diff options
| author | Chris Dyer <cdyer@cs.cmu.edu> | 2012-03-09 23:13:09 -0500 | 
|---|---|---|
| committer | Chris Dyer <cdyer@cs.cmu.edu> | 2012-03-09 23:13:09 -0500 | 
| commit | ef614a1d968aebbf463ed57876fee395b4c24635 (patch) | |
| tree | 603c9112772422aa4320933d7cc171135b11bb99 /gi | |
| parent | 600ff8e60086c5cc197fe302bfcea113ebd15565 (diff) | |
logging after alignment
Diffstat (limited to 'gi')
| -rw-r--r-- | gi/pf/align-lexonly-pyp.cc | 1 | ||||
| -rw-r--r-- | gi/pf/pyp_tm.cc | 7 | ||||
| -rw-r--r-- | gi/pf/pyp_word_model.h | 2 | 
3 files changed, 7 insertions, 3 deletions
| diff --git a/gi/pf/align-lexonly-pyp.cc b/gi/pf/align-lexonly-pyp.cc index d68a4b8f..4a1d1db6 100644 --- a/gi/pf/align-lexonly-pyp.cc +++ b/gi/pf/align-lexonly-pyp.cc @@ -208,6 +208,7 @@ int main(int argc, char** argv) {    }    for (unsigned i = 0; i < corpus.size(); ++i)      WriteAlignments(corpus[i]); +  aligner.model.Summary();    return 0;  } diff --git a/gi/pf/pyp_tm.cc b/gi/pf/pyp_tm.cc index 94cbe7c3..b5262f47 100644 --- a/gi/pf/pyp_tm.cc +++ b/gi/pf/pyp_tm.cc @@ -54,8 +54,6 @@ struct ConditionalPYPWordModel {      assert(it != r.end());      if (it->second.decrement(trglets, rng)) {        base.Decrement(trglets, rng); -      if (it->second.num_customers() == 0) -        r.erase(it);      }    } @@ -84,6 +82,11 @@ PYPLexicalTranslation::PYPLexicalTranslation(const vector<vector<WordID> >& lets      tmodel(new ConditionalPYPWordModel<PYPWordModel>(up0)),      kX(-TD::Convert("X")) {} +void PYPLexicalTranslation::Summary() const { +  tmodel->Summary(); +  up0->Summary(); +} +  prob_t PYPLexicalTranslation::Likelihood() const {    prob_t p = up0->Likelihood();    p *= tmodel->Likelihood(); diff --git a/gi/pf/pyp_word_model.h b/gi/pf/pyp_word_model.h index 800a4fd7..ff366865 100644 --- a/gi/pf/pyp_word_model.h +++ b/gi/pf/pyp_word_model.h @@ -12,7 +12,7 @@  // PYP(d,s,poisson-uniform) represented as a CRP  struct PYPWordModel { -  explicit PYPWordModel(const unsigned vocab_e_size, const double mean_len = 7.5) : +  explicit PYPWordModel(const unsigned vocab_e_size, const double mean_len = 5) :        base(prob_t::One()), r(1,1,1,1,0.66,50.0), u0(-std::log(vocab_e_size)), mean_length(mean_len) {}    void ResampleHyperparameters(MT19937* rng); | 
