few small fixes of alignment tools, add new orthographic similarity feature for word aligner, final naming of directories, libraries in cdec

1 files changed, 0 insertions, 507 deletions

diff --git a/src/cdec.cc b/src/cdec.cc
deleted file mode 100644
index 6185c79b..00000000
--- a/src/cdec.cc
+++ /dev/null
@@ -1,507 +0,0 @@
-#include <iostream>
-#include <fstream>
-#include <tr1/unordered_map>
-#include <tr1/unordered_set>
-
-#include <boost/shared_ptr.hpp>
-#include <boost/program_options.hpp>
-#include <boost/program_options/variables_map.hpp>
-
-#include "timing_stats.h"
-#include "translator.h"
-#include "phrasebased_translator.h"
-#include "aligner.h"
-#include "stringlib.h"
-#include "forest_writer.h"
-#include "hg_io.h"
-#include "filelib.h"
-#include "sampler.h"
-#include "sparse_vector.h"
-#include "lexcrf.h"
-#include "csplit.h"
-#include "weights.h"
-#include "tdict.h"
-#include "ff.h"
-#include "ff_factory.h"
-#include "hg_intersect.h"
-#include "apply_models.h"
-#include "viterbi.h"
-#include "kbest.h"
-#include "inside_outside.h"
-#include "exp_semiring.h"
-#include "sentence_metadata.h"
-
-using namespace std;
-using namespace std::tr1;
-using boost::shared_ptr;
-namespace po = boost::program_options;
-
-// some globals ...
-boost::shared_ptr<RandomNumberGenerator<boost::mt19937> > rng;
-
-namespace Hack { void MaxTrans(const Hypergraph& in, int beam_size); }
-
-void ShowBanner() {
-  cerr << "cdec v1.0 (c) 2009 by Chris Dyer\n";
-}
-
-void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
-  po::options_description opts("Configuration options");
-  opts.add_options()
-        ("formalism,f",po::value<string>(),"Translation formalism; values include SCFG, FST, PB, LexCRF (lexical translation model), CSplit (compound splitting)")
-        ("input,i",po::value<string>()->default_value("-"),"Source file")
-        ("grammar,g",po::value<vector<string> >()->composing(),"Either SCFG grammar file(s) or phrase tables file(s)")
-        ("weights,w",po::value<string>(),"Feature weights file")
-        ("feature_function,F",po::value<vector<string> >()->composing(), "Additional feature function(s) (-L for list)")
-        ("list_feature_functions,L","List available feature functions")
-        ("add_pass_through_rules,P","Add rules to translate OOV words as themselves")
-	("k_best,k",po::value<int>(),"Extract the k best derivations")
-	("unique_k_best,r", "Unique k-best translation list")
-        ("aligner,a", "Run as a word/phrase aligner (src & ref required)")
-        ("cubepruning_pop_limit,K",po::value<int>()->default_value(200), "Max number of pops from the candidate heap at each node")
-        ("goal",po::value<string>()->default_value("S"),"Goal symbol (SCFG & FST)")
-        ("scfg_extra_glue_grammar", po::value<string>(), "Extra glue grammar file (Glue grammars apply when i=0 but have no other span restrictions)")
-        ("scfg_no_hiero_glue_grammar,n", "No Hiero glue grammar (nb. by default the SCFG decoder adds Hiero glue rules)")
-        ("scfg_default_nt,d",po::value<string>()->default_value("X"),"Default non-terminal symbol in SCFG")
-        ("scfg_max_span_limit,S",po::value<int>()->default_value(10),"Maximum non-terminal span limit (except \"glue\" grammar)")
-	("show_tree_structure,T", "Show the Viterbi derivation structure")
-        ("show_expected_length", "Show the expected translation length under the model")
-        ("show_partition,z", "Compute and show the partition (inside score)")
-        ("beam_prune", po::value<double>(), "Prune paths from +LM forest")
-        ("csplit_output_plf", "(Compound splitter) Output lattice in PLF format")
