1 files changed, 45 insertions, 31 deletions

diff --git a/training/dtrain/dtrain.cc b/training/dtrain/dtrain.cc
index 149f87d4..0ee2f124 100644
--- a/training/dtrain/dtrain.cc
+++ b/training/dtrain/dtrain.cc
@@ -1,4 +1,10 @@
 #include "dtrain.h"
+#include "score.h"
+#include "kbestget.h"
+#include "ksampler.h"
+#include "pairsampling.h"
+
+using namespace dtrain;
 
 
 bool
@@ -138,23 +144,23 @@ main(int argc, char** argv)
   string scorer_str = cfg["scorer"].as<string>();
   LocalScorer* scorer;
   if (scorer_str == "bleu") {
-    scorer = dynamic_cast<BleuScorer*>(new BleuScorer);
+    scorer = static_cast<BleuScorer*>(new BleuScorer);
   } else if (scorer_str == "stupid_bleu") {
-    scorer = dynamic_cast<StupidBleuScorer*>(new StupidBleuScorer);
+    scorer = static_cast<StupidBleuScorer*>(new StupidBleuScorer);
   } else if (scorer_str == "fixed_stupid_bleu") {
-    scorer = dynamic_cast<FixedStupidBleuScorer*>(new FixedStupidBleuScorer);
+    scorer = static_cast<FixedStupidBleuScorer*>(new FixedStupidBleuScorer);
   } else if (scorer_str == "smooth_bleu") {
-    scorer = dynamic_cast<SmoothBleuScorer*>(new SmoothBleuScorer);
+    scorer = static_cast<SmoothBleuScorer*>(new SmoothBleuScorer);
   } else if (scorer_str == "sum_bleu") {
-    scorer = dynamic_cast<SumBleuScorer*>(new SumBleuScorer);
+    scorer = static_cast<SumBleuScorer*>(new SumBleuScorer);
   } else if (scorer_str == "sumexp_bleu") {
-    scorer = dynamic_cast<SumExpBleuScorer*>(new SumExpBleuScorer);
+    scorer = static_cast<SumExpBleuScorer*>(new SumExpBleuScorer);
   } else if (scorer_str == "sumwhatever_bleu") {
-    scorer = dynamic_cast<SumWhateverBleuScorer*>(new SumWhateverBleuScorer);
+    scorer = static_cast<SumWhateverBleuScorer*>(new SumWhateverBleuScorer);
   } else if (scorer_str == "approx_bleu") {
-    scorer = dynamic_cast<ApproxBleuScorer*>(new ApproxBleuScorer(N, approx_bleu_d));
+    scorer = static_cast<ApproxBleuScorer*>(new ApproxBleuScorer(N, approx_bleu_d));
   } else if (scorer_str == "lc_bleu") {
-    scorer = dynamic_cast<LinearBleuScorer*>(new LinearBleuScorer(N));
+    scorer = static_cast<LinearBleuScorer*>(new LinearBleuScorer(N));
   } else {
     cerr << "Don't know scoring metric: '" << scorer_str << "', exiting." << endl;
     exit(1);
@@ -166,9 +172,9 @@ main(int argc, char** argv)
   MT19937 rng; // random number generator, only for forest sampling
   HypSampler* observer;
   if (sample_from == "kbest")
-    observer = dynamic_cast<KBestGetter*>(new KBestGetter(k, filter_type));
+    observer = static_cast<KBestGetter*>(new KBestGetter(k, filter_type));
   else
-    observer = dynamic_cast<KSampler*>(new KSampler(k, &rng));
+    observer = static_cast<KSampler*>(new KSampler(k, &rng));
   observer->SetScorer(scorer);
 
   // init weights
@@ -360,6 +366,9 @@ main(int argc, char** argv)
         PROsampling(samples, pairs, pair_threshold, max_pairs);
       npairs += pairs.size();
 
+      SparseVector<weight_t> lambdas_copy;
+      if (l1naive||l1clip||l1cumul) lambdas_copy = lambdas;
+
       for (vector<pair<ScoredHyp,ScoredHyp> >::iterator it = pairs.begin();
            it != pairs.end(); it++) {
         bool rank_error;
@@ -369,7 +378,7 @@ main(int argc, char** argv)
           margin = std::numeric_limits<float>::max();
         } else {
           rank_error = it->first.model <= it->second.model;
-          margin = fabs(fabs(it->first.model) - fabs(it->second.model));
+          margin = fabs(it->first.model - it->second.model);
           if (!rank_error && margin < loss_margin) margin_violations++;
         }
         if (rank_error) rank_errors++;
@@ -383,23 +392,26 @@ main(int argc, char** argv)
       }
 
       // l1 regularization
-      // please note that this penalizes _all_ weights
-      // (contrary to only the ones changed by the last update)
-      // after a _sentence_ (not after each example/pair)
+      // please note that this regularizations happen
+      // after a _sentence_ -- not after each example/pair!
       if (l1naive) {
         FastSparseVector<weight_t>::iterator it = lambdas.begin();
         for (; it != lambdas.end(); ++it) {
-          it->second -= sign(it->second) * l1_reg;
+          if (!lambdas_copy.get(it->first) || lambdas_copy.get(it->first)!=it->second) {
+            it->second -= sign(it->second) * l1_reg;
+          }
         }
       } else if (l1clip) {
         FastSparseVector<weight_t>::iterator it = lambdas.begin();
         for (; it != lambdas.end(); ++it) {
-          if (it->second != 0) {
-            weight_t v = it->second;
-            if (v > 0) {
-              it->second = max(0., v - l1_reg);
-            } else {
-              it->second = min(0., v + l1_reg);
+          if (!lambdas_copy.get(it->first) || lambdas_copy.get(it->first)!=it->second) {
+            if (it->second != 0) {
+              weight_t v = it->second;
+              if (v > 0) {
+                it->second = max(0., v - l1_reg);
+              } else {
+                it->second = min(0., v + l1_reg);
+              }
             }
           }
         }
@@ -407,16 +419,18 @@ main(int argc, char** argv)
         weight_t acc_penalty = (ii+1) * l1_reg; // ii is the index of the current input
         FastSparseVector<weight_t>::iterator it = lambdas.begin();
         for (; it != lambdas.end(); ++it) {
-          if (it->second != 0) {
-            weight_t v = it->second;
-            weight_t penalized = 0.;
-            if (v > 0) {
-              penalized = max(0., v-(acc_penalty + cumulative_penalties.get(it->first)));
-            } else {
-              penalized = min(0., v+(acc_penalty - cumulative_penalties.get(it->first)));
+          if (!lambdas_copy.get(it->first) || lambdas_copy.get(it->first)!=it->second) {
+            if (it->second != 0) {
+              weight_t v = it->second;
+              weight_t penalized = 0.;
+              if (v > 0) {
+                penalized = max(0., v-(acc_penalty + cumulative_penalties.get(it->first)));
+              } else {
+                penalized = min(0., v+(acc_penalty - cumulative_penalties.get(it->first)));
+              }
+              it->second = penalized;
+              cumulative_penalties.set_value(it->first, cumulative_penalties.get(it->first)+penalized);
             }
-            it->second = penalized;
-            cumulative_penalties.set_value(it->first, cumulative_penalties.get(it->first)+penalized);
           }
         }
       }