diff options
| -rw-r--r-- | rst_parser/Makefile.am | 5 | ||||
| -rw-r--r-- | rst_parser/dep_training.cc | 4 | ||||
| -rw-r--r-- | rst_parser/rst_parse.cc | 111 |
3 files changed, 119 insertions, 1 deletions
diff --git a/rst_parser/Makefile.am b/rst_parser/Makefile.am index 876c2237..4977f584 100644 --- a/rst_parser/Makefile.am +++ b/rst_parser/Makefile.am @@ -1,5 +1,5 @@ bin_PROGRAMS = \ - mst_train rst_train + mst_train rst_train rst_parse noinst_LIBRARIES = librst.a @@ -11,4 +11,7 @@ mst_train_LDADD = librst.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/ rst_train_SOURCES = rst_train.cc rst_train_LDADD = librst.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a ../klm/lm/libklm.a ../klm/util/libklm_util.a -lz +rst_parse_SOURCES = rst_parse.cc +rst_parse_LDADD = librst.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a ../klm/lm/libklm.a ../klm/util/libklm_util.a -lz + AM_CPPFLAGS = -W -Wall -Wno-sign-compare $(GTEST_CPPFLAGS) -I$(top_srcdir)/decoder -I$(top_srcdir)/training -I$(top_srcdir)/utils -I$(top_srcdir)/mteval -I../klm diff --git a/rst_parser/dep_training.cc b/rst_parser/dep_training.cc index e26505ec..ef97798b 100644 --- a/rst_parser/dep_training.cc +++ b/rst_parser/dep_training.cc @@ -18,6 +18,10 @@ static void ParseInstance(const string& line, int start, TrainingInstance* out, TrainingInstance& cur = *out; TaggedSentence& ts = cur.ts; EdgeSubset& tree = cur.tree; + ts.pos.clear(); + ts.words.clear(); + tree.roots.clear(); + tree.h_m_pairs.clear(); assert(obj.is<picojson::object>()); const picojson::object& d = obj.get<picojson::object>(); const picojson::array& ta = d.find("tokens")->second.get<picojson::array>(); diff --git a/rst_parser/rst_parse.cc b/rst_parser/rst_parse.cc new file mode 100644 index 00000000..9c42a8f4 --- /dev/null +++ b/rst_parser/rst_parse.cc @@ -0,0 +1,111 @@ +#include "arc_factored.h" + +#include <vector> +#include <iostream> +#include <boost/program_options.hpp> +#include <boost/program_options/variables_map.hpp> + +#include "timing_stats.h" +#include "arc_ff.h" +#include "dep_training.h" +#include "stringlib.h" +#include "filelib.h" +#include "tdict.h" +#include "weights.h" +#include "rst.h" +#include "global_ff.h" + +using namespace std; +namespace po = boost::program_options; + +void InitCommandLine(int argc, char** argv, po::variables_map* conf) { + po::options_description opts("Configuration options"); + string cfg_file; + opts.add_options() + ("input,i",po::value<string>()->default_value("-"), "File containing test data (jsent format)") + ("q_weights,q",po::value<string>(), "Arc-factored weights for proposal distribution (mandatory)") + ("p_weights,p",po::value<string>(), "Weights for target distribution (optional)") + ("samples,n",po::value<unsigned>()->default_value(1000), "Number of samples"); + po::options_description clo("Command line options"); + clo.add_options() + ("config,c", po::value<string>(&cfg_file), "Configuration file") + ("help,?", "Print this help message and exit"); + + po::options_description dconfig_options, dcmdline_options; + dconfig_options.add(opts); + dcmdline_options.add(dconfig_options).add(clo); + po::store(parse_command_line(argc, argv, dcmdline_options), *conf); + if (cfg_file.size() > 0) { + ReadFile rf(cfg_file); + po::store(po::parse_config_file(*rf.stream(), dconfig_options), *conf); + } + if (conf->count("help") || conf->count("q_weights") == 0) { + cerr << dcmdline_options << endl; + exit(1); + } +} + +int main(int argc, char** argv) { + po::variables_map conf; + InitCommandLine(argc, argv, &conf); + vector<weight_t> qweights, pweights; + Weights::InitFromFile(conf["q_weights"].as<string>(), &qweights); + if (conf.count("p_weights")) + Weights::InitFromFile(conf["p_weights"].as<string>(), &pweights); + const bool global = pweights.size() > 0; + ArcFeatureFunctions ffs; + GlobalFeatureFunctions gff; + ReadFile rf(conf["input"].as<string>()); + istream* in = rf.stream(); + TrainingInstance sent; + MT19937 rng; + int samples = conf["samples"].as<unsigned>(); + int totroot = 0, root_right = 0, tot = 0, cor = 0; + while(TrainingInstance::ReadInstance(in, &sent)) { + ffs.PrepareForInput(sent.ts); + if (global) gff.PrepareForInput(sent.ts); + ArcFactoredForest forest(sent.ts.pos.size()); + forest.ExtractFeatures(sent.ts, ffs); + forest.Reweight(qweights); + TreeSampler ts(forest); + double best_score = -numeric_limits<double>::infinity(); + EdgeSubset best_tree; + for (int n = 0; n < samples; ++n) { + EdgeSubset tree; + ts.SampleRandomSpanningTree(&tree, &rng); + SparseVector<double> qfeats, gfeats; + tree.ExtractFeatures(sent.ts, ffs, &qfeats); + double score = 0; + if (global) { + gff.Features(sent.ts, tree, &gfeats); + score = (qfeats + gfeats).dot(pweights); + } else { + score = qfeats.dot(qweights); + } + if (score > best_score) { + best_tree = tree; + best_score = score; + } + } + cerr << "BEST SCORE: " << best_score << endl; + cout << best_tree << endl; + const bool sent_has_ref = sent.tree.h_m_pairs.size() > 0; + if (sent_has_ref) { + map<pair<short,short>, bool> ref; + for (int i = 0; i < sent.tree.h_m_pairs.size(); ++i) + ref[sent.tree.h_m_pairs[i]] = true; + int ref_root = sent.tree.roots.front(); + if (ref_root == best_tree.roots.front()) { ++root_right; } + ++totroot; + for (int i = 0; i < best_tree.h_m_pairs.size(); ++i) { + if (ref[best_tree.h_m_pairs[i]]) { + ++cor; + } + ++tot; + } + } + } + cerr << "F = " << (double(cor + root_right) / (tot + totroot)) << endl; + return 0; +} + |