-        ("csplit_preserve_full_word", "(Compound splitter) Always include the unsegmented form in the output lattice")
-        ("extract_rules", po::value<string>(), "Extract the rules used in translation (de-duped) to this file")
-        ("graphviz","Show (constrained) translation forest in GraphViz format")
-        ("max_translation_beam,x", po::value<int>(), "Beam approximation to get max translation from the chart")
-        ("max_translation_sample,X", po::value<int>(), "Sample the max translation from the chart")
-        ("pb_max_distortion,D", po::value<int>()->default_value(4), "Phrase-based decoder: maximum distortion")
-        ("gradient,G","Compute d log p(e|f) / d lambda_i and write to STDOUT (src & ref required)")
-        ("feature_expectations","Write feature expectations for all features in chart (**OBJ** will be the partition)")
-        ("vector_format",po::value<string>()->default_value("b64"), "Sparse vector serialization format for feature expectations or gradients, includes (text or b64)")
-        ("combine_size,C",po::value<int>()->default_value(1), "When option -G is used, process this many sentence pairs before writing the gradient (1=emit after every sentence pair)")
-        ("forest_output,O",po::value<string>(),"Directory to write forests to")
-        ("minimal_forests,m","Write minimal forests (excludes Rule information). Such forests can be used for ML/MAP training, but not rescoring, etc.");
-  po::options_description clo("Command line options");
-  clo.add_options()
-        ("config,c", po::value<string>(), "Configuration file")
-        ("help,h", "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")) {
-    const string cfg = (*conf)["config"].as<string>();
-    cerr << "Configuration file: " << cfg << endl;
-    ifstream config(cfg.c_str());
-    po::store(po::parse_config_file(config, dconfig_options), *conf);
-  }
-  po::notify(*conf);
-
-  if (conf->count("list_feature_functions")) {
-    cerr << "Available feature functions (specify with -F):\n";
-    global_ff_registry->DisplayList();
-    cerr << endl;
-    exit(1);
-  }
-
-  if (conf->count("help") || conf->count("formalism") == 0) {
-    cerr << dcmdline_options << endl;
-    exit(1);
-  }
-
-  const string formalism = LowercaseString((*conf)["formalism"].as<string>());
-  if (formalism != "scfg" && formalism != "fst" && formalism != "lexcrf" && formalism != "pb" && formalism != "csplit") {
-    cerr << "Error: --formalism takes only 'scfg', 'fst', 'pb', 'csplit' or 'lexcrf'\n";
-    cerr << dcmdline_options << endl;
-    exit(1);
-  }
-}
-
-// TODO move out of cdec into some sampling decoder file
-void SampleRecurse(const Hypergraph& hg, const vector<SampleSet>& ss, int n, vector<WordID>* out) {
-  const SampleSet& s = ss[n];
-  int i = rng->SelectSample(s);
-  const Hypergraph::Edge& edge = hg.edges_[hg.nodes_[n].in_edges_[i]];
-  vector<vector<WordID> > ants(edge.tail_nodes_.size());
-  for (int j = 0; j < ants.size(); ++j)
-    SampleRecurse(hg, ss, edge.tail_nodes_[j], &ants[j]);
-
-  vector<const vector<WordID>*> pants(ants.size());
-  for (int j = 0; j < ants.size(); ++j) pants[j] = &ants[j];
-  edge.rule_->ESubstitute(pants, out);
-}
-
-struct SampleSort {
-  bool operator()(const pair<int,string>& a, const pair<int,string>& b) const {
-    return a.first > b.first;
-  }
-};
-
-// TODO move out of cdec into some sampling decoder file
-void MaxTranslationSample(Hypergraph* hg, const int samples, const int k) {
-  unordered_map<string, int, boost::hash<string> > m;
-  hg->PushWeightsToGoal();
