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https://github.com/moses-smt/mosesdecoder.git
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Move implementation details from the header to .cpp file.
Also add const to variables that we don't want to change.
This commit is contained in:
Tetsuo Kiso
parent
cccfb9a0c9
commit
96f7b42eb9
@ -6,17 +6,61 @@
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// Copyright 2012 __MyCompanyName__. All rights reserved.
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//
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#include <iostream>
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#include "SentenceLevelScorer.h"
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#include <iostream>
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#include <boost/spirit/home/support/detail/lexer/runtime_error.hpp>
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using namespace std;
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namespace MosesTuning
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{
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/** The sentence level scores have already been calculated, just need to average them
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and include the differences. Allows scores which are floats **/
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SentenceLevelScorer::SentenceLevelScorer(const string& name, const string& config)
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: Scorer(name, config),
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m_regularisationStrategy(REG_NONE),
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m_regularisationWindow(0) {
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Init();
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}
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SentenceLevelScorer::~SentenceLevelScorer() {}
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void SentenceLevelScorer::Init() {
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// Configure regularisation.
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static string KEY_TYPE = "regtype";
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static string KEY_WINDOW = "regwin";
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static string KEY_CASE = "case";
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static string TYPE_NONE = "none";
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static string TYPE_AVERAGE = "average";
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static string TYPE_MINIMUM = "min";
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static string TRUE = "true";
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static string FALSE = "false";
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const string type = getConfig(KEY_TYPE, TYPE_NONE);
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if (type == TYPE_NONE) {
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m_regularisationStrategy = REG_NONE;
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} else if (type == TYPE_AVERAGE) {
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m_regularisationStrategy = REG_AVERAGE;
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} else if (type == TYPE_MINIMUM) {
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m_regularisationStrategy = REG_MINIMUM;
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} else {
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throw boost::lexer::runtime_error("Unknown scorer regularisation strategy: " + type);
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}
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cerr << "Using scorer regularisation strategy: " << type << endl;
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const string window = getConfig(KEY_WINDOW, "0");
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m_regularisationWindow = atoi(window.c_str());
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cerr << "Using scorer regularisation window: " << m_regularisationWindow << endl;
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const string preservecase = getConfig(KEY_CASE, TRUE);
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if (preservecase == TRUE) {
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m_enable_preserve_case = true;
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} else if (preservecase == FALSE) {
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m_enable_preserve_case = false;
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}
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cerr << "Using case preservation: " << m_enable_preserve_case << endl;
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}
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void SentenceLevelScorer::score(const candidates_t& candidates, const diffs_t& diffs,
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statscores_t& scores)
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{
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@ -31,7 +75,7 @@ void SentenceLevelScorer::score(const candidates_t& candidates, const diffs_t&
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if (candidates.size() == 0) {
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throw runtime_error("No candidates supplied");
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}
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int numCounts = m_score_data->get(0,candidates[0]).size();
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const int numCounts = m_score_data->get(0,candidates[0]).size();
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vector<float> totals(numCounts);
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for (size_t i = 0; i < candidates.size(); ++i) {
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//cout << " i " << i << " candi " << candidates[i] ;
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@ -57,21 +101,21 @@ void SentenceLevelScorer::score(const candidates_t& candidates, const diffs_t&
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totals[k] /= candidates.size();
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//cout << "finaltotals = " << totals[k] << endl;
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}
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scores.push_back(calculateScore(totals));
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candidates_t last_candidates(candidates);
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//apply each of the diffs, and get new scores
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for (size_t i = 0; i < diffs.size(); ++i) {
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for (size_t j = 0; j < diffs[i].size(); ++j) {
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size_t sid = diffs[i][j].first;
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size_t nid = diffs[i][j].second;
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const size_t sid = diffs[i][j].first;
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const size_t nid = diffs[i][j].second;
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//cout << "sid = " << sid << endl;
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//cout << "nid = " << nid << endl;
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size_t last_nid = last_candidates[sid];
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const size_t last_nid = last_candidates[sid];
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for (size_t k = 0; k < totals.size(); ++k) {
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float diff = m_score_data->get(sid,nid).get(k)
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- m_score_data->get(sid,last_nid).get(k);
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const float diff = m_score_data->get(sid,nid).get(k)
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- m_score_data->get(sid,last_nid).get(k);
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//cout << "diff = " << diff << endl;
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totals[k] += diff/candidates.size();
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//cout << "totals = " << totals[k] << endl;
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@ -80,29 +124,28 @@ void SentenceLevelScorer::score(const candidates_t& candidates, const diffs_t&
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}
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scores.push_back(calculateScore(totals));
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}
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//regularisation. This can either be none, or the min or average as described in
