From da6c892bc05a5520910e23089d83ceb1f2a0fbb4 Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Mon, 21 Mar 2011 22:10:02 -0400 Subject: add support for normalized 'summary features'- seemingly sound way of dealing with normalization problems in embedded crf translation models --- decoder/decoder.cc | 22 +++++++++++++++++++++- 1 file changed, 21 insertions(+), 1 deletion(-) (limited to 'decoder') diff --git a/decoder/decoder.cc b/decoder/decoder.cc index 95ff6270..8a03c5c9 100644 --- a/decoder/decoder.cc +++ b/decoder/decoder.cc @@ -141,12 +141,13 @@ inline shared_ptr make_fsa_ff(string const& ffp,bool verbose // and then prune the resulting (rescored) hypergraph. All feature values from previous // passes are carried over into subsequent passes (where they may have different weights). struct RescoringPass { - RescoringPass() : density_prune(), beam_prune() {} + RescoringPass() : fid_summary(), density_prune(), beam_prune() {} shared_ptr models; shared_ptr inter_conf; vector ffs; shared_ptr w; // null == use previous weights vector weight_vector; + int fid_summary; // 0 == no summary feature double density_prune; // 0 == don't density prune double beam_prune; // 0 == don't beam prune }; @@ -155,6 +156,7 @@ ostream& operator<<(ostream& os, const RescoringPass& rp) { os << "[num_fn=" << rp.ffs.size(); if (rp.inter_conf) { os << " int_alg=" << *rp.inter_conf; } if (rp.w) os << " new_weights"; + if (rp.fid_summary) os << " summary_feature=" << FD::Convert(rp.fid_summary); if (rp.density_prune) os << " density_prune=" << rp.density_prune; if (rp.beam_prune) os << " beam_prune=" << rp.beam_prune; os << ']'; @@ -361,18 +363,21 @@ DecoderImpl::DecoderImpl(po::variables_map& conf, int argc, char** argv, istream ("weights,w",po::value(),"Feature weights file (initial forest / pass 1)") ("feature_function,F",po::value >()->composing(), "Pass 1 additional feature function(s) (-L for list)") ("intersection_strategy,I",po::value()->default_value("cube_pruning"), "Pass 1 intersection strategy for incorporating finite-state features; values include Cube_pruning, Full") + ("summary_feature", po::value(), "Compute a 'summary feature' at the end of the pass (before any pruning) with name=arg and value=inside-outside/Z") ("density_prune", po::value(), "Pass 1 pruning: keep no more than this many times the number of edges used in the best derivation tree (>=1.0)") ("beam_prune", po::value(), "Pass 1 pruning: Prune paths from scored forest, keep paths within exp(alpha>=0)") ("weights2",po::value(),"Optional pass 2") ("feature_function2",po::value >()->composing(), "Optional pass 2") ("intersection_strategy2",po::value()->default_value("cube_pruning"), "Optional pass 2") + ("summary_feature2", po::value(), "Optional pass 2") ("density_prune2", po::value(), "Optional pass 2") ("beam_prune2", po::value(), "Optional pass 2") ("weights3",po::value(),"Optional pass 3") ("feature_function3",po::value >()->composing(), "Optional pass 3") ("intersection_strategy3",po::value()->default_value("cube_pruning"), "Optional pass 3") + ("summary_feature3", po::value(), "Optional pass 3") ("density_prune3", po::value(), "Optional pass 3") ("beam_prune3", po::value(), "Optional pass 3") @@ -559,6 +564,7 @@ DecoderImpl::DecoderImpl(po::variables_map& conf, int argc, char** argv, istream for (int pass = 0; pass < MAX_PASSES; ++pass) { string ws = "weights" + StringSuffixForRescoringPass(pass); string ff = "feature_function" + StringSuffixForRescoringPass(pass); + string sf = "summary_feature" + StringSuffixForRescoringPass(pass); string bp = "beam_prune" + StringSuffixForRescoringPass(pass); string dp = "density_prune" + StringSuffixForRescoringPass(pass); bool first_pass_condition = ((pass == 0) && (conf.count(ff) || conf.count(bp) || conf.count(dp))); @@ -583,6 +589,11 @@ DecoderImpl::DecoderImpl(po::variables_map& conf, int argc, char** argv, istream if (p->IsStateful()) { has_stateful = true; } } } + if (conf.count(sf)) { + rp.fid_summary = FD::Convert(conf[sf].as()); + assert(rp.fid_summary > 0); + // TODO assert that weights for this pass have coef(fid_summary) == 0.0? + } if (conf.count(bp)) { rp.beam_prune = conf[bp].as(); } if (conf.count(dp)) { rp.density_prune = conf[dp].as(); } int palg = (has_stateful ? 1 : 0); // if there are no stateful featueres, default to FULL @@ -794,6 +805,15 @@ bool DecoderImpl::Decode(const string& input, DecoderObserver* o) { cerr << " " << passtr << " partition log(Z): " << log(z) << endl; } + if (rp.fid_summary) { + Hypergraph::EdgeProbs posteriors; + const prob_t z = forest.ComputeEdgePosteriors(1.0, &posteriors); + if (!SILENT) { cerr << " " << passtr << " adding summary feature " << FD::Convert(rp.fid_summary) << " log(Z)=" << log(z) << endl; } + assert(forest.edges_.size() == posteriors.size()); + for (int i = 0; i < posteriors.size(); ++i) + forest.edges_[i].feature_values_.set_value(rp.fid_summary, log(posteriors[i] / z)); + } + string fullbp = "beam_prune" + StringSuffixForRescoringPass(pass); string fulldp = "density_prune" + StringSuffixForRescoringPass(pass); maybe_prune(forest,conf,fullbp.c_str(),fulldp.c_str(),passtr,srclen); -- cgit v1.2.3