-  const int num_nodes = hg->nodes_.size();
-  vector<SampleSet> ss(num_nodes);
-  for (int i = 0; i < num_nodes; ++i) {
-    SampleSet& s = ss[i];
-    const vector<int>& in_edges = hg->nodes_[i].in_edges_;
-    for (int j = 0; j < in_edges.size(); ++j) {
-      s.add(hg->edges_[in_edges[j]].edge_prob_);
-    }
-  }
-  for (int i = 0; i < samples; ++i) {
-    vector<WordID> yield;
-    SampleRecurse(*hg, ss, hg->nodes_.size() - 1, &yield);
-    const string trans = TD::GetString(yield);
-    ++m[trans];
-  }
-  vector<pair<int, string> > dist;
-  for (unordered_map<string, int, boost::hash<string> >::iterator i = m.begin();
-         i != m.end(); ++i) {
-    dist.push_back(make_pair(i->second, i->first));
-  }
-  sort(dist.begin(), dist.end(), SampleSort());
-  if (k) {
-    for (int i = 0; i < k; ++i)
-      cout << dist[i].first << " ||| " << dist[i].second << endl;
-  } else {
-    cout << dist[0].second << endl;
-  }
-}
-
-// TODO decoder output should probably be moved to another file
-void DumpKBest(const int sent_id, const Hypergraph& forest, const int k, const bool unique) {
-  if (unique) {
-    KBest::KBestDerivations<vector<WordID>, ESentenceTraversal, KBest::FilterUnique> kbest(forest, k);
-    for (int i = 0; i < k; ++i) {
-      const KBest::KBestDerivations<vector<WordID>, ESentenceTraversal, KBest::FilterUnique>::Derivation* d =
-        kbest.LazyKthBest(forest.nodes_.size() - 1, i);
-      if (!d) break;
-      cout << sent_id << " ||| " << TD::GetString(d->yield) << " ||| "
-           << d->feature_values << " ||| " << log(d->score) << endl;
-    }
-  } else {
-    KBest::KBestDerivations<vector<WordID>, ESentenceTraversal> kbest(forest, k);
-    for (int i = 0; i < k; ++i) {
-      const KBest::KBestDerivations<vector<WordID>, ESentenceTraversal>::Derivation* d =
-        kbest.LazyKthBest(forest.nodes_.size() - 1, i);
-      if (!d) break;
-      cout << sent_id << " ||| " << TD::GetString(d->yield) << " ||| "
-           << d->feature_values << " ||| " << log(d->score) << endl;
-    }
-  }
-}
-
-struct ELengthWeightFunction {
-  double operator()(const Hypergraph::Edge& e) const {
-    return e.rule_->ELength() - e.rule_->Arity();
-  }
-};
-
-
-struct TRPHash {
-  size_t operator()(const TRulePtr& o) const { return reinterpret_cast<size_t>(o.get()); }
-};
-static void ExtractRulesDedupe(const Hypergraph& hg, ostream* os) {
-  static unordered_set<TRulePtr, TRPHash> written;
-  for (int i = 0; i < hg.edges_.size(); ++i) {
-    const TRulePtr& rule = hg.edges_[i].rule_;
-    if (written.insert(rule).second) {
-      (*os) << rule->AsString() << endl;
-    }
-  }
-}
-
-void register_feature_functions();
-
-int main(int argc, char** argv) {
-  global_ff_registry.reset(new FFRegistry);
-  register_feature_functions();
-  ShowBanner();
-  po::variables_map conf;
-  InitCommandLine(argc, argv, &conf);
-  const bool write_gradient = conf.count("gradient");
-  const bool feature_expectations = conf.count("feature_expectations");
-  if (write_gradient && feature_expectations) {
-    cerr << "You can only specify --gradient or --feature_expectations, not both!\n";
-    exit(1);
-  }
-  const bool output_training_vector = (write_gradient || feature_expectations);
-
-  boost::shared_ptr<Translator> translator;
-  const string formalism = LowercaseString(conf["formalism"].as<string>());
-  const bool csplit_preserve_full_word = conf.count("csplit_preserve_full_word");
-  if (csplit_preserve_full_word &&
-      (formalism != "csplit" || !conf.count("beam_prune"))) {
-    cerr << "--csplit_preserve_full_word should only be "
-         << "used with csplit AND --beam_prune!\n";
