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Compiles, not tested. Conflicts: Jamroot OnDiskPt/PhraseNode.h OnDiskPt/TargetPhrase.cpp OnDiskPt/TargetPhrase.h OnDiskPt/TargetPhraseCollection.cpp mert/BleuScorer.cpp mert/Data.cpp mert/FeatureData.cpp moses-chart-cmd/src/Main.cpp moses/src/AlignmentInfo.h moses/src/ChartManager.cpp moses/src/LM/Ken.cpp moses/src/LM/Ken.h moses/src/LMList.h moses/src/LexicalReordering.h moses/src/PhraseDictionaryTree.h moses/src/ScoreIndexManager.h moses/src/StaticData.h moses/src/TargetPhrase.h moses/src/Word.cpp scripts/ems/experiment.meta scripts/ems/experiment.perl scripts/training/train-model.perl
133 lines
3.4 KiB
C++
133 lines
3.4 KiB
C++
/*
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* FeatureStats.h
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* mert - Minimum Error Rate Training
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*
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* Created by Nicola Bertoldi on 13/05/08.
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*
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*/
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#ifndef MERT_FEATURE_STATS_H_
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#define MERT_FEATURE_STATS_H_
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#include <cstring>
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#include <iostream>
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#include <map>
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#include <string>
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#include <vector>
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#include "Types.h"
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namespace MosesTuning
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{
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// Minimal sparse vector
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class SparseVector {
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public:
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typedef std::map<std::size_t,FeatureStatsType> fvector_t;
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typedef std::map<std::string, std::size_t> name2id_t;
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typedef std::vector<std::string> id2name_t;
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FeatureStatsType get(const std::string& name) const;
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FeatureStatsType get(std::size_t id) const;
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void set(const std::string& name, FeatureStatsType value);
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void clear();
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void load(const std::string& file);
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std::size_t size() const { return m_fvector.size(); }
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void write(std::ostream& out, const std::string& sep = " ") const;
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SparseVector& operator-=(const SparseVector& rhs);
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FeatureStatsType inner_product(const SparseVector& rhs) const;
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// Added by cherryc
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std::vector<std::size_t> feats() const;
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friend bool operator==(SparseVector const& item1, SparseVector const& item2);
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friend std::size_t hash_value(SparseVector const& item);
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static std::size_t encode(const std::string& feat);
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static std::string decode(std::size_t feat);
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// End added by cherryc
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private:
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static name2id_t m_name_to_id;
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static id2name_t m_id_to_name;
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fvector_t m_fvector;
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};
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SparseVector operator-(const SparseVector& lhs, const SparseVector& rhs);
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FeatureStatsType inner_product(const SparseVector& lhs, const SparseVector& rhs);
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class FeatureStats
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{
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private:
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std::size_t m_available_size;
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std::size_t m_entries;
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// TODO: Use smart pointer for exceptional-safety.
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featstats_t m_array;
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SparseVector m_map;
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public:
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FeatureStats();
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explicit FeatureStats(const std::size_t size);
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~FeatureStats();
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// We intentionally allow copying.
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FeatureStats(const FeatureStats &stats);
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FeatureStats& operator=(const FeatureStats &stats);
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void Copy(const FeatureStats &stats);
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bool isfull() const { return (m_entries < m_available_size) ? 0 : 1; }
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void expand();
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void add(FeatureStatsType v);
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void addSparse(const std::string& name, FeatureStatsType v);
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void clear() {
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memset((void*)m_array, 0, GetArraySizeWithBytes());
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m_map.clear();
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}
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void reset() {
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m_entries = 0;
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clear();
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}
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FeatureStatsType get(std::size_t i) { return m_array[i]; }
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FeatureStatsType get(std::size_t i)const { return m_array[i]; }
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featstats_t getArray() const { return m_array; }
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const SparseVector& getSparse() const { return m_map; }
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void set(std::string &theString, const SparseVector& sparseWeights);
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inline std::size_t bytes() const { return GetArraySizeWithBytes(); }
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std::size_t GetArraySizeWithBytes() const {
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return m_entries * sizeof(FeatureStatsType);
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}
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std::size_t size() const { return m_entries; }
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std::size_t available() const { return m_available_size; }
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void savetxt(const std::string &file);
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void savetxt(std::ostream* os);
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void savebin(std::ostream* os);
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void savetxt();
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void loadtxt(std::istream* is, const SparseVector& sparseWeights);
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void loadbin(std::istream* is);
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/**
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* Write the whole object to a stream.
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*/
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friend std::ostream& operator<<(std::ostream& o, const FeatureStats& e);
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};
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bool operator==(const FeatureStats& f1, const FeatureStats& f2);
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}
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#endif // MERT_FEATURE_STATS_H_
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