mosesdecoder/lm/ngram_query.hh
2012-01-14 17:07:31 +00:00

104 lines
2.9 KiB
C++

#ifndef LM_NGRAM_QUERY__
#define LM_NGRAM_QUERY__
#include "lm/enumerate_vocab.hh"
#include "lm/model.hh"
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <string>
#include <ctype.h>
#if !defined(_WIN32) && !defined(_WIN64)
#include <sys/resource.h>
#include <sys/time.h>
#endif
namespace lm {
namespace ngram {
#if !defined(_WIN32) && !defined(_WIN64)
float FloatSec(const struct timeval &tv) {
return static_cast<float>(tv.tv_sec) + (static_cast<float>(tv.tv_usec) / 1000000000.0);
}
#endif
void PrintUsage(const char *message) {
#if !defined(_WIN32) && !defined(_WIN64)
struct rusage usage;
if (getrusage(RUSAGE_SELF, &usage)) {
perror("getrusage");
return;
}
std::cerr << message;
std::cerr << "user\t" << FloatSec(usage.ru_utime) << "\nsys\t" << FloatSec(usage.ru_stime) << '\n';
// Linux doesn't set memory usage :-(.
std::ifstream status("/proc/self/status", std::ios::in);
std::string line;
while (getline(status, line)) {
if (!strncmp(line.c_str(), "VmRSS:\t", 7)) {
std::cerr << "rss " << (line.c_str() + 7) << '\n';
break;
}
}
#endif
}
template <class Model> void Query(const Model &model, bool sentence_context, std::istream &in_stream, std::ostream &out_stream) {
PrintUsage("Loading statistics:\n");
typename Model::State state, out;
lm::FullScoreReturn ret;
std::string word;
while (in_stream) {
state = sentence_context ? model.BeginSentenceState() : model.NullContextState();
float total = 0.0;
bool got = false;
unsigned int oov = 0;
while (in_stream >> word) {
got = true;
lm::WordIndex vocab = model.GetVocabulary().Index(word);
if (vocab == 0) ++oov;
ret = model.FullScore(state, vocab, out);
total += ret.prob;
out_stream << word << '=' << vocab << ' ' << static_cast<unsigned int>(ret.ngram_length) << ' ' << ret.prob << '\t';
state = out;
char c;
while (true) {
c = in_stream.get();
if (!in_stream) break;
if (c == '\n') break;
if (!isspace(c)) {
in_stream.unget();
break;
}
}
if (c == '\n') break;
}
if (!got && !in_stream) break;
if (sentence_context) {
ret = model.FullScore(state, model.GetVocabulary().EndSentence(), out);
total += ret.prob;
out_stream << "</s>=" << model.GetVocabulary().EndSentence() << ' ' << static_cast<unsigned int>(ret.ngram_length) << ' ' << ret.prob << '\t';
}
out_stream << "Total: " << total << " OOV: " << oov << '\n';
}
PrintUsage("After queries:\n");
}
template <class M> void Query(const char *file, bool sentence_context, std::istream &in_stream, std::ostream &out_stream) {
Config config;
// config.load_method = util::LAZY;
M model(file, config);
Query(model, sentence_context, in_stream, out_stream);
}
} // namespace ngram
} // namespace lm
#endif // LM_NGRAM_QUERY__