-    exit(1);
-  }
-  const bool csplit_output_plf = conf.count("csplit_output_plf");
-  if (csplit_output_plf && formalism != "csplit") {
-    cerr << "--csplit_output_plf should only be used with csplit!\n";
-    exit(1);
-  }
-
-  if (formalism == "scfg")
-    translator.reset(new SCFGTranslator(conf));
-  else if (formalism == "fst")
-    translator.reset(new FSTTranslator(conf));
-  else if (formalism == "pb")
-    translator.reset(new PhraseBasedTranslator(conf));
-  else if (formalism == "csplit")
-    translator.reset(new CompoundSplit(conf));
-  else if (formalism == "lexcrf")
-    translator.reset(new LexicalCRF(conf));
-  else
-    assert(!"error");
-
-  vector<double> feature_weights;
-  Weights w;
-  if (conf.count("weights")) {
-    w.InitFromFile(conf["weights"].as<string>());
-    feature_weights.resize(FD::NumFeats());
-    w.InitVector(&feature_weights);
-  }
-
-  // set up additional scoring features
-  vector<shared_ptr<FeatureFunction> > pffs;
-  vector<const FeatureFunction*> late_ffs;
-  if (conf.count("feature_function") > 0) {
-    const vector<string>& add_ffs = conf["feature_function"].as<vector<string> >();
-    for (int i = 0; i < add_ffs.size(); ++i) {
-      string ff, param;
-      SplitCommandAndParam(add_ffs[i], &ff, &param);
-      cerr << "Feature: " << ff;
-      if (param.size() > 0) cerr << " (with config parameters '" << param << "')\n";
-      else cerr << " (no config parameters)\n";
-      shared_ptr<FeatureFunction> pff = global_ff_registry->Create(ff, param);
-      if (!pff) { exit(1); }
-      // TODO check that multiple features aren't trying to set the same fid
-      pffs.push_back(pff);
-      late_ffs.push_back(pff.get());
-    }
-  }
-  ModelSet late_models(feature_weights, late_ffs);
-
-  const int sample_max_trans = conf.count("max_translation_sample") ?
-    conf["max_translation_sample"].as<int>() : 0;
-  if (sample_max_trans)
-    rng.reset(new RandomNumberGenerator<boost::mt19937>);
-  const bool aligner_mode = conf.count("aligner");
-  const bool minimal_forests = conf.count("minimal_forests");
-  const bool graphviz = conf.count("graphviz");
-  const bool encode_b64 = conf["vector_format"].as<string>() == "b64";
-  const bool kbest = conf.count("k_best");
-  const bool unique_kbest = conf.count("unique_k_best");
-  shared_ptr<WriteFile> extract_file;
-  if (conf.count("extract_rules"))
-    extract_file.reset(new WriteFile(conf["extract_rules"].as<string>()));
-
-  int combine_size = conf["combine_size"].as<int>();
-  if (combine_size < 1) combine_size = 1;
-  const string input = conf["input"].as<string>();
-  cerr << "Reading input from " << ((input == "-") ? "STDIN" : input.c_str()) << endl;
-  ReadFile in_read(input);
-  istream *in = in_read.stream();
-  assert(*in);
-
-  SparseVector<double> acc_vec;  // accumulate gradient
-  double acc_obj = 0; // accumulate objective
-  int g_count = 0;    // number of gradient pieces computed
-  int sent_id = -1;         // line counter
-
-  while(*in) {
-    Timer::Summarize();
-    ++sent_id;
-    string buf;
-    getline(*in, buf);
-    if (buf.empty()) continue;
-    map<string, string> sgml;
-    ProcessAndStripSGML(&buf, &sgml);
-    if (sgml.find("id") != sgml.end())
-      sent_id = atoi(sgml["id"].c_str());
-
-    cerr << "\nINPUT: ";
-    if (buf.size() < 100)
-      cerr << buf << endl;
-    else {
-     size_t x = buf.rfind(" ", 100);
-     if (x == string::npos) x = 100;
-     cerr << buf.substr(0, x) << " ..." << endl;
-    }
-    cerr << "  id = " << sent_id << endl;
-    string to_translate;
-    Lattice ref;
