mirror of
https://github.com/moses-smt/mosesdecoder.git
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187 lines
4.6 KiB
C++
187 lines
4.6 KiB
C++
#ifndef __SCORER_H__
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#define __SCORER_H__
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#include <iostream>
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#include <sstream>
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#include <stdexcept>
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#include <string>
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#include <vector>
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#include "Types.h"
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#include "ScoreData.h"
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using namespace std;
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enum ScorerRegularisationStrategy {REG_NONE, REG_AVERAGE, REG_MINIMUM};
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class ScoreStats;
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/**
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* Superclass of all scorers and dummy implementation.
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*
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* In order to add a new scorer it should be sufficient to override the members
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* prepareStats(), setReferenceFiles() and score() (or calculateScore()).
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*/
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class Scorer
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{
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private:
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string _name;
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public:
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Scorer(const string& name, const string& config);
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virtual ~Scorer() {}
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/**
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* Return the number of statistics needed for the computation of the score.
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*/
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virtual size_t NumberOfScores() const {
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cerr << "Scorer: 0" << endl;
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return 0;
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}
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/**
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* Set the reference files. This must be called before prepareStats().
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*/
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virtual void setReferenceFiles(const vector<string>& referenceFiles) {
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//do nothing
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}
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/**
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* Process the given guessed text, corresponding to the given reference sindex
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* and add the appropriate statistics to the entry.
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*/
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virtual void prepareStats(size_t sindex, const string& text, ScoreStats& entry)
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{}
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virtual void prepareStats(const string& sindex, const string& text, ScoreStats& entry) {
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// cerr << sindex << endl;
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this->prepareStats(static_cast<size_t>(atoi(sindex.c_str())), text, entry);
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//cerr << text << std::endl;
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}
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/**
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* Score using each of the candidate index, then go through the diffs
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* applying each in turn, and calculating a new score each time.
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*/
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virtual void score(const candidates_t& candidates, const diffs_t& diffs,
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statscores_t& scores) const {
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//dummy impl
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if (!_scoreData) {
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throw runtime_error("score data not loaded");
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}
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scores.push_back(0);
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for (size_t i = 0; i < diffs.size(); ++i) {
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scores.push_back(0);
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}
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}
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/**
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* Calculate the score of the sentences corresponding to the list of candidate
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* indices. Each index indicates the 1-best choice from the n-best list.
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*/
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float score(const candidates_t& candidates) const {
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diffs_t diffs;
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statscores_t scores;
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score(candidates, diffs, scores);
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return scores[0];
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}
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const string& getName() const {
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return _name;
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}
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size_t getReferenceSize() const {
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if (_scoreData) {
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return _scoreData->size();
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}
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return 0;
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}
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/**
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* Set the score data, prior to scoring.
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*/
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void setScoreData(ScoreData* data) {
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_scoreData = data;
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}
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protected:
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typedef map<string,int> encodings_t;
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typedef map<string,int>::iterator encodings_it;
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ScoreData* _scoreData;
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encodings_t _encodings;
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bool _preserveCase;
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/**
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* Get value of config variable. If not provided, return default.
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*/
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string getConfig(const string& key, const string& def="") const {
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map<string,string>::const_iterator i = _config.find(key);
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if (i == _config.end()) {
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return def;
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} else {
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return i->second;
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}
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}
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/**
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* Tokenise line and encode.
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* Note: We assume that all tokens are separated by single spaces.
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*/
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void encode(const string& line, vector<int>& encoded) {
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//cerr << line << endl;
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istringstream in (line);
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string token;
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while (in >> token) {
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if (!_preserveCase) {
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for (string::iterator i = token.begin(); i != token.end(); ++i) {
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*i = tolower(*i);
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}
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}
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encodings_it encoding = _encodings.find(token);
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int encoded_token;
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if (encoding == _encodings.end()) {
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encoded_token = static_cast<int>(_encodings.size());
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_encodings[token] = encoded_token;
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//cerr << encoded_token << "(n) ";
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} else {
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encoded_token = encoding->second;
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//cerr << encoded_token << " ";
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}
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encoded.push_back(encoded_token);
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}
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//cerr << endl;
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}
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private:
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map<string,string> _config;
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};
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/**
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* Abstract base class for Scorers that work by adding statistics across all
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* outout sentences, then apply some formula, e.g., BLEU, PER.
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*/
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class StatisticsBasedScorer : public Scorer
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{
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public:
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StatisticsBasedScorer(const string& name, const string& config);
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virtual ~StatisticsBasedScorer() {}
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virtual void score(const candidates_t& candidates, const diffs_t& diffs,
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statscores_t& scores) const;
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protected:
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/**
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* Calculate the actual score.
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*/
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virtual statscore_t calculateScore(const vector<int>& totals) const = 0;
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// regularisation
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ScorerRegularisationStrategy _regularisationStrategy;
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size_t _regularisationWindow;
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};
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#endif // __SCORER_H__
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