cdec cleanup, remove bayesian stuff, parsing stuff

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;
-}
-