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author | Chris Dyer <cdyer@cs.cmu.edu> | 2011-03-10 20:02:07 -0500 |
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committer | Chris Dyer <cdyer@cs.cmu.edu> | 2011-03-10 20:02:07 -0500 |
commit | e7dfcff76b8d53775f753c2367776c5348bd73b5 (patch) | |
tree | 0315feb787dd7d3d5c8755a34cbc13fad7c3a0b4 /training/augment_grammar.cc | |
parent | 1c6ba93d7f9d46186b05c07cd5208793554c06af (diff) |
experimental nonlinear feature
Diffstat (limited to 'training/augment_grammar.cc')
-rw-r--r-- | training/augment_grammar.cc | 9 |
1 files changed, 9 insertions, 0 deletions
diff --git a/training/augment_grammar.cc b/training/augment_grammar.cc index 19120d00..9ad03b6c 100644 --- a/training/augment_grammar.cc +++ b/training/augment_grammar.cc @@ -36,6 +36,7 @@ bool InitCommandLine(int argc, char** argv, po::variables_map* conf) { ("source_lm,l",po::value<string>(),"Source language LM (KLM)") ("collapse_weights,w",po::value<string>(), "Collapse weights into a single feature X using the coefficients from this weights file") ("add_shape_types,s", "Add rule shape types") + ("extra_lex_feature,x", "Experimental nonlinear lexical weighting feature") ("replace_files,r", "Replace files with transformed variants (requires loading full grammar into memory)") ("grammar,g", po::value<vector<string> >(), "Input (also output) grammar file(s)"); po::options_description clo("Command line options"); @@ -85,6 +86,7 @@ template <class Model> float Score(const vector<WordID>& str, const Model &model return total; } +bool extra_feature; int kSrcLM; vector<double> col_weights; bool gather_rules; @@ -94,9 +96,15 @@ static void RuleHelper(const TRulePtr& new_rule, const unsigned int ctf_level, c static const int kSrcLM = FD::Convert("SrcLM"); static const int kPC = FD::Convert("PC"); static const int kX = FD::Convert("X"); + static const int kPhraseModel2 = FD::Convert("PhraseModel_1"); + static const int kNewLex = FD::Convert("NewLex"); TRulePtr r; r.reset(new TRule(*new_rule)); if (ngram) r->scores_.set_value(kSrcLM, Score(r->f_, *ngram)); r->scores_.set_value(kPC, 1.0); + if (extra_feature) { + float v = r->scores_.value(kPhraseModel2); + r->scores_.set_value(kNewLex, v*(v+1)); + } if (col_weights.size()) { double score = r->scores_.dot(col_weights); r->scores_.clear(); @@ -122,6 +130,7 @@ int main(int argc, char** argv) { cerr << "Loaded " << (int)ngram->Order() << "-gram KenLM (MapSize=" << word_map.size() << ")\n"; cerr << " <s> = " << kSOS << endl; } else { ngram = NULL; } + extra_feature = conf.count("extra_lex_feature") > 0; if (conf.count("collapse_weights")) { Weights w; w.InitFromFile(conf["collapse_weights"].as<string>()); |