diff options
| -rw-r--r-- | decoder/cdec.cc | 14 |
1 files changed, 11 insertions, 3 deletions
diff --git a/decoder/cdec.cc b/decoder/cdec.cc index c940fdac..e3a2435d 100644 --- a/decoder/cdec.cc +++ b/decoder/cdec.cc @@ -38,6 +38,8 @@ using namespace std::tr1; using boost::shared_ptr; namespace po = boost::program_options; +bool verbose_feature_functions=true; + // some globals ... boost::shared_ptr<RandomNumberGenerator<boost::mt19937> > rng; static const double kMINUS_EPSILON = -1e-6; // don't be too strict @@ -63,6 +65,7 @@ void InitCommandLine(int argc, char** argv, po::variables_map* conf) { ("weights,w",po::value<string>(),"Feature weights file") ("prelm_weights",po::value<string>(),"Feature weights file for prelm_beam_prune. Requires --weights.") ("prelm_copy_weights","use --weights as value for --prelm_weights.") + ("keep_prelm_cube_order","when forest rescoring with final models, use the edge ordering from the prelm pruning features*weights. only meaningful if --prelm_weights given. UNTESTED but assume that cube pruning gives a sensible result, and that 'good' (as tuned for bleu w/ prelm features) edges come first.") ("no_freeze_feature_set,Z", "Do not freeze feature set after reading feature weights file") ("feature_function,F",po::value<vector<string> >()->composing(), "Additional feature function(s) (-L for list)") @@ -348,8 +351,10 @@ int main(int argc, char** argv) { // TODO check that multiple features aren't trying to set the same fid pffs.push_back(pff); late_ffs.push_back(p); + int nbyte=p->NumBytesContext(); + if (verbose_feature_functions) + cerr<<"State is "<<nbyte<<" bytes for feature "<<ff<<endl; if (has_prelm_models) { - int nbyte=p->NumBytesContext(); if (nbyte==0) prelm_ffs.push_back(p); else @@ -357,6 +362,9 @@ int main(int argc, char** argv) { } } } + if (has_prelm_models) + cerr << "prelm rescoring with "<<prelm_ffs.size()<<" 0-state feature functions. +LM pass will use "<<late_ffs.size()<<" features (not counting rule features)."<<endl; + ModelSet late_models(feature_weights, late_ffs); int palg = 1; @@ -454,7 +462,6 @@ int main(int argc, char** argv) { if (has_prelm_models) { ModelSet prelm_models(prelm_feature_weights, prelm_ffs); - cerr << "Rescoring with rule probabilities and "<<prelm_ffs.size()<<" 0-state feature functions. +LM pass will use "<<late_ffs.size()<<" features."<<endl; Timer t("prelm rescoring"); forest.Reweight(prelm_feature_weights); forest.SortInEdgesByEdgeWeights(); @@ -482,7 +489,8 @@ int main(int argc, char** argv) { if (has_late_models) { Timer t("Forest rescoring:"); forest.Reweight(feature_weights); - forest.SortInEdgesByEdgeWeights(); + if (!has_prelm_models || conf.count("keep_prelm_cube_order")) + forest.SortInEdgesByEdgeWeights(); Hypergraph lm_forest; ApplyModelSet(forest, smeta, |