-    ParseTranslatorInputLattice(buf, &to_translate, &ref);
-    const bool has_ref = ref.size() > 0;
-    SentenceMetadata smeta(sent_id, ref);
-    const bool hadoop_counters = (write_gradient);
-    Hypergraph forest;          // -LM forest
-    Timer t("Translation");
-    if (!translator->Translate(to_translate, &smeta, feature_weights, &forest)) {
-      cerr << "  NO PARSE FOUND.\n";
-      if (hadoop_counters)
-        cerr << "reporter:counter:UserCounters,FParseFailed,1" << endl;
-      cout << endl << flush;
-      continue;
-    }
-    cerr << "  -LM forest (nodes/edges): " << forest.nodes_.size() << '/' << forest.edges_.size() << endl;
-    cerr << "  -LM forest       (paths): " << forest.NumberOfPaths() << endl;
-    if (conf.count("show_expected_length")) {
-      const PRPair<double, double> res =
-        Inside<PRPair<double, double>,
-               PRWeightFunction<double, EdgeProb, double, ELengthWeightFunction> >(forest);
-      cerr << "  Expected length  (words): " << res.r / res.p << "\t" << res << endl;
-    }
-    if (conf.count("show_partition")) {
-      const prob_t z = Inside<prob_t, EdgeProb>(forest);
-      cerr << "  -LM partition     log(Z): " << log(z) << endl;
-    }
-    if (extract_file)
-      ExtractRulesDedupe(forest, extract_file->stream());
-    vector<WordID> trans;
-    const prob_t vs = ViterbiESentence(forest, &trans);
-    cerr << "  -LM Viterbi: " << TD::GetString(trans) << endl;
-    if (conf.count("show_tree_structure"))
-      cerr << "  -LM    tree: " << ViterbiETree(forest) << endl;;
-    cerr << "  -LM Viterbi: " << log(vs) << endl;
-
-    bool has_late_models = !late_models.empty();
-    if (has_late_models) {
-      forest.Reweight(feature_weights);
-      forest.SortInEdgesByEdgeWeights();
-      Hypergraph lm_forest;
-      int cubepruning_pop_limit = conf["cubepruning_pop_limit"].as<int>();
-      ApplyModelSet(forest,
-                    smeta,
-                    late_models,
-                    PruningConfiguration(cubepruning_pop_limit),
-                    &lm_forest);
-      forest.swap(lm_forest);
-      forest.Reweight(feature_weights);
-      trans.clear();
-      ViterbiESentence(forest, &trans);
-      cerr << "  +LM forest (nodes/edges): " << forest.nodes_.size() << '/' << forest.edges_.size() << endl;
-      cerr << "  +LM forest       (paths): " << forest.NumberOfPaths() << endl;
-      cerr << "  +LM Viterbi: " << TD::GetString(trans) << endl;
-    }
-    if (conf.count("beam_prune")) {
-      vector<bool> preserve_mask(forest.edges_.size(), false);
-      if (csplit_preserve_full_word)
-        preserve_mask[CompoundSplit::GetFullWordEdgeIndex(forest)] = true;
-      forest.BeamPruneInsideOutside(1.0, false, conf["beam_prune"].as<double>(), &preserve_mask);
-      cerr << "  Pruned forest    (paths): " << forest.NumberOfPaths() << endl;
-    }
-
-    if (conf.count("forest_output") && !has_ref) {
-      ForestWriter writer(conf["forest_output"].as<string>(), sent_id);
-      assert(writer.Write(forest, minimal_forests));
-    }
-
-    if (sample_max_trans) {
-      MaxTranslationSample(&forest, sample_max_trans, conf.count("k_best") ? conf["k_best"].as<int>() : 0);
-    } else {
-      if (kbest) {
-        DumpKBest(sent_id, forest, conf["k_best"].as<int>(), unique_kbest);
-      } else if (csplit_output_plf) {
-        cout << HypergraphIO::AsPLF(forest, false) << endl;
-      } else {
-        if (!graphviz && !has_ref) {
-          cout << TD::GetString(trans) << endl << flush;
-        }
-      }
-    }
-
-    const int max_trans_beam_size = conf.count("max_translation_beam") ?
