summaryrefslogtreecommitdiff
path: root/gi/pf/bayes_lattice_score.cc
diff options
context:
space:
mode:
Diffstat (limited to 'gi/pf/bayes_lattice_score.cc')
-rw-r--r--gi/pf/bayes_lattice_score.cc309
1 files changed, 0 insertions, 309 deletions
diff --git a/gi/pf/bayes_lattice_score.cc b/gi/pf/bayes_lattice_score.cc
deleted file mode 100644
index 70cb8dc2..00000000
--- a/gi/pf/bayes_lattice_score.cc
+++ /dev/null
@@ -1,309 +0,0 @@
-#include <iostream>
-#include <queue>
-
-#include <boost/functional.hpp>
-#include <boost/program_options.hpp>
-#include <boost/program_options/variables_map.hpp>
-
-#include "inside_outside.h"
-#include "hg.h"
-#include "hg_io.h"
-#include "bottom_up_parser.h"
-#include "fdict.h"
-#include "grammar.h"
-#include "m.h"
-#include "trule.h"
-#include "tdict.h"
-#include "filelib.h"
-#include "dict.h"
-#include "sampler.h"
-#include "ccrp.h"
-#include "ccrp_onetable.h"
-
-using namespace std;
-using namespace tr1;
-namespace po = boost::program_options;
-
-boost::shared_ptr<MT19937> prng;
-
-void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
- po::options_description opts("Configuration options");
- opts.add_options()
- ("samples,s",po::value<unsigned>()->default_value(1000),"Number of samples")
- ("input,i",po::value<string>(),"Read parallel data from")
- ("random_seed,S",po::value<uint32_t>(), "Random seed");
- po::options_description clo("Command line options");
- clo.add_options()
- ("config", po::value<string>(), "Configuration file")
- ("help", "Print this help message and exit");
- po::options_description dconfig_options, dcmdline_options;
- dconfig_options.add(opts);
- dcmdline_options.add(opts).add(clo);
-
- po::store(parse_command_line(argc, argv, dcmdline_options), *conf);
- if (conf->count("config")) {
- ifstream config((*conf)["config"].as<string>().c_str());
- po::store(po::parse_config_file(config, dconfig_options), *conf);
- }
- po::notify(*conf);
-
- if (conf->count("help") || (conf->count("input") == 0)) {
- cerr << dcmdline_options << endl;
- exit(1);
- }
-}
-
-unsigned ReadCorpus(const string& filename,
- vector<Lattice>* e,
- set<WordID>* vocab_e) {
- e->clear();
- vocab_e->clear();
- ReadFile rf(filename);
- istream* in = rf.stream();
- assert(*in);
- string line;
- unsigned toks = 0;
- while(*in) {
- getline(*in, line);
- if (line.empty() && !*in) break;
- e->push_back(Lattice());
- Lattice& le = e->back();
- LatticeTools::ConvertTextOrPLF(line, & le);
- for (unsigned i = 0; i < le.size(); ++i)
- for (unsigned j = 0; j < le[i].size(); ++j)
- vocab_e->insert(le[i][j].label);
- toks += le.size();
- }
- return toks;
-}
-
-struct BaseModel {
- explicit BaseModel(unsigned tc) :
- unif(1.0 / tc), p(prob_t::One()) {}
- prob_t prob(const TRule& r) const {
- return unif;
- }
- void increment(const TRule& r, MT19937* rng) {
- p *= prob(r);
- }
- void decrement(const TRule& r, MT19937* rng) {
- p /= prob(r);
- }
- prob_t Likelihood() const {
- return p;
- }
- const prob_t unif;
- prob_t p;
-};
-
-struct UnigramModel {
- explicit UnigramModel(unsigned tc) : base(tc), crp(1,1,1,1), glue(1,1,1,1) {}
- BaseModel base;
- CCRP<TRule> crp;
- CCRP<TRule> glue;
-
- prob_t Prob(const TRule& r) const {
