mosesdecoder/lm/model_test.cc
2012-06-28 10:58:59 -04:00

436 lines
14 KiB
C++

#include "lm/model.hh"
#include <stdlib.h>
#define BOOST_TEST_MODULE ModelTest
#include <boost/test/unit_test.hpp>
#include <boost/test/floating_point_comparison.hpp>
namespace lm {
namespace ngram {
std::ostream &operator<<(std::ostream &o, const State &state) {
o << "State length " << static_cast<unsigned int>(state.length) << ':';
for (const WordIndex *i = state.words; i < state.words + state.length; ++i) {
o << ' ' << *i;
}
return o;
}
namespace {
const char *TestLocation() {
if (boost::unit_test::framework::master_test_suite().argc < 2) {
return "test.arpa";
}
return boost::unit_test::framework::master_test_suite().argv[1];
}
const char *TestNoUnkLocation() {
if (boost::unit_test::framework::master_test_suite().argc < 3) {
return "test_nounk.arpa";
}
return boost::unit_test::framework::master_test_suite().argv[2];
}
template <class Model> State GetState(const Model &model, const char *word, const State &in) {
WordIndex context[in.length + 1];
context[0] = model.GetVocabulary().Index(word);
std::copy(in.words, in.words + in.length, context + 1);
State ret;
model.GetState(context, context + in.length + 1, ret);
return ret;
}
#define StartTest(word, ngram, score, indep_left) \
ret = model.FullScore( \
state, \
model.GetVocabulary().Index(word), \
out);\
BOOST_CHECK_CLOSE(score, ret.prob, 0.001); \
BOOST_CHECK_EQUAL(static_cast<unsigned int>(ngram), ret.ngram_length); \
BOOST_CHECK_GE(std::min<unsigned char>(ngram, 5 - 1), out.length); \
BOOST_CHECK_EQUAL(indep_left, ret.independent_left); \
BOOST_CHECK_EQUAL(out, GetState(model, word, state));
#define AppendTest(word, ngram, score, indep_left) \
StartTest(word, ngram, score, indep_left) \
state = out;
template <class M> void Starters(const M &model) {
FullScoreReturn ret;
Model::State state(model.BeginSentenceState());
Model::State out;
StartTest("looking", 2, -0.4846522, true);
// , probability plus <s> backoff
StartTest(",", 1, -1.383514 + -0.4149733, true);
// <unk> probability plus <s> backoff
StartTest("this_is_not_found", 1, -1.995635 + -0.4149733, true);
}
template <class M> void Continuation(const M &model) {
FullScoreReturn ret;
Model::State state(model.BeginSentenceState());
Model::State out;
AppendTest("looking", 2, -0.484652, true);
AppendTest("on", 3, -0.348837, true);
AppendTest("a", 4, -0.0155266, true);
AppendTest("little", 5, -0.00306122, true);
State preserve = state;
AppendTest("the", 1, -4.04005, true);
AppendTest("biarritz", 1, -1.9889, true);
AppendTest("not_found", 1, -2.29666, true);
AppendTest("more", 1, -1.20632 - 20.0, true);
AppendTest(".", 2, -0.51363, true);
AppendTest("</s>", 3, -0.0191651, true);
BOOST_CHECK_EQUAL(0, state.length);
state = preserve;
AppendTest("more", 5, -0.00181395, true);
BOOST_CHECK_EQUAL(4, state.length);
AppendTest("loin", 5, -0.0432557, true);
BOOST_CHECK_EQUAL(1, state.length);
}
template <class M> void Blanks(const M &model) {
FullScoreReturn ret;
State state(model.NullContextState());
State out;
AppendTest("also", 1, -1.687872, false);
AppendTest("would", 2, -2, true);
AppendTest("consider", 3, -3, true);
State preserve = state;
AppendTest("higher", 4, -4, true);
AppendTest("looking", 5, -5, true);
BOOST_CHECK_EQUAL(1, state.length);
state = preserve;
// also would consider not_found
AppendTest("not_found", 1, -1.995635 - 7.0 - 0.30103, true);
state = model.NullContextState();
// higher looking is a blank.
