diff options
Diffstat (limited to 'rampion')
| -rw-r--r-- | rampion/Makefile.am | 4 | ||||
| -rwxr-xr-x | rampion/rampion.pl | 16 | ||||
| -rw-r--r-- | rampion/rampion_cccp.cc | 69 |
3 files changed, 54 insertions, 35 deletions
diff --git a/rampion/Makefile.am b/rampion/Makefile.am index 12df39c2..f4dbb7cc 100644 --- a/rampion/Makefile.am +++ b/rampion/Makefile.am @@ -1,6 +1,6 @@ bin_PROGRAMS = rampion_cccp rampion_cccp_SOURCES = rampion_cccp.cc -rampion_cccp_LDADD = $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a -lz +rampion_cccp_LDADD = $(top_srcdir)/training/libtraining.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a -lz -AM_CPPFLAGS = -W -Wall -Wno-sign-compare $(GTEST_CPPFLAGS) -I$(top_srcdir)/utils -I$(top_srcdir)/decoder -I$(top_srcdir)/mteval -I$(top_srcdir)/training +AM_CPPFLAGS = -W -Wall $(GTEST_CPPFLAGS) -I$(top_srcdir)/utils -I$(top_srcdir)/decoder -I$(top_srcdir)/mteval -I$(top_srcdir)/training diff --git a/rampion/rampion.pl b/rampion/rampion.pl index 9884f453..55f7b3f1 100755 --- a/rampion/rampion.pl +++ b/rampion/rampion.pl @@ -65,12 +65,14 @@ my $cpbin=1; my $tune_regularizer = 0; my $reg = 500; my $reg_previous = 5000; +my $dont_accum = 0; # Process command-line options Getopt::Long::Configure("no_auto_abbrev"); if (GetOptions( "jobs=i" => \$jobs, "dont-clean" => \$disable_clean, + "dont-accumulate" => \$dont_accum, "pass-suffix=s" => \$pass_suffix, "qsub" => \$useqsub, "dry-run" => \$dryrun, @@ -163,8 +165,6 @@ my $decoderBase = check_output("basename $decoder"); chomp $decoderBase; my $newIniFile = "$dir/$decoderBase.ini"; my $inputFileName = "$dir/input"; my $user = $ENV{"USER"}; - - # process ini file -e $iniFile || die "Error: could not open $iniFile for reading\n"; open(INI, $iniFile); @@ -229,6 +229,13 @@ close F; unless($best_weights){ $best_weights = $weights; } unless($projected_score){ $projected_score = 0.0; } $seen_weights{$weights} = 1; +my $kbest = "$dir/kbest"; +if ($dont_accum) { + $kbest = ''; +} else { + check_call("mkdir -p $kbest"); + $kbest = "--kbest_repository $kbest"; +} my $random_seed = int(time / 1000); my $lastWeightsFile; @@ -305,7 +312,7 @@ while (1){ $cmd="$MAPINPUT $dir/hgs > $dir/agenda.$im1"; print STDERR "COMMAND:\n$cmd\n"; check_call($cmd); - $cmd="$MAPPER $refs_comma_sep -m $metric -i $dir/agenda.$im1 -w $inweights > $outweights"; + $cmd="$MAPPER $refs_comma_sep -m $metric -i $dir/agenda.$im1 $kbest -w $inweights > $outweights"; check_call($cmd); $lastWeightsFile = $outweights; $iteration++; @@ -445,6 +452,9 @@ General options: --help Print this message and exit. + --dont-accumulate + Don't accumulate k-best lists from multiple iterations. + --max-iterations <M> Maximum number of iterations to run. If not specified, defaults to $default_max_iter. diff --git a/rampion/rampion_cccp.cc b/rampion/rampion_cccp.cc index 7a6f1f0c..1e36dc51 100644 --- a/rampion/rampion_cccp.cc +++ b/rampion/rampion_cccp.cc @@ -14,6 +14,7 @@ #include "viterbi.h" #include "ns.h" #include "ns_docscorer.h" +#include "candidate_set.h" using namespace std; namespace po = boost::program_options; @@ -25,6 +26,7 @@ void InitCommandLine(int argc, char** argv, po::variables_map* conf) { ("weights,w",po::value<string>(), "[REQD] Weights files from current iterations") ("input,i",po::value<string>()->default_value("-"), "Input file to map (- is STDIN)") ("evaluation_metric,m",po::value<string>()->default_value("IBM_BLEU"), "Evaluation metric (ibm_bleu, koehn_bleu, nist_bleu, ter, meteor, etc.)") + ("kbest_repository,R",po::value<string>(), "Accumulate k-best lists from previous iterations (parameter is path to repository)") ("kbest_size,k",po::value<unsigned>()->default_value(500u), "Top k-hypotheses to extract") ("cccp_iterations,I", po::value<unsigned>()->default_value(10u), "CCCP iterations (T')") ("ssd_iterations,J", po::value<unsigned>()->default_value(5u), "Stochastic subgradient iterations (T'')") @@ -50,38 +52,36 @@ void InitCommandLine(int argc, char** argv, po::variables_map* conf) { } } -struct HypInfo { - HypInfo() : g(-100.0f) {} - HypInfo(const vector<WordID>& h, - const SparseVector<weight_t>& feats, - const SegmentEvaluator& scorer, const EvaluationMetric* metric) : hyp(h), x(feats) { - SufficientStats ss; - scorer.Evaluate(hyp, &ss); - g = metric->ComputeScore(ss); +struct GainFunction { + explicit GainFunction(const EvaluationMetric* m) : metric(m) {} + float operator()(const SufficientStats& eval_feats) const { + float g = metric->ComputeScore(eval_feats); if (!metric->IsErrorMetric()) g = 1 - g; + return g; } - - vector<WordID> hyp; - float g; - SparseVector<weight_t> x; + const EvaluationMetric* metric; }; -void CostAugmentedSearch(const vector<HypInfo>& kbest, +template <typename GainFunc> +void CostAugmentedSearch(const GainFunc& gain, + const training::CandidateSet& cs, const SparseVector<double>& w, double alpha, SparseVector<double>* fmap) { unsigned best_i = 0; double best = -numeric_limits<double>::infinity(); - for (unsigned i = 0; i < kbest.size(); ++i) { - double s = kbest[i].x.dot(w) + alpha * kbest[i].g; + for (unsigned i = 0; i < cs.size(); ++i) { + double s = cs[i].fmap.dot(w) + alpha * gain(cs[i].eval_feats); if (s > best) { best = s; best_i = i; } } - *fmap = kbest[best_i].x; + *fmap = cs[best_i].fmap; } + + // runs lines 4--15 of rampion algorithm int main(int argc, char** argv) { po::variables_map conf; @@ -97,6 +97,11 @@ int main(int argc, char** argv) { Hypergraph hg; string last_file; ReadFile in_read(conf["input"].as<string>()); + string kbest_repo; + if (conf.count("kbest_repository")) { + kbest_repo = conf["kbest_repository"].as<string>(); + MkDirP(kbest_repo); + } istream &in=*in_read.stream(); const unsigned kbest_size = conf["kbest_size"].as<unsigned>(); const unsigned tp = conf["cccp_iterations"].as<unsigned>(); @@ -112,40 +117,44 @@ int main(int argc, char** argv) { Weights::InitSparseVector(vweights, &weights); } string line, file; - vector<vector<HypInfo> > kis; + vector<training::CandidateSet> kis; cerr << "Loading hypergraphs...\n"; while(getline(in, line)) { istringstream is(line); int sent_id; kis.resize(kis.size() + 1); - vector<HypInfo>& curkbest = kis.back(); + training::CandidateSet& curkbest = kis.back(); + string kbest_file; + if (kbest_repo.size()) { + ostringstream os; + os << kbest_repo << "/kbest." << sent_id << ".txt.gz"; + kbest_file = os.str(); + if (FileExists(kbest_file)) + curkbest.ReadFromFile(kbest_file); + } is >> file >> sent_id; ReadFile rf(file); if (kis.size() % 5 == 0) { cerr << '.'; } if (kis.size() % 200 == 0) { cerr << " [" << kis.size() << "]\n"; } HypergraphIO::ReadFromJSON(rf.stream(), &hg); hg.Reweight(weights); - KBest::KBestDerivations<vector<WordID>, ESentenceTraversal> kbest(hg, kbest_size); - - for (int i = 0; i < kbest_size; ++i) { - const KBest::KBestDerivations<vector<WordID>, ESentenceTraversal>::Derivation* d = - kbest.LazyKthBest(hg.nodes_.size() - 1, i); - if (!d) break; - curkbest.push_back(HypInfo(d->yield, d->feature_values, *ds[sent_id], metric)); - } + curkbest.AddKBestCandidates(hg, kbest_size, ds[sent_id]); + if (kbest_file.size()) + curkbest.WriteToFile(kbest_file); } cerr << "\nHypergraphs loaded.\n"; vector<SparseVector<weight_t> > goals(kis.size()); // f(x_i,y+,h+) SparseVector<weight_t> fear; // f(x,y-,h-) + const GainFunction gain(metric); for (unsigned iterp = 1; iterp <= tp; ++iterp) { cerr << "CCCP Iteration " << iterp << endl; - for (int i = 0; i < goals.size(); ++i) - CostAugmentedSearch(kis[i], weights, goodsign * alpha, &goals[i]); + for (unsigned i = 0; i < goals.size(); ++i) + CostAugmentedSearch(gain, kis[i], weights, goodsign * alpha, &goals[i]); for (unsigned iterpp = 1; iterpp <= tpp; ++iterpp) { cerr << " SSD Iteration " << iterpp << endl; - for (int i = 0; i < goals.size(); ++i) { - CostAugmentedSearch(kis[i], weights, badsign * alpha, &fear); + for (unsigned i = 0; i < goals.size(); ++i) { + CostAugmentedSearch(gain, kis[i], weights, badsign * alpha, &fear); weights -= weights * (eta * reg / goals.size()); weights += (goals[i] - fear) * eta; } |