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Option for null context in n-gram query, use tab for delimiter
git-svn-id: https://mosesdecoder.svn.sourceforge.net/svnroot/mosesdecoder/trunk@3871 1f5c12ca-751b-0410-a591-d2e778427230
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@ -35,14 +35,14 @@ void PrintUsage(const char *message) {
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}
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}
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template <class Model> void Query(const Model &model) {
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template <class Model> void Query(const Model &model, bool sentence_context) {
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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 (std::cin) {
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state = model.BeginSentenceState();
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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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@ -52,7 +52,7 @@ template <class Model> void Query(const Model &model) {
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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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std::cout << word << '=' << vocab << ' ' << static_cast<unsigned int>(ret.ngram_length) << ' ' << ret.prob << '\n';
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std::cout << 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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@ -67,9 +67,11 @@ template <class Model> void Query(const Model &model) {
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if (c == '\n') break;
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}
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if (!got && !std::cin) break;
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ret = model.FullScore(state, model.GetVocabulary().EndSentence(), out);
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total += ret.prob;
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std::cout << "</s>=" << model.GetVocabulary().EndSentence() << ' ' << static_cast<unsigned int>(ret.ngram_length) << ' ' << ret.prob << '\n';
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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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std::cout << "</s>=" << model.GetVocabulary().EndSentence() << ' ' << static_cast<unsigned int>(ret.ngram_length) << ' ' << ret.prob << '\t';
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}
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std::cout << "Total: " << total << " OOV: " << oov << '\n';
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}
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PrintUsage("After queries:\n");
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@ -82,29 +84,30 @@ template <class Model> void Query(const char *name) {
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}
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int main(int argc, char *argv[]) {
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if (argc < 2) {
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std::cerr << "Pass language model name." << std::endl;
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return 0;
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if (!(argc == 2 || (argc == 3 && !strcmp(argv[2], "null")))) {
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std::cerr << "Usage: " << argv[0] << " lm_file [null]" << std::endl;
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std::cerr << "Input is wrapped in <s> and </s> unless null is passed." << std::endl;
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return 1;
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}
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bool sentence_context = (argc == 2);
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lm::ngram::ModelType model_type;
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if (lm::ngram::RecognizeBinary(argv[1], model_type)) {
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switch(model_type) {
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case lm::ngram::HASH_PROBING:
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Query<lm::ngram::ProbingModel>(argv[1]);
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break;
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case lm::ngram::HASH_SORTED:
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Query<lm::ngram::SortedModel>(argv[1]);
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Query<lm::ngram::ProbingModel>(argv[1], sentence_context);
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break;
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case lm::ngram::TRIE_SORTED:
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Query<lm::ngram::TrieModel>(argv[1]);
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Query<lm::ngram::TrieModel>(argv[1], sentence_context);
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break;
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case lm::ngram::HASH_SORTED:
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default:
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std::cerr << "Unrecognized kenlm model type " << model_type << std::endl;
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abort();
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}
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} else {
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Query<lm::ngram::ProbingModel>(argv[1]);
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Query<lm::ngram::ProbingModel>(argv[1], sentence_context);
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}
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PrintUsage("Total time including destruction:\n");
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return 0;
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}
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