AppendTest("higher", 1, -1.509559, false);
AppendTest("looking", 2, -1.285941 - 0.30103, false);
State higher_looking = state;
BOOST_CHECK_EQUAL(1, state.length);
AppendTest("not_found", 1, -1.995635 - 0.4771212, true);
state = higher_looking;
// higher looking consider
AppendTest("consider", 1, -1.687872 - 0.4771212, true);
state = model.NullContextState();
AppendTest("would", 1, -1.687872, false);
BOOST_CHECK_EQUAL(1, state.length);
AppendTest("consider", 2, -1.687872 -0.30103, false);
BOOST_CHECK_EQUAL(2, state.length);
AppendTest("higher", 3, -1.509559 - 0.30103, false);
BOOST_CHECK_EQUAL(3, state.length);
AppendTest("looking", 4, -1.285941 - 0.30103, false);
}
template <class M> void Unknowns(const M &model) {
FullScoreReturn ret;
State state(model.NullContextState());
State out;
AppendTest("not_found", 1, -1.995635, false);
State preserve = state;
AppendTest("not_found2", 2, -15.0, true);
AppendTest("not_found3", 2, -15.0 - 2.0, true);
state = preserve;
AppendTest("however", 2, -4, true);
AppendTest("not_found3", 3, -6, true);
}
template <class M> void MinimalState(const M &model) {
FullScoreReturn ret;
State state(model.NullContextState());
State out;
AppendTest("baz", 1, -6.535897, true);
BOOST_CHECK_EQUAL(0, state.length);
state = model.NullContextState();
AppendTest("foo", 1, -3.141592, true);
BOOST_CHECK_EQUAL(1, state.length);
AppendTest("bar", 2, -6.0, true);
// Has to include the backoff weight.
BOOST_CHECK_EQUAL(1, state.length);
AppendTest("bar", 1, -2.718281 + 3.0, true);
BOOST_CHECK_EQUAL(1, state.length);
state = model.NullContextState();
AppendTest("to", 1, -1.687872, false);
AppendTest("look", 2, -0.2922095, true);
BOOST_CHECK_EQUAL(2, state.length);
AppendTest("good", 3, -7, true);
}
template <class M> void ExtendLeftTest(const M &model) {
State right;
FullScoreReturn little(model.FullScore(model.NullContextState(), model.GetVocabulary().Index("little"), right));
const float kLittleProb = -1.285941;
BOOST_CHECK_CLOSE(kLittleProb, little.prob, 0.001);
unsigned char next_use;
float backoff_out[4];
FullScoreReturn extend_none(model.ExtendLeft(NULL, NULL, NULL, little.extend_left, 1, NULL, next_use));
BOOST_CHECK_EQUAL(0, next_use);
BOOST_CHECK_EQUAL(little.extend_left, extend_none.extend_left);
BOOST_CHECK_CLOSE(little.prob - little.rest, extend_none.prob, 0.001);
BOOST_CHECK_EQUAL(1, extend_none.ngram_length);
const WordIndex a = model.GetVocabulary().Index("a");
float backoff_in = 3.14;
// a little
FullScoreReturn extend_a(model.ExtendLeft(&a, &a + 1, &backoff_in, little.extend_left, 1, backoff_out, next_use));
BOOST_CHECK_EQUAL(1, next_use);
BOOST_CHECK_CLOSE(-0.69897, backoff_out[0], 0.001);
BOOST_CHECK_CLOSE(-0.09132547 - little.rest, extend_a.prob, 0.001);
BOOST_CHECK_EQUAL(2, extend_a.ngram_length);
BOOST_CHECK(!extend_a.independent_left);
const WordIndex on = model.GetVocabulary().Index("on");
FullScoreReturn extend_on(model.ExtendLeft(&on, &on + 1, &backoff_in, extend_a.extend_left, 2, backoff_out, next_use));
BOOST_CHECK_EQUAL(1, next_use);
BOOST_CHECK_CLOSE(-0.4771212, backoff_out[0], 0.001);
BOOST_CHECK_CLOSE(-0.0283603 - (extend_a.rest + little.rest), extend_on.prob, 0.001);
BOOST_CHECK_EQUAL(3, extend_on.ngram_length);
BOOST_CHECK(!extend_on.independent_left);
