fix

1 files changed, 11 insertions, 7 deletions

diff --git a/training/dtrain/dtrain.cc b/training/dtrain/dtrain.cc
index 2bb4ec98..149f87d4 100644
--- a/training/dtrain/dtrain.cc
+++ b/training/dtrain/dtrain.cc
@@ -34,8 +34,7 @@ dtrain_init(int argc, char** argv, po::variables_map* cfg)
     ("scale_bleu_diff",   po::value<bool>()->zero_tokens(),                      "learning rate <- bleu diff of a misranked pair")
     ("loss_margin",       po::value<weight_t>()->default_value(0.),  "update if no error in pref pair but model scores this near")
     ("max_pairs",         po::value<unsigned>()->default_value(std::numeric_limits<unsigned>::max()), "max. # of pairs per Sent.")
-    ("noup",              po::value<bool>()->zero_tokens(),                                               "do not update weights")
-    ("pair_stats",        po::value<bool>()->zero_tokens(), "stats about correctly ranked/misranked pairs even if loss_margin=0 and gamma=0");
+    ("noup",              po::value<bool>()->zero_tokens(),                                               "do not update weights");
   po::options_description cl("Command Line Options");
   cl.add_options()
     ("config,c",         po::value<string>(),              "dtrain config file")
@@ -125,10 +124,7 @@ main(int argc, char** argv)
   vector<string> print_weights;
   if (cfg.count("print_weights"))
     boost::split(print_weights, cfg["print_weights"].as<string>(), boost::is_any_of(" "));
-  bool pair_stats = false;
-  if (cfg.count("pair_stats")) pair_stats = true;
-  bool faster_perceptron = false;
-  if (gamma==0 && loss_margin==0 && !pair_stats) faster_perceptron = true;
+
 
   // setup decoder
   register_feature_functions();
@@ -185,6 +181,11 @@ main(int argc, char** argv)
   weight_t eta = cfg["learning_rate"].as<weight_t>();
   weight_t gamma = cfg["gamma"].as<weight_t>();
 
+  // faster perceptron: consider only misranked pairs, see
+  // DO NOT ENABLE  WITH SVM (gamma > 0) OR loss_margin!
+  bool faster_perceptron = false;
+  if (gamma==0 && loss_margin==0) faster_perceptron = true;
+
   // l1 regularization
   bool l1naive = false;
   bool l1clip = false;
@@ -232,6 +233,7 @@ main(int argc, char** argv)
     else cerr << setw(25) << "learning rate " << "bleu diff" << endl;
     cerr << setw(25) << "gamma " << gamma << endl;
     cerr << setw(25) << "loss margin " << loss_margin << endl;
+    cerr << setw(25) << "faster perceptron " << faster_perceptron << endl;
     cerr << setw(25) << "pairs " << "'" << pair_sampling << "'" << endl;
     if (pair_sampling == "XYX")
       cerr << setw(25) << "hi lo " << hi_lo << endl;
@@ -461,7 +463,9 @@ main(int argc, char** argv)
     cerr << _np << " 1best avg model score: " << model_avg;
     cerr << _p << " (" << model_diff << ")" << endl;
     cerr << "           avg # pairs: ";
-    cerr << _np << npairs/(float)in_sz << endl;
+    cerr << _np << npairs/(float)in_sz;
+    if (faster_perceptron) cerr << " (meaningless)";
+    cerr << endl;
     cerr << "        avg # rank err: ";
     cerr << rank_errors/(float)in_sz << endl;
     cerr << "     avg # margin viol: ";