-      conf["max_translation_beam"].as<int>() : 0;
-    if (max_trans_beam_size) {
-      Hack::MaxTrans(forest, max_trans_beam_size);
-      continue;
-    }
-
-    if (graphviz && !has_ref) forest.PrintGraphviz();
-
-    // the following are only used if write_gradient is true!
-    SparseVector<double> full_exp, ref_exp, gradient;
-    double log_z = 0, log_ref_z = 0;
-    if (write_gradient)
-      log_z = log(
-        InsideOutside<prob_t, EdgeProb, SparseVector<double>, EdgeFeaturesWeightFunction>(forest, &full_exp));
-
-    if (has_ref) {
-      if (HG::Intersect(ref, &forest)) {
-        cerr << "  Constr. forest (nodes/edges): " << forest.nodes_.size() << '/' << forest.edges_.size() << endl;
-        cerr << "  Constr. forest       (paths): " << forest.NumberOfPaths() << endl;
-        forest.Reweight(feature_weights);
-        cerr << "  Constr. VitTree: " << ViterbiFTree(forest) << endl;
-	if (hadoop_counters)
-          cerr << "reporter:counter:UserCounters,SentencePairsParsed,1" << endl;
-        if (conf.count("show_partition")) {
-           const prob_t z = Inside<prob_t, EdgeProb>(forest);
-           cerr << "  Contst. partition  log(Z): " << log(z) << endl;
-        }
-        //DumpKBest(sent_id, forest, 1000);
-        if (conf.count("forest_output")) {
-          ForestWriter writer(conf["forest_output"].as<string>(), sent_id);
-          assert(writer.Write(forest, minimal_forests));
-        }
-        if (aligner_mode && !output_training_vector)
-          AlignerTools::WriteAlignment(to_translate, ref, forest);
-        if (write_gradient) {
-          log_ref_z = log(
-            InsideOutside<prob_t, EdgeProb, SparseVector<double>, EdgeFeaturesWeightFunction>(forest, &ref_exp));
-          if (log_z < log_ref_z) {
-            cerr << "DIFF. ERR! log_z < log_ref_z: " << log_z << " " << log_ref_z << endl;
-            exit(1);
-          }
-          //cerr << "FULL: " << full_exp << endl;
-          //cerr << " REF: " << ref_exp << endl;
-          ref_exp -= full_exp;
-          acc_vec += ref_exp;
-          acc_obj += (log_z - log_ref_z);
-        }
-        if (feature_expectations) {
-          acc_obj += log(
-            InsideOutside<prob_t, EdgeProb, SparseVector<double>, EdgeFeaturesWeightFunction>(forest, &ref_exp));
-          acc_vec += ref_exp;
-        }
-
-        if (output_training_vector) {
-          ++g_count;
-          if (g_count % combine_size == 0) {
-            if (encode_b64) {
-              cout << "0\t";
-              B64::Encode(acc_obj, acc_vec, &cout);
-              cout << endl << flush;
-            } else {
-              cout << "0\t**OBJ**=" << acc_obj << ';' <<  acc_vec << endl << flush;
-            }
-            acc_vec.clear();
-            acc_obj = 0;
-          }
-        }
-        if (conf.count("graphviz")) forest.PrintGraphviz();
-      } else {
-        cerr << "  REFERENCE UNREACHABLE.\n";
-        if (write_gradient) {
-	  if (hadoop_counters)
-            cerr << "reporter:counter:UserCounters,EFParseFailed,1" << endl;
-          cout << endl << flush;
-	}
-      }
-    }
-  }
-  if (output_training_vector && !acc_vec.empty()) {
-    if (encode_b64) {
-      cout << "0\t";
-      B64::Encode(acc_obj, acc_vec, &cout);
-      cout << endl << flush;
-    } else {
-      cout << "0\t**OBJ**=" << acc_obj << ';' << acc_vec << endl << flush;
-    }
-  }
-}
-