const WordIndex both[2] = {a, on};
float backoff_in_arr[4];
FullScoreReturn extend_both(model.ExtendLeft(both, both + 2, backoff_in_arr, little.extend_left, 1, backoff_out, next_use));
BOOST_CHECK_EQUAL(2, next_use);
BOOST_CHECK_CLOSE(-0.69897, backoff_out[0], 0.001);
BOOST_CHECK_CLOSE(-0.4771212, backoff_out[1], 0.001);
BOOST_CHECK_CLOSE(-0.0283603 - little.rest, extend_both.prob, 0.001);
BOOST_CHECK_EQUAL(3, extend_both.ngram_length);
BOOST_CHECK(!extend_both.independent_left);
BOOST_CHECK_EQUAL(extend_on.extend_left, extend_both.extend_left);
}
#define StatelessTest(word, provide, ngram, score) \
ret = model.FullScoreForgotState(indices + num_words - word, indices + num_words - word + provide, indices[num_words - word - 1], state); \
BOOST_CHECK_CLOSE(score, ret.prob, 0.001); \
BOOST_CHECK_EQUAL(static_cast<unsigned int>(ngram), ret.ngram_length); \
model.GetState(indices + num_words - word, indices + num_words - word + provide, before); \
ret = model.FullScore(before, indices[num_words - word - 1], out); \
BOOST_CHECK(state == out); \
BOOST_CHECK_CLOSE(score, ret.prob, 0.001); \
BOOST_CHECK_EQUAL(static_cast<unsigned int>(ngram), ret.ngram_length);
template <class M> void Stateless(const M &model) {
const char *words[] = {"<s>", "looking", "on", "a", "little", "the", "biarritz", "not_found", "more", ".", "</s>"};
const size_t num_words = sizeof(words) / sizeof(const char*);
// Silience "array subscript is above array bounds" when extracting end pointer.
WordIndex indices[num_words + 1];
for (unsigned int i = 0; i < num_words; ++i) {
indices[num_words - 1 - i] = model.GetVocabulary().Index(words[i]);
}
FullScoreReturn ret;
State state, out, before;
ret = model.FullScoreForgotState(indices + num_words - 1, indices + num_words, indices[num_words - 2], state);
BOOST_CHECK_CLOSE(-0.484652, ret.prob, 0.001);
StatelessTest(1, 1, 2, -0.484652);
// looking
StatelessTest(1, 2, 2, -0.484652);
// on
AppendTest("on", 3, -0.348837, true);
StatelessTest(2, 3, 3, -0.348837);
StatelessTest(2, 2, 3, -0.348837);
StatelessTest(2, 1, 2, -0.4638903);
// a
StatelessTest(3, 4, 4, -0.0155266);
// little
AppendTest("little", 5, -0.00306122, true);
StatelessTest(4, 5, 5, -0.00306122);
// the
AppendTest("the", 1, -4.04005, true);
StatelessTest(5, 5, 1, -4.04005);
// No context of the.
StatelessTest(5, 0, 1, -1.687872);
// biarritz
StatelessTest(6, 1, 1, -1.9889);
// not found
StatelessTest(7, 1, 1, -2.29666);
StatelessTest(7, 0, 1, -1.995635);
WordIndex unk[1];
unk[0] = 0;
model.GetState(unk, unk + 1, state);
BOOST_CHECK_EQUAL(1, state.length);
BOOST_CHECK_EQUAL(static_cast<WordIndex>(0), state.words[0]);
}
template <class M> void NoUnkCheck(const M &model) {
WordIndex unk_index = 0;
State state;
FullScoreReturn ret = model.FullScoreForgotState(&unk_index, &unk_index + 1, unk_index, state);
BOOST_CHECK_CLOSE(-100.0, ret.prob, 0.001);
}
template <class M> void Everything(const M &m) {
Starters(m);
Continuation(m);
Blanks(m);
Unknowns(m);
MinimalState(m);
ExtendLeftTest(m);
Stateless(m);
}
class ExpectEnumerateVocab : public EnumerateVocab {
public:
ExpectEnumerateVocab() {}
void Add(WordIndex index, const StringPiece &str) {
BOOST_CHECK_EQUAL(seen.size(), index);
seen.push_back(std::string(str.data(), str.length()));
