Improved multiMLP

neural_network/src/MultiMLP.cpp

 #include "MultiMLP.hpp"
+#include <cmath>
 
 MultiMLP::MultiMLP()
 {
@@ -77,14 +78,19 @@ dynet::Trainer * MultiMLP::createTrainer()
 
 std::vector<float> MultiMLP::predict(FeatureModel::FeatureDescription & fd)
 {
+  double totalSum = 0.0;
   std::vector<float> prediction(mlps.size());
   for (unsigned int i = 0; i < mlps.size(); i++)
   {
     int id = std::stoi(split(mlps[i].name, '_')[1]);
     auto value = mlps[i].predict(fd);
-    prediction[id] = value[1];
+    prediction[id] = exp(value[1]);
+    totalSum += prediction[id];
   }
 
+  for (unsigned int i = 0; i < prediction.size(); i++)
+    prediction[i] /= totalSum;
+
   return prediction;
 }
 
@@ -98,10 +104,8 @@ float MultiMLP::update(FeatureModel::FeatureDescription & fd, int gold)
       mlp.setBatchSize(getBatchSize());
       if (gold >= 0)
         loss += mlp.update(fd, id == gold ? 1 : 0);
-      else if (id == (-1-gold))
-        loss += mlp.update(fd, 0);
       else
-        continue;
+        loss += mlp.update(fd, id == (-1-gold) ? 0 : 1);
 
       trainer->update();
     } catch (BatchNotFull &)
@@ -128,10 +132,8 @@ float MultiMLP::getLoss(FeatureModel::FeatureDescription & fd, int gold)
       mlp.setBatchSize(getBatchSize());
       if (gold >= 0)
         loss += mlp.update(fd, id == gold ? 1 : 0);
-      else if (id == (-1-gold))
-        loss += mlp.update(fd, 0);
       else
-        continue;
+        loss += mlp.update(fd, id == (-1-gold) ? 0 : 1);
     } catch (BatchNotFull &)
     {
     }