diff options
Diffstat (limited to 'gi/pf/align-lexonly-pyp.cc')
-rw-r--r-- | gi/pf/align-lexonly-pyp.cc | 24 |
1 files changed, 17 insertions, 7 deletions
diff --git a/gi/pf/align-lexonly-pyp.cc b/gi/pf/align-lexonly-pyp.cc index 6c054753..942dcf51 100644 --- a/gi/pf/align-lexonly-pyp.cc +++ b/gi/pf/align-lexonly-pyp.cc @@ -20,6 +20,9 @@ void InitCommandLine(int argc, char** argv, po::variables_map* conf) { po::options_description opts("Configuration options"); opts.add_options() ("samples,s",po::value<unsigned>()->default_value(1000),"Number of samples") + ("infer_alignment_hyperparameters,I", "Infer alpha and p_null, otherwise fixed values will be assumed") + ("p_null,0", po::value<double>()->default_value(0.08), "probability of aligning to null") + ("align_alpha,a", po::value<double>()->default_value(4.0), "how 'tight' is the bias toward be along the diagonal?") ("input,i",po::value<string>(),"Read parallel data from") ("random_seed,S",po::value<uint32_t>(), "Random seed"); po::options_description clo("Command line options"); @@ -59,9 +62,13 @@ struct AlignedSentencePair { }; struct Aligner { - Aligner(const vector<vector<WordID> >& lets, int num_letters, vector<AlignedSentencePair>* c) : + Aligner(const vector<vector<WordID> >& lets, + int num_letters, + const po::variables_map& conf, + vector<AlignedSentencePair>* c) : corpus(*c), - paj_model(4, 0.08), + paj_model(conf["align_alpha"].as<double>(), conf["p_null"].as<double>()), + infer_paj(conf.count("infer_alignment_hyperparameters") > 0), model(lets, num_letters), kNULL(TD::Convert("NULL")) { assert(lets[kNULL].size() == 0); @@ -69,12 +76,13 @@ struct Aligner { vector<AlignedSentencePair>& corpus; QuasiModel2 paj_model; + const bool infer_paj; PYPLexicalTranslation model; const WordID kNULL; void ResampleHyperparameters() { model.ResampleHyperparameters(prng); - paj_model.ResampleHyperparameters(prng); + if (infer_paj) paj_model.ResampleHyperparameters(prng); } void InitializeRandom() { @@ -117,8 +125,6 @@ struct Aligner { paj_model.Increment(a_j, j, asp.src.size(), asp.trg.size()); } } - cerr << "LLH = " << Likelihood() << " \t(Amodel=" << paj_model.Likelihood() - << " TModel=" << model.Likelihood() << ") contexts=" << model.UniqueConditioningContexts() << endl; } prob_t Likelihood() const { @@ -211,13 +217,17 @@ int main(int argc, char** argv) { ExtractLetters(vocabf, &letters, NULL); letters[TD::Convert("NULL")].clear(); - Aligner aligner(letters, letset.size(), &corpus); + Aligner aligner(letters, letset.size(), conf, &corpus); aligner.InitializeRandom(); const unsigned samples = conf["samples"].as<unsigned>(); for (int i = 0; i < samples; ++i) { for (int j = 65; j < 67; ++j) Debug(corpus[j]); - if (i % 10 == 9) aligner.ResampleHyperparameters(); + if (i % 10 == 9) { + aligner.ResampleHyperparameters(); + cerr << "LLH = " << aligner.Likelihood() << " \t(Amodel=" << aligner.paj_model.Likelihood() + << " TModel=" << aligner.model.Likelihood() << ") contexts=" << aligner.model.UniqueConditioningContexts() << endl; + } aligner.ResampleCorpus(); if (i > (samples / 5) && (i % 6 == 5)) for (int j = 0; j < corpus.size(); ++j) AddSample(&corpus[j]); } |