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#include "lm/model.hh"
#include <stdlib.h>
#define BOOST_TEST_MODULE ModelTest
#include <boost/test/unit_test.hpp>
namespace lm {
namespace ngram {
namespace {
#define StartTest(word, ngram, score) \
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_EQUAL(std::min<unsigned char>(ngram, 5 - 1), out.valid_length_);
#define AppendTest(word, ngram, score) \
StartTest(word, ngram, score) \
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);
// , probability plus <s> backoff
StartTest(",", 1, -1.383514 + -0.4149733);
// <unk> probability plus <s> backoff
StartTest("this_is_not_found", 0, -1.995635 + -0.4149733);
}
template <class M> void Continuation(const M &model) {
FullScoreReturn ret;
Model::State state(model.BeginSentenceState());
Model::State out;
AppendTest("looking", 2, -0.484652);
AppendTest("on", 3, -0.348837);
AppendTest("a", 4, -0.0155266);
AppendTest("little", 5, -0.00306122);
State preserve = state;
AppendTest("the", 1, -4.04005);
AppendTest("biarritz", 1, -1.9889);
AppendTest("not_found", 0, -2.29666);
AppendTest("more", 1, -1.20632);
AppendTest(".", 2, -0.51363);
AppendTest("</s>", 3, -0.0191651);
state = preserve;
AppendTest("more", 5, -0.00181395);
AppendTest("loin", 5, -0.0432557);
}
#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);
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);
StatelessTest(4, 5, 5, -0.00306122);
// the
AppendTest("the", 1, -4.04005);
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, 0, -2.29666);
StatelessTest(7, 0, 0, -1.995635);
WordIndex unk[1];
unk[0] = 0;
model.GetState(unk, unk + 1, state);
BOOST_CHECK_EQUAL(0, state.valid_length_);
}
//const char *kExpectedOrderProbing[] = {"<unk>", ",", ".", "</s>", "<s>", "a", "also", "beyond", "biarritz", "call", "concerns", "consider", "considering", "for", "higher", "however", "i", "immediate", "in", "is", "little", "loin", "look", "looking", "more", "on", "screening", "small", "the", "to", "watch", "watching", "what", "would"};
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(34, 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;
ExpectEnumerateVocab enumerate;
config.enumerate_vocab = &enumerate;
ModelT m("test.arpa", config);
enumerate.Check(m.GetVocabulary());
Starters(m);
Continuation(m);
Stateless(m);
}
BOOST_AUTO_TEST_CASE(probing) {
LoadingTest<Model>();
}
BOOST_AUTO_TEST_CASE(sorted) {
LoadingTest<SortedModel>();
}
BOOST_AUTO_TEST_CASE(trie) {
LoadingTest<TrieModel>();
}
template <class ModelT> void BinaryTest() {
Config config;
config.write_mmap = "test.binary";
config.messages = NULL;
ExpectEnumerateVocab enumerate;
config.enumerate_vocab = &enumerate;
{
ModelT copy_model("test.arpa", config);
enumerate.Check(copy_model.GetVocabulary());
enumerate.Clear();
}
config.write_mmap = NULL;
ModelT binary("test.binary", config);
enumerate.Check(binary.GetVocabulary());
Starters(binary);
Continuation(binary);
Stateless(binary);
unlink("test.binary");
}
BOOST_AUTO_TEST_CASE(write_and_read_probing) {
BinaryTest<Model>();
}
BOOST_AUTO_TEST_CASE(write_and_read_sorted) {
BinaryTest<SortedModel>();
}
BOOST_AUTO_TEST_CASE(write_and_read_trie) {
BinaryTest<TrieModel>();
}
} // namespace
} // namespace ngram
} // namespace lm
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