mirror of
https://github.com/moses-smt/mosesdecoder.git
synced 2024-12-27 14:05:29 +03:00
9ca364fb22
As in Nakov et al (Coling 2012)
277 lines
7.9 KiB
C++
277 lines
7.9 KiB
C++
#include "BleuScorer.h"
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#define BOOST_TEST_MODULE MertBleuScorer
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#include <boost/test/unit_test.hpp>
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#include <cmath>
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#include "Ngram.h"
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#include "Vocabulary.h"
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#include "Util.h"
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using namespace MosesTuning;
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namespace {
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NgramCounts* g_counts = NULL;
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NgramCounts* GetNgramCounts() {
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assert(g_counts);
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return g_counts;
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}
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void SetNgramCounts(NgramCounts* counts) {
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g_counts = counts;
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}
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struct Unigram {
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Unigram(const std::string& a) {
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(a));
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}
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NgramCounts::Key instance;
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};
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struct Bigram {
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Bigram(const std::string& a, const std::string& b) {
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(a));
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(b));
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}
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NgramCounts::Key instance;
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};
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struct Trigram {
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Trigram(const std::string& a, const std::string& b, const std::string& c) {
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(a));
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(b));
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(c));
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}
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NgramCounts::Key instance;
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};
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struct Fourgram {
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Fourgram(const std::string& a, const std::string& b,
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const std::string& c, const std::string& d) {
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(a));
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(b));
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(c));
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instance.push_back(mert::VocabularyFactory::GetVocabulary()->Encode(d));
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}
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NgramCounts::Key instance;
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};
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bool CheckUnigram(const std::string& str) {
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Unigram unigram(str);
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NgramCounts::Value v;
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return GetNgramCounts()->Lookup(unigram.instance, &v);
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}
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bool CheckBigram(const std::string& a, const std::string& b) {
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Bigram bigram(a, b);
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NgramCounts::Value v;
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return GetNgramCounts()->Lookup(bigram.instance, &v);
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}
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bool CheckTrigram(const std::string& a, const std::string& b,
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const std::string& c) {
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Trigram trigram(a, b, c);
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NgramCounts::Value v;
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return GetNgramCounts()->Lookup(trigram.instance, &v);
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}
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bool CheckFourgram(const std::string& a, const std::string& b,
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const std::string& c, const std::string& d) {
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Fourgram fourgram(a, b, c, d);
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NgramCounts::Value v;
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return GetNgramCounts()->Lookup(fourgram.instance, &v);
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}
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void SetUpReferences(BleuScorer& scorer) {
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// The following examples are taken from Koehn, "Statistical Machine Translation",
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// Cambridge University Press, 2010.
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{
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std::stringstream ref1;
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ref1 << "israeli officials are responsible for airport security" << std::endl;
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BOOST_CHECK(scorer.OpenReferenceStream(&ref1, 0));
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}
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{
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std::stringstream ref2;
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ref2 << "israel is in charge of the security at this airport" << std::endl;
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BOOST_CHECK(scorer.OpenReferenceStream(&ref2, 1));
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}
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{
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std::stringstream ref3;
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ref3 << "the security work for this airport is the responsibility of the israel government"
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<< std::endl;
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BOOST_CHECK(scorer.OpenReferenceStream(&ref3, 2));
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}
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{
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std::stringstream ref4;
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ref4 << "israli side was in charge of the security of this airport" << std::endl;
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BOOST_CHECK(scorer.OpenReferenceStream(&ref4, 3));
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}
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}
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} // namespace
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BOOST_AUTO_TEST_CASE(bleu_reference_type) {
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BleuScorer scorer;
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// BleuScorer will use "closest" by default.
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BOOST_CHECK_EQUAL(scorer.GetReferenceLengthType(), BleuScorer::CLOSEST);
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scorer.SetReferenceLengthType(BleuScorer::AVERAGE);
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BOOST_CHECK_EQUAL(scorer.GetReferenceLengthType(), BleuScorer::AVERAGE);
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scorer.SetReferenceLengthType(BleuScorer::SHORTEST);
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BOOST_CHECK_EQUAL(scorer.GetReferenceLengthType(), BleuScorer::SHORTEST);
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}
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BOOST_AUTO_TEST_CASE(bleu_reference_type_with_config) {
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{
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BleuScorer scorer("reflen:average");
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BOOST_CHECK_EQUAL(scorer.GetReferenceLengthType(), BleuScorer::AVERAGE);
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}
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{
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BleuScorer scorer("reflen:shortest");
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BOOST_CHECK_EQUAL(scorer.GetReferenceLengthType(), BleuScorer::SHORTEST);
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}
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}
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BOOST_AUTO_TEST_CASE(bleu_count_ngrams) {
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BleuScorer scorer;
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std::string line = "I saw a girl with a telescope .";
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// In the above string, we will get the 25 ngrams.
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//
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// unigram: "I", "saw", "a", "girl", "with", "telescope", "."
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// bigram: "I saw", "saw a", "a girl", "girl with", "with a", "a telescope"
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// "telescope ."
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// trigram: "I saw a", "saw a girl", "a girl with", "girl with a",
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// "with a telescope", "a telescope ."
