Added option alwaysSave for training

maca_common/include/ProgramParameters.hpp

@@ -75,6 +75,7 @@ struct ProgramParameters
   static bool devLoss;
   static bool randomDebug;
   static float randomDebugProbability;
+  static bool alwaysSave;
 
   private :
 

maca_common/src/ProgramParameters.cpp

@@ -69,4 +69,4 @@ bool ProgramParameters::devEvalOnGold;
 bool ProgramParameters::devLoss;
 bool ProgramParameters::randomDebug;
 float ProgramParameters::randomDebugProbability;
-
+bool ProgramParameters::alwaysSave;

maca_common/src/programOptionsTemplates.cpp

@@ -41,6 +41,7 @@ po::options_description getTrainOptionsDescription()
   opt.add_options()
     ("help,h", "Produce this help message")
     ("debug,d", "Print infos on stderr")
+    ("alwaysSave", "Save the model at every iteration")
     ("randomDebug", "Print infos on stderr with a probability of randomDebugProbability")
     ("randomDebugProbability", po::value<float>()->default_value(0.001),
       "Probability that debug infos will be printed")
@@ -268,6 +269,7 @@ void loadTrainProgramParameters(int argc, char * argv[])
   ProgramParameters::bdName = vm["bd"].as<std::string>();
   ProgramParameters::mcdName = vm["mcd"].as<std::string>();
   ProgramParameters::debug = vm.count("debug") == 0 ? false : true;
+  ProgramParameters::alwaysSave = vm.count("alwaysSave") == 0 ? false : true;
   ProgramParameters::randomDebug = vm.count("randomDebug") == 0 ? false : true;
   ProgramParameters::printEntropy = vm.count("printEntropy") == 0 ? false : true;
   ProgramParameters::printTime = vm.count("printTime") == 0 ? false : true;

trainer/src/TrainInfos.cpp

@@ -203,6 +203,7 @@ void TrainInfos::computeMustSaves()
     for (auto & it : devScoresPerClassifierPerEpoch)
     {
       mustSavePerClassifierPerEpoch[it.first].push_back(true);
+      if (!ProgramParameters::alwaysSave)
         for (auto & score : it.second)
           if (score > it.second.back())
             mustSavePerClassifierPerEpoch[it.first].back() = false;
@@ -214,6 +215,7 @@ void TrainInfos::computeMustSaves()
     for (auto & it : trainScoresPerClassifierPerEpoch)
     {
       mustSavePerClassifierPerEpoch[it.first].push_back(true);
+      if (!ProgramParameters::alwaysSave)
         for (auto & score : it.second)
           if (score > it.second.back())
             mustSavePerClassifierPerEpoch[it.first].back() = false;