From c914b17d0621eb6626a98f86e4d4e118cd589555 Mon Sep 17 00:00:00 2001
From: Patrick Simianer <simianer@cl.uni-heidelberg.de>
Date: Fri, 27 Apr 2012 16:07:12 +0200
Subject: improved readability, fixes

---
 dtrain/dtrain.cc | 47 ++++++++++-------------------------------------
 1 file changed, 10 insertions(+), 37 deletions(-)

(limited to 'dtrain/dtrain.cc')

diff --git a/dtrain/dtrain.cc b/dtrain/dtrain.cc
index 3dee10f2..e817e7ab 100644
--- a/dtrain/dtrain.cc
+++ b/dtrain/dtrain.cc
@@ -30,7 +30,6 @@ dtrain_init(int argc, char** argv, po::variables_map* cfg)
     ("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")
-    ("inc_correct",       po::value<bool>()->zero_tokens(),                      "include correctly ranked pairs into updates")
     ("fselect",           po::value<weight_t>()->default_value(-1),   "TODO select top x percent of features after each epoch")
     ("approx_bleu_d",     po::value<score_t>()->default_value(0.9),                                "discount for approx. BLEU")
 #ifdef DTRAIN_LOCAL
@@ -122,9 +121,6 @@ main(int argc, char** argv)
   HSReporter rep(task_id);
   bool keep = false;
   if (cfg.count("keep")) keep = true;
-  bool inc_correct = false;
-  if (cfg.count("inc_correct"))
-    inc_correct = true;
 
   const unsigned k = cfg["k"].as<unsigned>();
   const unsigned N = cfg["N"].as<unsigned>();
@@ -226,7 +222,6 @@ main(int argc, char** argv)
   score_t max_score = 0.;
   unsigned best_it = 0;
   float overall_time = 0.;
-  unsigned pair_count = 0, feature_count = 0;
 
   // output cfg
   if (!quiet) {
@@ -250,8 +245,6 @@ main(int argc, char** argv)
     cerr << setw(25) << "select weights " << "'" << select_weights << "'" << endl;
     if (cfg.count("l1_reg"))
       cerr << setw(25) << "l1 reg " << l1_reg << " '" << cfg["l1_reg"].as<string>() << "'" << endl;
-    if (inc_correct)
-      cerr << setw(25) << "inc. correct " << inc_correct << endl;
     if (rescale)
       cerr << setw(25) << "rescale " << rescale << endl;
     cerr << setw(25) << "cdec cfg " << "'" << cfg["decoder_config"].as<string>() << "'" << endl;
@@ -420,36 +413,18 @@ main(int argc, char** argv)
       if (pair_sampling == "PRO")
         PROsampling(samples, pairs, pair_threshold);
       npairs += pairs.size();
-      pair_count += 2*pairs.size();
 
       for (vector<pair<ScoredHyp,ScoredHyp> >::iterator it = pairs.begin();
            it != pairs.end(); it++) {
-        score_t rank_error = it->second.score - it->first.score;
-        feature_count += it->first.f.size() + it->second.f.size();
-        if (!gamma) {
-          // perceptron
-          if (rank_error > 0) {
-            SparseVector<weight_t> diff_vec = it->second.f - it->first.f;
-            lambdas.plus_eq_v_times_s(diff_vec, eta);
-            rank_errors++;
-          } else {
-            if (inc_correct) {
-              SparseVector<weight_t> diff_vec = it->first.f - it->second.f;
-              lambdas.plus_eq_v_times_s(diff_vec, eta);
-            }
-          }
-          if (it->first.model - it->second.model < 1) margin_violations++;
-        } else {
-          // SVM
-          score_t margin = it->first.model - it->second.model;
-          if (rank_error > 0 || margin < 1) {
-            SparseVector<weight_t> diff_vec = it->second.f - it->first.f;
-            lambdas.plus_eq_v_times_s(diff_vec, eta);
-            if (rank_error > 0) rank_errors++;
-            if (margin < 1) margin_violations++;
-          }
-          // regularization
-          lambdas.plus_eq_v_times_s(lambdas, -2*gamma*eta*(1./npairs));
+        bool rank_error = it->first.model <= it->second.model;
+        if (rank_error) rank_errors++;
+        score_t margin = fabs(it->first.model - it->second.model);
+        if (!rank_error && margin < 1) margin_violations++;
+        if (rank_error || (gamma && margin<1)) {
+          SparseVector<weight_t> diff_vec = it->first.f - it->second.f;
+          lambdas.plus_eq_v_times_s(diff_vec, eta);
+          if (gamma)
+            lambdas.plus_eq_v_times_s(lambdas, -2*gamma*eta*(1./npairs));
         }
       }
 
@@ -553,8 +528,6 @@ main(int argc, char** argv)
     cerr << "     avg # margin viol: ";
     cerr << margin_violations/(float)in_sz << endl;
     cerr << "    non0 feature count: " <<  nonz << endl;
-    cerr << "           avg f count: ";
-    cerr << feature_count/(float)pair_count << endl;
   }
 
   if (hstreaming) {
@@ -580,7 +553,7 @@ main(int argc, char** argv)
   overall_time += time_diff;
   if (!quiet) {
     cerr << _p2 << _np << "(time " << time_diff/60. << " min, ";
-    cerr << time_diff/(float)in_sz<< " s/S)" << endl;
+    cerr << time_diff/in_sz << " s/S)" << endl;
   }
   if (t+1 != T && !quiet) cerr << endl;
 
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