}
void Check(const base::Vocabulary &vocab) {
BOOST_CHECK_EQUAL(37ULL, seen.size());
BOOST_REQUIRE(!seen.empty());
BOOST_CHECK_EQUAL("<unk>", seen[0]);
for (WordIndex i = 0; i < seen.size(); ++i) {
BOOST_CHECK_EQUAL(i, vocab.Index(seen[i]));
}
}
void Clear() {
seen.clear();
}
std::vector<std::string> seen;
};
template <class ModelT> void LoadingTest() {
Config config;
config.arpa_complain = Config::NONE;
config.messages = NULL;
config.probing_multiplier = 2.0;
{
ExpectEnumerateVocab enumerate;
config.enumerate_vocab = &enumerate;
ModelT m(TestLocation(), config);
enumerate.Check(m.GetVocabulary());
BOOST_CHECK_EQUAL((WordIndex)37, m.GetVocabulary().Bound());
Everything(m);
}
{
ExpectEnumerateVocab enumerate;
config.enumerate_vocab = &enumerate;
ModelT m(TestNoUnkLocation(), config);
enumerate.Check(m.GetVocabulary());
BOOST_CHECK_EQUAL((WordIndex)37, m.GetVocabulary().Bound());
NoUnkCheck(m);
}
}
BOOST_AUTO_TEST_CASE(probing) {
LoadingTest<Model>();
}
BOOST_AUTO_TEST_CASE(trie) {
LoadingTest<TrieModel>();
}
BOOST_AUTO_TEST_CASE(quant_trie) {
LoadingTest<QuantTrieModel>();
}
BOOST_AUTO_TEST_CASE(bhiksha_trie) {
LoadingTest<ArrayTrieModel>();
}
BOOST_AUTO_TEST_CASE(quant_bhiksha_trie) {
LoadingTest<QuantArrayTrieModel>();
}
template <class ModelT> void BinaryTest() {
Config config;
config.write_mmap = "test.binary";
config.messages = NULL;
ExpectEnumerateVocab enumerate;
config.enumerate_vocab = &enumerate;
{
ModelT copy_model(TestLocation(), config);
enumerate.Check(copy_model.GetVocabulary());
enumerate.Clear();
Everything(copy_model);
}
config.write_mmap = NULL;
ModelType type;
BOOST_REQUIRE(RecognizeBinary("test.binary", type));
BOOST_CHECK_EQUAL(ModelT::kModelType, type);
{
ModelT binary("test.binary", config);
enumerate.Check(binary.GetVocabulary());
Everything(binary);
}
unlink("test.binary");
// Now test without <unk>.
config.write_mmap = "test_nounk.binary";
config.messages = NULL;
enumerate.Clear();
{
ModelT copy_model(TestNoUnkLocation(), config);
enumerate.Check(copy_model.GetVocabulary());
enumerate.Clear();
NoUnkCheck(copy_model);
}
config.write_mmap = NULL;
{
ModelT binary(TestNoUnkLocation(), config);
enumerate.Check(binary.GetVocabulary());
NoUnkCheck(binary);
}
unlink("test_nounk.binary");
}
BOOST_AUTO_TEST_CASE(write_and_read_probing) {
BinaryTest<ProbingModel>();
}
BOOST_AUTO_TEST_CASE(write_and_read_rest_probing) {
BinaryTest<RestProbingModel>();
}
BOOST_AUTO_TEST_CASE(write_and_read_trie) {
BinaryTest<TrieModel>();
}
BOOST_AUTO_TEST_CASE(write_and_read_quant_trie) {
BinaryTest<QuantTrieModel>();
}
BOOST_AUTO_TEST_CASE(write_and_read_array_trie) {
BinaryTest<ArrayTrieModel>();
}
BOOST_AUTO_TEST_CASE(write_and_read_quant_array_trie) {
BinaryTest<QuantArrayTrieModel>();
}
BOOST_AUTO_TEST_CASE(rest_max) {
Config config;
config.arpa_complain = Config::NONE;
config.messages = NULL;
RestProbingModel model(TestLocation(), config);
State state, out;
FullScoreReturn ret(model.FullScore(model.NullContextState(), model.GetVocabulary().Index("."), state));
BOOST_CHECK_CLOSE(-0.2705918, ret.rest, 0.001);
BOOST_CHECK_CLOSE(-0.01916512, model.FullScore(state, model.GetVocabulary().EndSentence(), out).rest, 0.001);
}
} // namespace
} // namespace ngram
} // namespace lm