mode 100644 index 00000000..768bbd65 --- /dev/null +++ b/decoder/incremental.cc @@ -0,0 +1,184 @@ +#include "incremental.h" + +#include "hg.h" +#include "fdict.h" +#include "tdict.h" + +#include "lm/enumerate_vocab.hh" +#include "lm/model.hh" +#include "search/config.hh" +#include "search/context.hh" +#include "search/edge.hh" +#include "search/edge_generator.hh" +#include "search/rule.hh" +#include "search/vertex.hh" +#include "search/vertex_generator.hh" +#include "util/exception.hh" + +#include <boost/scoped_ptr.hpp> +#include <boost/scoped_array.hpp> + +#include <iostream> +#include <vector> + +namespace { + +struct MapVocab : public lm::EnumerateVocab { + public: + MapVocab() {} + + // Do not call after Lookup. + void Add(lm::WordIndex index, const StringPiece &str) { + const WordID cdec_id = TD::Convert(str.as_string()); + if (cdec_id >= out_.size()) out_.resize(cdec_id + 1); + out_[cdec_id] = index; + } + + // Assumes Add has been called and will never be called again. + lm::WordIndex FromCDec(WordID id) const { + return out_[out_.size() > id ? id : 0]; + } + + private: + std::vector<lm::WordIndex> out_; +}; + +class IncrementalBase { + public: + IncrementalBase(const std::vector<weight_t> &weights) : + cdec_weights_(weights), + weights_(weights[FD::Convert("KLanguageModel")], weights[FD::Convert("KLanguageModel_OOV")], weights[FD::Convert("WordPenalty")]) { + std::cerr << "Weights KLanguageModel " << weights_.LM() << " KLanguageModel_OOV " << weights_.OOV() << " WordPenalty " << weights_.WordPenalty() << std::endl; + } + + virtual ~IncrementalBase() {} + + virtual void Search(unsigned int pop_limit, const Hypergraph &hg) const = 0; + + static IncrementalBase *Load(const char *model_file, const std::vector<weight_t> &weights); + + protected: + lm::ngram::Config GetConfig() { + lm::ngram::Config ret; + ret.enumerate_vocab = &vocab_; + return ret; + } + + MapVocab vocab_; + + const std::vector<weight_t> &cdec_weights_; + + const search::Weights weights_; +}; + +template <class Model> class Incremental : public IncrementalBase { + public: + Incremental(const char *model_file, const std::vector<weight_t> &weights) : IncrementalBase(weights), m_(model_file, GetConfig()) {} + + void Search(unsigned int pop_limit, const Hypergraph &hg) const; + + private: + void ConvertEdge(const search::Context<Model> &context, bool final, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const; + + const Model m_; +}; + +IncrementalBase *IncrementalBase::Load(const char *model_file, const std::vector<weight_t> &weights) { + lm::ngram::ModelType model_type; + if (!lm::ngram::RecognizeBinary(model_file, model_type)) model_type = lm::ngram::PROBING; + switch (model_type) { + case lm::ngram::PROBING: + return new Incremental<lm::ngram::ProbingModel>(model_file, weights); + case lm::ngram::REST_PROBING: + return new Incremental<lm::ngram::RestProbingModel>(model_file, weights); + default: + UTIL_THROW(util::Exception, "Sorry this lm type isn't supported yet."); + } +} + +void PrintFinal(const Hypergraph &hg, const search::Final final) { + const std::vector<WordID> &words = static_cast<const Hypergraph::Edge*>(final.GetNote().vp)->rule_->e(); + const search::Final *child(final.Children()); + for (std::vector<WordID>::const_iterator i = words.begin(); i != words.end(); ++i) { + if (*i > 0) { + std::cout << TD::Convert(*i) << ' '; + } else { + PrintFinal(hg, *child++); + } + } +} + +template <class Model> void Incremental<Model>::Search(unsigned int pop_limit, const Hypergraph &hg) const { + boost::scoped_array<search::Vertex> out_vertices(new search::Vertex[hg.nodes_.size()]); + search::Config config(weights_, pop_limit); + search::Context<Model> context(config, m_); + + for (unsigned int i = 0; i < hg.nodes_.size() - 1; ++i) { + search::EdgeGenerator gen; + const Hypergraph::EdgesVector &down_edges = hg.nodes_[i].in_edges_; + for (unsigned int j = 0; j < down_edges.size(); ++j) { + unsigned int edge_index = down_edges[j]; + ConvertEdge(context, i == hg.nodes_.size() - 2, out_vertices.get(), hg.edges_[edge_index], gen); + } + search::VertexGenerator vertex_gen(context, out_vertices[i]); + gen.Search(context, vertex_gen); + } + const search::Final top = out_vertices[hg.nodes_.size() - 2].BestChild(); + if (top.Valid()) { + std::cout << "NO PATH FOUND" << std::endl; + } else { + PrintFinal(hg, top); + std::cout << "||| " << top.GetScore() << std::endl; + } +} + +template <class Model> void Incremental<Model>::ConvertEdge(const search::Context<Model> &context, bool final, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const { + const std::vector<WordID> &e = in.rule_->e(); + std::vector<lm::WordIndex> words; + words.reserve(e.size()); + std::vector<search::PartialVertex> nts; + unsigned int terminals = 0; + float score = 0.0; + for (std::vector<WordID>::const_iterator word = e.begin(); word != e.end(); ++word) { + if (*word <= 0) { + nts.push_back(vertices[in.tail_nodes_[-*word]].RootPartial()); + if (nts.back().Empty()) return; + score += nts.back().Bound(); + words.push_back(lm::kMaxWordIndex); + } else { + ++terminals; + words.push_back(vocab_.FromCDec(*word)); + } + } + + if (final) { + words.push_back(m_.GetVocabulary().EndSentence()); + } + + search::PartialEdge out(gen.AllocateEdge(nts.size())); + + memcpy(out.NT(), &nts[0], sizeof(search::PartialVertex) * nts.size()); + + search::Note note; + note.vp = ∈ + out.SetNote(note); + + score += in.rule_->GetFeatureValues().dot(cdec_weights_); + score -= static_cast<float>(terminals) * context.GetWeights().WordPenalty() / M_LN10; + score += search::ScoreRule(context, words, final, out.Between()); + out.SetScore(score); + + gen.AddEdge(out); +} + +boost::scoped_ptr<IncrementalBase> AwfulGlobalIncremental; + +} // namespace + +void PassToIncremental(const char *model_file, const std::vector<weight_t> &weights, unsigned int pop_limit, const Hypergraph &hg) { + if (!AwfulGlobalIncremental.get()) { + std::cerr << "Pop limit " << pop_limit << std::endl; + AwfulGlobalIncremental.reset(IncrementalBase::Load(model_file, weights)); + } + AwfulGlobalIncremental->Search(pop_limit, hg); +} |