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// 4-gram: "I saw a girl", "saw a girl with", "a girl with a",
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// "girl with a telescope", "with a telescope ."
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NgramCounts counts;
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BOOST_REQUIRE(scorer.CountNgrams(line, counts, kBleuNgramOrder) == 8);
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BOOST_CHECK_EQUAL((std::size_t)25, counts.size());
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mert::Vocabulary* vocab = scorer.GetVocab();
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BOOST_CHECK_EQUAL((std::size_t)7, vocab->size());
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std::vector<std::string> res;
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Tokenize(line.c_str(), ' ', &res);
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std::vector<int> ids(res.size());
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for (std::size_t i = 0; i < res.size(); ++i) {
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BOOST_CHECK(vocab->Lookup(res[i], &ids[i]));
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}
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SetNgramCounts(&counts);
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// unigram
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for (std::size_t i = 0; i < res.size(); ++i) {
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BOOST_CHECK(CheckUnigram(res[i]));
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}
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// bigram
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BOOST_CHECK(CheckBigram("I", "saw"));
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BOOST_CHECK(CheckBigram("saw", "a"));
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BOOST_CHECK(CheckBigram("a", "girl"));
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BOOST_CHECK(CheckBigram("girl", "with"));
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BOOST_CHECK(CheckBigram("with", "a"));
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BOOST_CHECK(CheckBigram("a", "telescope"));
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BOOST_CHECK(CheckBigram("telescope", "."));
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// trigram
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BOOST_CHECK(CheckTrigram("I", "saw", "a"));
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BOOST_CHECK(CheckTrigram("saw", "a", "girl"));
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BOOST_CHECK(CheckTrigram("a", "girl", "with"));
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BOOST_CHECK(CheckTrigram("girl", "with", "a"));
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BOOST_CHECK(CheckTrigram("with", "a", "telescope"));
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BOOST_CHECK(CheckTrigram("a", "telescope", "."));
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// 4-gram
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BOOST_CHECK(CheckFourgram("I", "saw", "a", "girl"));
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BOOST_CHECK(CheckFourgram("saw", "a", "girl", "with"));
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BOOST_CHECK(CheckFourgram("a", "girl", "with", "a"));
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BOOST_CHECK(CheckFourgram("girl", "with", "a", "telescope"));
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BOOST_CHECK(CheckFourgram("with", "a", "telescope", "."));
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}
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BOOST_AUTO_TEST_CASE(bleu_clipped_counts) {
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BleuScorer scorer;
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SetUpReferences(scorer);
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std::string line("israeli officials responsibility of airport safety");
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ScoreStats entry;
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scorer.prepareStats(0, line, entry);
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BOOST_CHECK_EQUAL(entry.size(), (std::size_t)(2 * kBleuNgramOrder + 1));
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// Test hypothesis ngram counts
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BOOST_CHECK_EQUAL(entry.get(0), 5); // unigram
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BOOST_CHECK_EQUAL(entry.get(2), 2); // bigram
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BOOST_CHECK_EQUAL(entry.get(4), 0); // trigram
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BOOST_CHECK_EQUAL(entry.get(6), 0); // fourgram
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// Test reference ngram counts.
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BOOST_CHECK_EQUAL(entry.get(1), 6); // unigram
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BOOST_CHECK_EQUAL(entry.get(3), 5); // bigram
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BOOST_CHECK_EQUAL(entry.get(5), 4); // trigram
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BOOST_CHECK_EQUAL(entry.get(7), 3); // fourgram
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}
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BOOST_AUTO_TEST_CASE(calculate_actual_score) {
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BOOST_REQUIRE(4 == kBleuNgramOrder);
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std::vector<int> stats(2 * kBleuNgramOrder + 1);
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BleuScorer scorer;
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// unigram
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stats[0] = 6;
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stats[1] = 6;
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// bigram
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stats[2] = 4;
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stats[3] = 5;
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// trigram
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stats[4] = 2;
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stats[5] = 4;
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// fourgram
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stats[6] = 1;
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stats[7] = 3;
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// reference-length
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stats[8] = 7;
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BOOST_CHECK_CLOSE(0.5115f, scorer.calculateScore(stats), 0.01);
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}
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BOOST_AUTO_TEST_CASE(sentence_level_bleu) {
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BOOST_REQUIRE(4 == kBleuNgramOrder);
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std::vector<float> stats(2 * kBleuNgramOrder + 1);
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// unigram
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stats[0] = 6.0;
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stats[1] = 6.0;
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// bigram
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stats[2] = 4.0;
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stats[3] = 5.0;
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// trigram
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stats[4] = 2.0;
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stats[5] = 4.0;
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// fourgram
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stats[6] = 1.0;
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stats[7] = 3.0;
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// reference-length
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stats[8] = 7.0;
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BOOST_CHECK_CLOSE(0.5985f, smoothedSentenceBleu(stats), 0.01);
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BOOST_CHECK_CLOSE(0.5624f, smoothedSentenceBleu(stats, 0.5), 0.01 );
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BOOST_CHECK_CLOSE(0.5067f, smoothedSentenceBleu(stats, 1.0, true), 0.01);
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}
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