mirror of
https://github.com/moses-smt/mosesdecoder.git
synced 2024-10-26 19:37:58 +03:00
92 lines
2.5 KiB
C++
92 lines
2.5 KiB
C++
#ifndef LM_NGRAM_QUERY__
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#define LM_NGRAM_QUERY__
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#include "lm/enumerate_vocab.hh"
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#include "lm/model.hh"
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#include <cstdlib>
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#include <fstream>
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#include <iostream>
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#include <string>
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#include <ctype.h>
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#if !defined(_WIN32) && !defined(_WIN64)
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#include <sys/resource.h>
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#include <sys/time.h>
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#endif
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#if !defined(_WIN32) && !defined(_WIN64)
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float FloatSec(const struct timeval &tv) {
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return static_cast<float>(tv.tv_sec) + (static_cast<float>(tv.tv_usec) / 1000000000.0);
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}
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#endif
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void PrintUsage(const char *message) {
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#if !defined(_WIN32) && !defined(_WIN64)
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struct rusage usage;
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if (getrusage(RUSAGE_SELF, &usage)) {
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perror("getrusage");
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return;
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}
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std::cerr << message;
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std::cerr << "user\t" << FloatSec(usage.ru_utime) << "\nsys\t" << FloatSec(usage.ru_stime) << '\n';
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// Linux doesn't set memory usage :-(.
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std::ifstream status("/proc/self/status", std::ios::in);
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std::string line;
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while (getline(status, line)) {
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if (!strncmp(line.c_str(), "VmRSS:\t", 7)) {
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std::cerr << "rss " << (line.c_str() + 7) << '\n';
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break;
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}
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}
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#endif
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}
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template <class Model> void Query(const Model &model, bool sentence_context, std::istream &inStream, std::ostream &outStream) {
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PrintUsage("Loading statistics:\n");
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typename Model::State state, out;
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lm::FullScoreReturn ret;
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std::string word;
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while (inStream) {
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state = sentence_context ? model.BeginSentenceState() : model.NullContextState();
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float total = 0.0;
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bool got = false;
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unsigned int oov = 0;
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while (inStream >> word) {
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got = true;
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lm::WordIndex vocab = model.GetVocabulary().Index(word);
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if (vocab == 0) ++oov;
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ret = model.FullScore(state, vocab, out);
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total += ret.prob;
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outStream << word << '=' << vocab << ' ' << static_cast<unsigned int>(ret.ngram_length) << ' ' << ret.prob << '\t';
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state = out;
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char c;
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while (true) {
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c = inStream.get();
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if (!inStream) break;
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if (c == '\n') break;
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if (!isspace(c)) {
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inStream.unget();
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break;
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}
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}
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if (c == '\n') break;
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}
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if (!got && !inStream) break;
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if (sentence_context) {
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ret = model.FullScore(state, model.GetVocabulary().EndSentence(), out);
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total += ret.prob;
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outStream << "</s>=" << model.GetVocabulary().EndSentence() << ' ' << static_cast<unsigned int>(ret.ngram_length) << ' ' << ret.prob << '\t';
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}
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outStream << "Total: " << total << " OOV: " << oov << '\n';
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}
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PrintUsage("After queries:\n");
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}
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#endif // LM_NGRAM_QUERY__
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