- if (r.Arity() != 0) {
- return glue.prob(r, prob_t(0.5));
- }
- return crp.prob(r, base.prob(r));
- }
-
- int Increment(const TRule& r, MT19937* rng) {
- if (r.Arity() != 0) {
- glue.increment(r, 0.5, rng);
- return 0;
- } else {
- if (crp.increment(r, base.prob(r), rng)) {
- base.increment(r, rng);
- return 1;
- }
- return 0;
- }
- }
-
- int Decrement(const TRule& r, MT19937* rng) {
- if (r.Arity() != 0) {
- glue.decrement(r, rng);
- return 0;
- } else {
- if (crp.decrement(r, rng)) {
- base.decrement(r, rng);
- return -1;
- }
- return 0;
- }
- }
-
- prob_t Likelihood() const {
- prob_t p;
- p.logeq(crp.log_crp_prob() + glue.log_crp_prob());
- p *= base.Likelihood();
- return p;
- }
-
- void ResampleHyperparameters(MT19937* rng) {
- crp.resample_hyperparameters(rng);
- glue.resample_hyperparameters(rng);
- cerr << " d=" << crp.discount() << ", s=" << crp.strength() << "\t STOP d=" << glue.discount() << ", s=" << glue.strength() << endl;
- }
-};
-
-UnigramModel* plm;
-
-void SampleDerivation(const Hypergraph& hg, MT19937* rng, vector<unsigned>* sampled_deriv) {
- vector<prob_t> node_probs;
- Inside<prob_t, EdgeProb>(hg, &node_probs);
- queue<unsigned> q;
- q.push(hg.nodes_.size() - 2);
- while(!q.empty()) {
- unsigned cur_node_id = q.front();
-// cerr << "NODE=" << cur_node_id << endl;
- q.pop();
- const Hypergraph::Node& node = hg.nodes_[cur_node_id];
- const unsigned num_in_edges = node.in_edges_.size();
- unsigned sampled_edge = 0;
- if (num_in_edges == 1) {
- sampled_edge = node.in_edges_[0];
- } else {
- //prob_t z;
- assert(num_in_edges > 1);
- SampleSet<prob_t> ss;
- for (unsigned j = 0; j < num_in_edges; ++j) {
- const Hypergraph::Edge& edge = hg.edges_[node.in_edges_[j]];
- prob_t p = edge.edge_prob_;
- for (unsigned k = 0; k < edge.tail_nodes_.size(); ++k)
- p *= node_probs[edge.tail_nodes_[k]];
- ss.add(p);
-// cerr << log(ss[j]) << " ||| " << edge.rule_->AsString() << endl;
- //z += p;
- }
-// for (unsigned j = 0; j < num_in_edges; ++j) {
-// const Hypergraph::Edge& edge = hg.edges_[node.in_edges_[j]];
-// cerr << exp(log(ss[j] / z)) << " ||| " << edge.rule_->AsString() << endl;
-// }
-// cerr << " --- \n";
- sampled_edge = node.in_edges_[rng->SelectSample(ss)];
- }
- sampled_deriv->push_back(sampled_edge);
- const Hypergraph::Edge& edge = hg.edges_[sampled_edge];
- for (unsigned j = 0; j < edge.tail_nodes_.size(); ++j) {
- q.push(edge.tail_nodes_[j]);
- }
- }
-// for (unsigned i = 0; i < sampled_deriv->size(); ++i) {
-// cerr << *hg.edges_[(*sampled_deriv)[i]].rule_ << endl;
-// }
-}
-
-void IncrementDerivation(const Hypergraph& hg, const vector<unsigned>& d, UnigramModel* plm, MT19937* rng) {
- for (unsigned i = 0; i < d.size(); ++i)
- plm->Increment(*hg.edges_[d[i]].rule_, rng);
-}
-
-void DecrementDerivation(const Hypergraph& hg, const vector<unsigned>& d, UnigramModel* plm, MT19937* rng) {
- for (unsigned i = 0; i < d.size(); ++i)
- plm->Decrement(*hg.edges_[d[i]].rule_, rng);
-}
-
-prob_t TotalProb(const Hypergraph& hg) {
- return Inside<prob_t, EdgeProb>(hg);
-}
-
-void IncrementLatticePath(const Hypergraph& hg, const vector<unsigned>& d, Lattice* pl) {
- Lattice& lat = *pl;
- for (int i = 0; i < d.size(); ++i) {