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//Cer, Jurafsky and Manning at WMT08
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if (_regularisationStrategy == REG_NONE || _regularisationWindow <= 0) {
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if (m_regularisationStrategy == REG_NONE || m_regularisationWindow <= 0) {
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//no regularisation
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return;
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}
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//window size specifies the +/- in each direction
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statscores_t raw_scores(scores);//copy scores
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for (size_t i = 0; i < scores.size(); ++i) {
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size_t start = 0;
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if (i >= _regularisationWindow) {
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start = i - _regularisationWindow;
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if (i >= m_regularisationWindow) {
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start = i - m_regularisationWindow;
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}
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size_t end = min(scores.size(), i + _regularisationWindow+1);
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if (_regularisationStrategy == REG_AVERAGE) {
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scores[i] = score_average(raw_scores,start,end);
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const size_t end = min(scores.size(), i + m_regularisationWindow+1);
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if (m_regularisationStrategy == REG_AVERAGE) {
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scores[i] = score_average(raw_scores, start, end);
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} else {
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scores[i] = score_min(raw_scores,start,end);
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scores[i] = score_min(raw_scores, start, end);
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}
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}
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}
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}
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@ -12,77 +12,37 @@
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#include "Scorer.h"
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#include <string>
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#include <vector>
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#include <vector>
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#include <boost/spirit/home/support/detail/lexer/runtime_error.hpp>
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namespace MosesTuning
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{
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/**
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* Abstract base class for scorers that work by using sentence level
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* statistics eg. permutation distance metrics **/
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* statistics (e.g., permutation distance metrics). **/
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class SentenceLevelScorer : public Scorer
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{
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public:
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SentenceLevelScorer(const std::string& name, const std::string& config): Scorer(name,config) {
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//configure regularisation
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static std::string KEY_TYPE = "regtype";
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static std::string KEY_WINDOW = "regwin";
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static std::string KEY_CASE = "case";
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static std::string TYPE_NONE = "none";
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static std::string TYPE_AVERAGE = "average";
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static std::string TYPE_MINIMUM = "min";
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static std::string TRUE = "true";
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static std::string FALSE = "false";
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std::string type = getConfig(KEY_TYPE,TYPE_NONE);
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if (type == TYPE_NONE) {
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_regularisationStrategy = REG_NONE;
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} else if (type == TYPE_AVERAGE) {
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_regularisationStrategy = REG_AVERAGE;
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} else if (type == TYPE_MINIMUM) {
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_regularisationStrategy = REG_MINIMUM;
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} else {
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throw boost::lexer::runtime_error("Unknown scorer regularisation strategy: " + type);
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}
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std::cerr << "Using scorer regularisation strategy: " << type << std::endl;
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std::string window = getConfig(KEY_WINDOW,"0");
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_regularisationWindow = atoi(window.c_str());
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std::cerr << "Using scorer regularisation window: " << _regularisationWindow << std::endl;
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std::string preservecase = getConfig(KEY_CASE,TRUE);
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if (preservecase == TRUE) {
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m_enable_preserve_case = true;
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} else if (preservecase == FALSE) {
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m_enable_preserve_case = false;
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}
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std::cerr << "Using case preservation: " << m_enable_preserve_case << std::endl;
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}
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~SentenceLevelScorer() {};
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SentenceLevelScorer(const std::string& name, const std::string& config);
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~SentenceLevelScorer();
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/** The sentence level scores have already been calculated, just need to average them
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and include the differences. Allows scores which are floats. **/
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virtual void score(const candidates_t& candidates, const diffs_t& diffs,
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statscores_t& scores);
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//calculate the actual score
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virtual statscore_t calculateScore(const std::vector<statscore_t>& totals) {
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// calculate the actual score *
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virtual statscore_t calculateScore(const std::vector<statscore_t>& totals) const {
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return 0;
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};
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}
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protected:
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// Set up regularisation parameters.
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void Init();
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//regularisation
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ScorerRegularisationStrategy _regularisationStrategy;
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size_t _regularisationWindow;
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ScorerRegularisationStrategy m_regularisationStrategy;
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size_t m_regularisationWindow;
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};
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}
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#endif
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