mirror of
https://github.com/moses-smt/mosesdecoder.git
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4ee8f2dec1
Don't load all references, read them line by line. Corpora with millions of sentences can now be evaluated without consuming gigabytes of RAM.
66 lines
1.7 KiB
C++
66 lines
1.7 KiB
C++
#pragma once
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#include <ostream>
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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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#include "StatisticsBasedScorer.h"
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#include "ScopedVector.h"
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#include "BleuScorer.h"
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namespace MosesTuning
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{
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/**
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* Bleu document scoring
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*
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* Needs xml reference files, and nbest lists where sentences are separated by '\n'
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*/
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class BleuDocScorer : public BleuScorer
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{
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public:
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explicit BleuDocScorer(const std::string& config = "");
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~BleuDocScorer();
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virtual void prepareStats(std::size_t sid, const std::string& text, ScoreStats& entry);
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virtual statscore_t calculateScore(const std::vector<int>& comps) const;
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int CalcReferenceLength(std::size_t doc_id, std::size_t sentence_id, std::size_t length);
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// NOTE: this function is used for unit testing.
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virtual bool OpenReferenceStream(std::istream* is, std::size_t file_id);
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private:
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ReferenceLengthType m_ref_length_type;
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// reference translations.
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ScopedVector<ScopedVector<Reference> > m_references;
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// no copying allowed
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BleuDocScorer(const BleuDocScorer&);
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BleuDocScorer& operator=(const BleuDocScorer&);
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std::vector<std::string> splitDoc(const std::string& text);
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};
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/* /\** Computes sentence-level BLEU+1 score. */
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/* * This function is used in PRO. */
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/* *\/ */
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/* float sentenceLevelBleuPlusOne(const std::vector<float>& stats); */
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/* /\** Computes sentence-level BLEU score given a background corpus. */
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/* * This function is used in batch MIRA. */
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/* *\/ */
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/* float sentenceLevelBackgroundBleu(const std::vector<float>& sent, const std::vector<float>& bg); */
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/* /\** */
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/* * Computes plain old BLEU from a vector of stats */
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/* *\/ */
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/* float unsmoothedBleu(const std::vector<float>& stats); */
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}
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