mosesdecoder/mert/BleuScorerTest.cpp
Barry Haddow 9ca364fb22 Implement brevity penalty smoothing for PRO
As in Nakov et al (Coling 2012)
2013-02-18 11:11:20 +00:00

277 lines
7.9 KiB
C++

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