- const Hypergraph::Edge& edge = hg.edges_[d[i]];
- if (edge.rule_->Arity() != 0) continue;
- WordID sym = edge.rule_->e_[0];
- vector<LatticeArc>& las = lat[edge.i_];
- int dist = edge.j_ - edge.i_;
- assert(dist > 0);
- for (int j = 0; j < las.size(); ++j) {
- if (las[j].dist2next == dist &&
- las[j].label == sym) {
- las[j].cost += 1;
- }
- }
- }
-}
-
-int main(int argc, char** argv) {
- po::variables_map conf;
-
- InitCommandLine(argc, argv, &conf);
- vector<GrammarPtr> grammars(2);
- grammars[0].reset(new GlueGrammar("S","X"));
- const unsigned samples = conf["samples"].as<unsigned>();
-
- if (conf.count("random_seed"))
- prng.reset(new MT19937(conf["random_seed"].as<uint32_t>()));
- else
- prng.reset(new MT19937);
- MT19937& rng = *prng;
- vector<Lattice> corpuse;
- set<WordID> vocabe;
- cerr << "Reading corpus...\n";
- const unsigned toks = ReadCorpus(conf["input"].as<string>(), &corpuse, &vocabe);
- cerr << "E-corpus size: " << corpuse.size() << " lattices\t (" << vocabe.size() << " word types)\n";
- UnigramModel lm(vocabe.size());
- vector<Hypergraph> hgs(corpuse.size());
- vector<vector<unsigned> > derivs(corpuse.size());
- for (int i = 0; i < corpuse.size(); ++i) {
- grammars[1].reset(new PassThroughGrammar(corpuse[i], "X"));
- ExhaustiveBottomUpParser parser("S", grammars);
- bool res = parser.Parse(corpuse[i], &hgs[i]); // exhaustive parse
- assert(res);
- }
-
- double csamples = 0;
- for (int SS=0; SS < samples; ++SS) {
- const bool is_last = ((samples - 1) == SS);
- prob_t dlh = prob_t::One();
- bool record_sample = (SS > (samples * 1 / 3) && (SS % 5 == 3));
- if (record_sample) csamples++;
- for (int ci = 0; ci < corpuse.size(); ++ci) {
- Lattice& lat = corpuse[ci];
- Hypergraph& hg = hgs[ci];
- vector<unsigned>& d = derivs[ci];
- if (!is_last) DecrementDerivation(hg, d, &lm, &rng);
- for (unsigned i = 0; i < hg.edges_.size(); ++i) {
- TRule& r = *hg.edges_[i].rule_;
- if (r.Arity() != 0)
- hg.edges_[i].edge_prob_ = prob_t::One();
- else
- hg.edges_[i].edge_prob_ = lm.Prob(r);
- }
- if (!is_last) {
- d.clear();
- SampleDerivation(hg, &rng, &d);
- IncrementDerivation(hg, derivs[ci], &lm, &rng);
- } else {
- prob_t p = TotalProb(hg);
- dlh *= p;
- cerr << " p(sentence) = " << log(p) << "\t" << log(dlh) << endl;
- }
- if (record_sample) IncrementLatticePath(hg, derivs[ci], &lat);
- }
- double llh = log(lm.Likelihood());
- cerr << "LLH=" << llh << "\tENTROPY=" << (-llh / log(2) / toks) << "\tPPL=" << pow(2, -llh / log(2) / toks) << endl;
- if (SS % 10 == 9) lm.ResampleHyperparameters(&rng);
- if (is_last) {
- double z = log(dlh);
- cerr << "TOTAL_PROB=" << z << "\tENTROPY=" << (-z / log(2) / toks) << "\tPPL=" << pow(2, -z / log(2) / toks) << endl;
- }
- }
- cerr << lm.crp << endl;
- cerr << lm.glue << endl;
- for (int i = 0; i < corpuse.size(); ++i) {
- for (int j = 0; j < corpuse[i].size(); ++j)
- for (int k = 0; k < corpuse[i][j].size(); ++k) {
- corpuse[i][j][k].cost /= csamples;
- corpuse[i][j][k].cost += 1e-3;
- corpuse[i][j][k].cost = log(corpuse[i][j][k].cost);
- }
- cout << HypergraphIO::AsPLF(corpuse[i]) << endl;
- }
- return 0;
-}
-
generated by cgit v1.2.3 (git 2.39.1) at 2024-11-11 02:58:36 +0000