mirror of
https://github.com/moses-smt/mosesdecoder.git
synced 2024-08-16 15:00:33 +03:00
150 lines
3.9 KiB
C++
150 lines
3.9 KiB
C++
/*
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* FeatureData.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_DATA_H_
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#define MERT_FEATURE_DATA_H_
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#include <vector>
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#include <iostream>
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#include <stdexcept>
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#include <boost/lexical_cast.hpp>
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#include "FeatureArray.h"
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namespace MosesTuning
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{
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class FeatureData
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{
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private:
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std::size_t m_num_features;
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std::string m_features;
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std::map<std::string, std::size_t> m_feature_name_to_index; // map from name to index of features
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std::map<std::size_t, std::string> m_index_to_feature_name; // map from index to name of features
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featdata_t m_array;
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idx2name m_index_to_array_name; // map from index to name of array
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name2idx m_array_name_to_index; // map from name to index of array
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public:
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FeatureData();
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~FeatureData() {}
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void clear() {
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m_array.clear();
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}
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FeatureArray& get(size_t idx) {
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return m_array.at(idx);
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}
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const FeatureArray& get(size_t idx) const {
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return m_array.at(idx);
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}
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inline bool exists(int sent_idx) const {
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return existsInternal(getIndex(sent_idx));
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}
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inline bool existsInternal(int sent_idx) const {
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return (sent_idx > -1 && sent_idx < static_cast<int>(m_array.size())) ? true : false;
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}
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inline FeatureStats& get(std::size_t i, std::size_t j) {
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return m_array.at(i).get(j);
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}
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inline const FeatureStats& get(std::size_t i, std::size_t j) const {
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return m_array.at(i).get(j);
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}
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void add(FeatureArray& e);
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void add(FeatureStats& e, int sent_idx);
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std::size_t size() const {
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return m_array.size();
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}
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std::size_t NumberOfFeatures() const {
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return m_num_features;
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}
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void NumberOfFeatures(std::size_t v) {
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m_num_features = v;
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}
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std::string Features() const {
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return m_features;
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}
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void Features(const std::string& f) {
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m_features = f;
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}
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void save(const std::string &file, bool bin=false);
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void save(std::ostream* os, bool bin=false);
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void save(bool bin=false);
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void load(std::istream* is, const SparseVector& sparseWeights);
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void load(const std::string &file, const SparseVector& sparseWeights);
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bool check_consistency() const;
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void setIndex();
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inline int getIndex(int idx) const {
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name2idx::const_iterator i = m_array_name_to_index.find(idx);
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if (i != m_array_name_to_index.end())
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return i->second;
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else
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return -1;
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}
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inline int getName(std::size_t idx) const {
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idx2name::const_iterator i = m_index_to_array_name.find(idx);
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if (i != m_index_to_array_name.end())
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throw std::runtime_error("there is no entry at index " + boost::lexical_cast<std::string>(idx));
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return i->second;
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}
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bool existsFeatureNames() const {
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return (m_index_to_feature_name.size() > 0) ? true : false;
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}
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std::string getFeatureName(std::size_t idx) const {
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if (idx >= m_index_to_feature_name.size())
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throw std::runtime_error("Error: you required an too big index");
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std::map<std::size_t, std::string>::const_iterator it = m_index_to_feature_name.find(idx);
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if (it == m_index_to_feature_name.end()) {
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throw std::runtime_error("Error: specified id is unknown: " + boost::lexical_cast<std::string>(idx));
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} else {
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return it->second;
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}
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}
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std::size_t getFeatureIndex(const std::string& name) const {
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std::map<std::string, std::size_t>::const_iterator it = m_feature_name_to_index.find(name);
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if (it == m_feature_name_to_index.end()) {
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std::string msg = "Error: feature " + name + " is unknown. Known features: ";
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for (std::map<std::string, std::size_t>::const_iterator cit = m_feature_name_to_index.begin();
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cit != m_feature_name_to_index.end(); cit++) {
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msg += cit->first;
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msg += ", ";
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}
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throw std::runtime_error(msg);
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}
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return it->second;
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}
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void setFeatureMap(const std::string& feat);
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/* For debugging */
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std::string ToString() const;
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};
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}
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#endif // MERT_FEATURE_DATA_H_
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