mirror of
https://github.com/moses-smt/mosesdecoder.git
synced 2024-08-17 07:20:48 +03:00
143 lines
3.7 KiB
C++
143 lines
3.7 KiB
C++
#include "CderScorer.h"
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#include <algorithm>
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#include <fstream>
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#include <stdexcept>
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using namespace std;
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namespace
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{
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inline int CalcDistance(int word1, int word2)
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{
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return word1 == word2 ? 0 : 1;
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}
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} // namespace
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namespace MosesTuning
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{
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CderScorer::CderScorer(const string& config, bool allowed_long_jumps)
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: StatisticsBasedScorer(allowed_long_jumps ? "CDER" : "WER", config),
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m_allowed_long_jumps(allowed_long_jumps) {}
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CderScorer::~CderScorer() {}
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void CderScorer::setReferenceFiles(const vector<string>& referenceFiles)
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{
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//make sure reference data is clear
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m_ref_sentences.clear();
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//load reference data
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for (size_t rid = 0; rid < referenceFiles.size(); ++rid) {
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ifstream refin(referenceFiles[rid].c_str());
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if (!refin) {
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throw runtime_error("Unable to open: " + referenceFiles[rid]);
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}
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m_ref_sentences.push_back(vector<sent_t>());
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string line;
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while (getline(refin,line)) {
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line = this->preprocessSentence(line);
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sent_t encoded;
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TokenizeAndEncode(line, encoded);
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m_ref_sentences[rid].push_back(encoded);
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}
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}
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}
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void CderScorer::prepareStats(size_t sid, const string& text, ScoreStats& entry)
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{
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string sentence = this->preprocessSentence(text);
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vector<ScoreStatsType> stats;
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prepareStatsVector(sid, sentence, stats);
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entry.set(stats);
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}
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void CderScorer::prepareStatsVector(size_t sid, const string& text, vector<ScoreStatsType>& stats)
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{
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sent_t cand;
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TokenizeAndEncode(text, cand);
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float max = -2;
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vector<ScoreStatsType> tmp;
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for (size_t rid = 0; rid < m_ref_sentences.size(); ++rid) {
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const sent_t& ref = m_ref_sentences[rid][sid];
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tmp.clear();
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computeCD(cand, ref, tmp);
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int score = calculateScore(tmp);
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if (rid == 0) {
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stats = tmp;
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max = score;
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} else if (score > max) {
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stats = tmp;
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max = score;
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}
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}
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}
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float CderScorer::calculateScore(const vector<ScoreStatsType>& comps) const
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{
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if (comps.size() != 2) {
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throw runtime_error("Size of stat vector for CDER is not 2");
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}
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if (comps[1] == 0) return 1.0f;
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return 1.0f - (comps[0] / static_cast<float>(comps[1]));
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}
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void CderScorer::computeCD(const sent_t& cand, const sent_t& ref,
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vector<ScoreStatsType>& stats) const
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{
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int I = cand.size() + 1; // Number of inter-words positions in candidate sentence
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int L = ref.size() + 1; // Number of inter-words positions in reference sentence
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int l = 0;
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// row[i] stores cost of cheapest path from (0,0) to (i,l) in CDER aligment grid.
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vector<int>* row = new vector<int>(I);
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// Initialization of first row
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for (int i = 0; i < I; ++i) (*row)[i] = i;
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// For CDER metric, the initialization is different
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if (m_allowed_long_jumps) {
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for (int i = 1; i < I; ++i) (*row)[i] = 1;
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}
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// Calculating costs for next row using costs from the previous row.
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while (++l < L) {
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vector<int>* nextRow = new vector<int>(I);
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for (int i = 0; i < I; ++i) {
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vector<int> possibleCosts;
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if (i > 0) {
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possibleCosts.push_back((*nextRow)[i-1] + 1); // Deletion
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possibleCosts.push_back((*row)[i-1] + CalcDistance(ref[l-1], cand[i-1])); // Substitution/Identity
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}
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possibleCosts.push_back((*row)[i] + 1); // Insertion
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(*nextRow)[i] = *min_element(possibleCosts.begin(), possibleCosts.end());
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}
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if (m_allowed_long_jumps) {
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// Cost of LongJumps is the same for all in the row
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int LJ = 1 + *min_element(nextRow->begin(), nextRow->end());
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for (int i = 0; i < I; ++i) {
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(*nextRow)[i] = min((*nextRow)[i], LJ); // LongJumps
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}
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}
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delete row;
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row = nextRow;
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}
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stats.resize(2);
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stats[0] = *(row->rbegin()); // CD distance is the cost of path from (0,0) to (I,L)
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stats[1] = ref.size();
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delete row;
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}
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}
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