spare a arg

1 files changed, 6 insertions, 6 deletions

diff --git a/dtrain/dtrain.cc b/dtrain/dtrain.cc
index e07b9307..9db8516c 100644
--- a/dtrain/dtrain.cc
+++ b/dtrain/dtrain.cc
@@ -25,12 +25,12 @@ dtrain_init(int argc, char** argv, po::variables_map* cfg)
     ("scorer",          po::value<string>()->default_value("stupid_bleu"),        "scoring: bleu, stupid_, smooth_, approx_")
     ("learning_rate",   po::value<weight_t>()->default_value(0.0001),                                        "learning rate")
     ("gamma",           po::value<weight_t>()->default_value(0),                          "gamma for SVM (0 for perceptron)")
-    ("select_weights",  po::value<string>()->default_value("last"), "output 'best' or 'last' weights ('VOID' to throw away)")
+    ("select_weights",  po::value<string>()->default_value("last"),  "output best, last, avg weights ('VOID' to throw away)")
     ("rescale",         po::value<bool>()->zero_tokens(),                           "rescale weight vector after each input")
     ("l1_reg",          po::value<string>()->default_value("none"),   "apply l1 regularization as in 'Tsuroka et al' (2010)")
     ("l1_reg_strength", po::value<weight_t>(),                                                  "l1 regularization strength")
     ("funny",           po::value<bool>()->zero_tokens(),                      "include correctly ranked pairs into updates")
-    ("average",         po::value<bool>()->zero_tokens(),                "output weight vector is average of all iterations")
+    ("fselect",         po::value<weight_t>()->default_value(-1),        "select top x percent of features after each epoch")     
 #ifdef DTRAIN_LOCAL
     ("refs,r",         po::value<string>(),                                                       "references in local mode")
 #endif
@@ -81,7 +81,7 @@ dtrain_init(int argc, char** argv, po::variables_map* cfg)
     return false;
   }
   if ((*cfg)["select_weights"].as<string>() != "last" && (*cfg)["select_weights"].as<string>() != "best" &&
-        (*cfg)["select_weights"].as<string>() != "VOID") {
+        (*cfg)["select_weights"].as<string>() != "avg" && (*cfg)["select_weights"].as<string>() != "VOID") {
     cerr << "Wrong 'select_weights' param: '" << (*cfg)["select_weights"].as<string>() << "', use 'last' or 'best'." << endl;
     return false;
   }
@@ -116,9 +116,6 @@ main(int argc, char** argv)
   bool funny = false;
   if (cfg.count("funny"))
     funny = true;
-  bool average = false;
-  if (cfg.count("average"))
-    average = true;
 
   const unsigned k = cfg["k"].as<unsigned>();
   const unsigned N = cfg["N"].as<unsigned>(); 
@@ -129,6 +126,9 @@ main(int argc, char** argv)
   const string pair_sampling = cfg["pair_sampling"].as<string>();
   const score_t pair_threshold = cfg["pair_threshold"].as<score_t>();
   const string select_weights = cfg["select_weights"].as<string>();
+  bool average = false;
+  if (select_weights == "avg")
+    average = true;
   vector<string> print_weights;
   if (cfg.count("print_weights"))
     boost::split(print_weights, cfg["print_weights"].as<string>(), boost::is_any_of(" "));