epoch averaging

1 files changed, 20 insertions, 5 deletions

diff --git a/dtrain/dtrain.cc b/dtrain/dtrain.cc
index 581c985a..e07b9307 100644
--- a/dtrain/dtrain.cc
+++ b/dtrain/dtrain.cc
@@ -30,6 +30,7 @@ dtrain_init(int argc, char** argv, po::variables_map* cfg)
     ("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")
 #ifdef DTRAIN_LOCAL
     ("refs,r",         po::value<string>(),                                                       "references in local mode")
 #endif
@@ -115,6 +116,9 @@ 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>(); 
@@ -167,7 +171,7 @@ main(int argc, char** argv)
 
   // init weights
   vector<weight_t>& dense_weights = decoder.CurrentWeightVector();
-  SparseVector<weight_t> lambdas, cumulative_penalties;
+  SparseVector<weight_t> lambdas, cumulative_penalties, w_average;
   if (cfg.count("input_weights")) Weights::InitFromFile(cfg["input_weights"].as<string>(), &dense_weights);
   Weights::InitSparseVector(dense_weights, &lambdas);
 
@@ -480,6 +484,8 @@ if (false) {
 
   } // input loop
 
+  if (average) w_average += lambdas; 
+
   if (scorer_str == "approx_bleu") scorer->Reset();
 
   if (t == 0) {
@@ -572,20 +578,29 @@ if (false) {
 
   } // outer loop
 
+  if (average) w_average /= (weight_t)T;
+
 #ifndef DTRAIN_LOCAL
   unlink(grammar_buf_fn.c_str());
 #endif
 
   if (!noup) {
     if (!quiet) cerr << endl << "Writing weights file to '" << output_fn << "' ..." << endl;
-    if (select_weights == "last") { // last
+    if (select_weights == "last" || average) { // last, average
       WriteFile of(output_fn); // works with '-'
       ostream& o = *of.stream();
       o.precision(17);
       o << _np;
-      for (SparseVector<weight_t>::const_iterator it = lambdas.begin(); it != lambdas.end(); ++it) {
-	    if (it->second == 0) continue;
-        o << FD::Convert(it->first) << '\t' << it->second << endl;
+      if (average) {
+        for (SparseVector<weight_t>::const_iterator it = w_average.begin(); it != w_average.end(); ++it) {
+	      if (it->second == 0) continue;
+          o << FD::Convert(it->first) << '\t' << it->second << endl;
+        }
+      } else {
+        for (SparseVector<weight_t>::const_iterator it = lambdas.begin(); it != lambdas.end(); ++it) {
+	      if (it->second == 0) continue;
+          o << FD::Convert(it->first) << '\t' << it->second << endl;
+        }
       }
     } else if (select_weights == "VOID") { // do nothing with the weights
     } else { // best