1 files changed, 138 insertions, 0 deletions
diff --git a/mteval/mbr_kbest.cc b/mteval/mbr_kbest.cc
new file mode 100644
index 00000000..2867b36b
--- /dev/null
+++ b/mteval/mbr_kbest.cc
@@ -0,0 +1,138 @@
+#include <iostream>
+#include <vector>
+
+#include <boost/program_options.hpp>
+
+#include "prob.h"
+#include "tdict.h"
+#include "scorer.h"
+#include "filelib.h"
+#include "stringlib.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");
+  opts.add_options()
+        ("scale,a",po::value<double>()->default_value(1.0), "Posterior scaling factor (alpha)")
+        ("loss_function,l",po::value<string>()->default_value("bleu"), "Loss function")
+        ("input,i",po::value<string>()->default_value("-"), "File to read k-best lists from")
+        ("output_list,L", "Show reranked list as output")
+        ("help,h", "Help");
+  po::options_description dcmdline_options;
+  dcmdline_options.add(opts);
+  po::store(parse_command_line(argc, argv, dcmdline_options), *conf);
+  bool flag = false;
+  if (flag || conf->count("help")) {
+    cerr << dcmdline_options << endl;
+    exit(1);
+  }
+}
+
+struct LossComparer {
+  bool operator()(const pair<vector<WordID>, double>& a, const pair<vector<WordID>, double>& b) const {
+    return a.second < b.second;
+  }
+};
+
+bool ReadKBestList(istream* in, string* sent_id, vector<pair<vector<WordID>, prob_t> >* list) {
+  static string cache_id;
+  static pair<vector<WordID>, prob_t> cache_pair;
+  list->clear();
+  string cur_id;
+  if (cache_pair.first.size() > 0) {
+    list->push_back(cache_pair);
+    cur_id = cache_id;
+    cache_pair.first.clear();
+  }
+  string line;
+  string tstr;
+  while(*in) {
+    getline(*in, line);
+    if (line.empty()) continue;
+    size_t p1 = line.find(" ||| ");
+    if (p1 == string::npos) { cerr << "Bad format: " << line << endl; abort(); }
+    size_t p2 = line.find(" ||| ", p1 + 4);
+    if (p2 == string::npos) { cerr << "Bad format: " << line << endl; abort(); }
+    size_t p3 = line.rfind(" ||| ");
+    cache_id = line.substr(0, p1);
+    tstr = line.substr(p1 + 5, p2 - p1 - 5);
+    double val = strtod(line.substr(p3 + 5).c_str(), NULL);
+    TD::ConvertSentence(tstr, &cache_pair.first);
+    cache_pair.second.logeq(val);
+    if (cur_id.empty()) cur_id = cache_id;
+    if (cur_id == cache_id) {
+      list->push_back(cache_pair);
+      *sent_id = cur_id;
+      cache_pair.first.clear();
+    } else { break; }
+  }
+  return !list->empty();
+}
+
+int main(int argc, char** argv) {
+  po::variables_map conf;
+  InitCommandLine(argc, argv, &conf);
+  const string metric = conf["loss_function"].as<string>();
+  const bool output_list = conf.count("output_list") > 0;
+  const string file = conf["input"].as<string>();
+  const double mbr_scale = conf["scale"].as<double>();
+  cerr << "Posterior scaling factor (alpha) = " << mbr_scale << endl;
+
+  ScoreType type = ScoreTypeFromString(metric);
+  vector<pair<vector<WordID>, prob_t> > list;
+  ReadFile rf(file);
+  string sent_id;
+  while(ReadKBestList(rf.stream(), &sent_id, &list)) {
+    vector<prob_t> joints(list.size());
+    const prob_t max_score = pow(list.front().second, mbr_scale);
+    prob_t marginal = prob_t::Zero();
+    for (int i = 0 ; i < list.size(); ++i) {
+      const prob_t joint = pow(list[i].second, mbr_scale) / max_score;
+      joints[i] = joint;
+      // cerr << "list[" << i << "] joint=" << log(joint) << endl;
+      marginal += joint;
+    }
+    int mbr_idx = -1;
+    vector<double> mbr_scores(output_list ? list.size() : 0);
+    double mbr_loss = numeric_limits<double>::max();
+    for (int i = 0 ; i < list.size(); ++i) {
+      vector<vector<WordID> > refs(1, list[i].first);
+      //cerr << i << ": " << list[i].second <<"\t" << TD::GetString(list[i].first) << endl;
+      ScorerP scorer = SentenceScorer::CreateSentenceScorer(type, refs);
+      double wl_acc = 0;
+      for (int j = 0; j < list.size(); ++j) {
+        if (i != j) {
+          ScoreP s = scorer->ScoreCandidate(list[j].first);
+          double loss = 1.0 - s->ComputeScore();
+          if (type == TER || type == AER) loss = 1.0 - loss;
+          double weighted_loss = loss * (joints[j] / marginal);
+          wl_acc += weighted_loss;
+          if ((!output_list) && wl_acc > mbr_loss) break;
+        }
+      }
+      if (output_list) mbr_scores[i] = wl_acc;
+      if (wl_acc < mbr_loss) {
+        mbr_loss = wl_acc;
+        mbr_idx = i;
+      }
+    }
+    // cerr << "ML translation: " << TD::GetString(list[0].first) << endl;
+    cerr << "MBR Best idx: " << mbr_idx << endl;
+    if (output_list) {
+      for (int i = 0; i < list.size(); ++i)
+        list[i].second.logeq(mbr_scores[i]);
+      sort(list.begin(), list.end(), LossComparer());
+      for (int i = 0; i < list.size(); ++i)
+        cout << sent_id << " ||| "
+             << TD::GetString(list[i].first) << " ||| "
+             << log(list[i].second) << endl;
+    } else {
+      cout << TD::GetString(list[mbr_idx].first) << endl;
+    }
+  }
+  return 0;
+}
+