Fixed unknownValueThreshold usage

torch_modules/src/SplitTransLSTM.cpp

@@ -24,10 +24,11 @@ std::size_t SplitTransLSTMImpl::getInputSize()
 void SplitTransLSTMImpl::addToContext(std::vector<std::vector<long>> & context, Dict & dict, const Config & config) const
 {
   auto & splitTransitions = config.getAppliableSplitTransitions();
-  for (int i = 0; i < maxNbTrans; i++)
-    if (i < (int)splitTransitions.size())
-      context.back().emplace_back(dict.getIndexOrInsert(splitTransitions[i]->getName()));
-    else
-      context.back().emplace_back(dict.getIndexOrInsert(Dict::nullValueStr));
+  for (auto & contextElement : context)
+    for (int i = 0; i < maxNbTrans; i++)
+      if (i < (int)splitTransitions.size())
+        contextElement.emplace_back(dict.getIndexOrInsert(splitTransitions[i]->getName()));
+      else
+        contextElement.emplace_back(dict.getIndexOrInsert(Dict::nullValueStr));
 }
 

trainer/include/Trainer.hpp

@@ -22,7 +22,6 @@ class Trainer
   std::unique_ptr<torch::optim::Adam> optimizer;
   std::size_t epochNumber{0};
   int batchSize;
-  int nbExamples{0};
 
   private :
 

trainer/src/Trainer.cpp

@@ -9,11 +9,10 @@ void Trainer::createDataset(BaseConfig & goldConfig, bool debug, std::filesystem
 {
   SubConfig config(goldConfig, goldConfig.getNbLines());
 
+  machine.trainMode(true);
   extractExamples(config, debug, dir, epoch, dynamicOracleInterval);
   trainDataset.reset(new Dataset(dir));
 
-  nbExamples = trainDataset->size().value();
-
   dataLoader = torch::data::make_data_loader(*trainDataset, torch::data::DataLoaderOptions(batchSize).workers(0).max_jobs(0));
 
   if (optimizer.get() == nullptr)
@@ -24,6 +23,7 @@ void Trainer::createDevDataset(BaseConfig & goldConfig, bool debug, std::filesys
 {
   SubConfig config(goldConfig, goldConfig.getNbLines());
 
+  machine.trainMode(false);
   extractExamples(config, debug, dir, epoch, dynamicOracleInterval);
   devDataset.reset(new Dataset(dir));
 
@@ -43,7 +43,6 @@ void Trainer::saveExamples(std::vector<torch::Tensor> & contexts, std::vector<to
 void Trainer::extractExamples(SubConfig & config, bool debug, std::filesystem::path dir, int epoch, int dynamicOracleInterval)
 {
   torch::AutoGradMode useGrad(false);
-  machine.trainMode(false);
   machine.setDictsState(Dict::State::Open);
 
   int maxNbExamplesPerFile = 250000;