Make sure nothing is added to the dict mid training

reading_machine/src/ReadingMachine.cpp

@@ -11,6 +11,7 @@ ReadingMachine::ReadingMachine(std::filesystem::path path, std::vector<std::file
   readFromFile(path);
 
   loadDicts();
+  trainMode(false);
   classifier->getNN()->registerEmbeddings();
   classifier->getNN()->to(NeuralNetworkImpl::device);
 

torch_modules/src/Submodule.cpp

@@ -9,6 +9,8 @@ void Submodule::loadPretrainedW2vEmbeddings(torch::nn::Embedding & embeddings, s
 {
   if (path.empty())
     return;
+  if (!is_training())
+    return;
 
   if (!std::filesystem::exists(path))
     util::myThrow(fmt::format("pretrained word2vec file '{}' do not exist", path.string()));

trainer/src/MacaonTrain.cpp

@@ -207,7 +207,7 @@ int MacaonTrain::main()
     }
     if (trainStrategy[currentEpoch].count(Trainer::TrainAction::ExtractGold) or trainStrategy[currentEpoch].count(Trainer::TrainAction::ExtractDynamic))
     {
-      machine.setDictsState(Dict::State::Open);
+      machine.setDictsState(trainStrategy[currentEpoch].count(Trainer::TrainAction::ExtractDynamic) ? Dict::State::Closed : Dict::State::Open);
       trainer.createDataset(goldConfig, debug, modelPath/"examples/train", currentEpoch, trainStrategy[currentEpoch].count(Trainer::TrainAction::ExtractDynamic));
       if (!computeDevScore)
       {
@@ -220,6 +220,7 @@ int MacaonTrain::main()
       if (trainStrategy[currentEpoch].count(Trainer::TrainAction::ResetParameters))
       {
         machine.resetClassifier();
+        machine.trainMode(currentEpoch == 0);
         machine.getClassifier()->getNN()->registerEmbeddings();
         machine.getClassifier()->getNN()->to(NeuralNetworkImpl::device);
         fmt::print(stderr, "[{}] Model has {} parameters\n", util::getTime(), util::int2HumanStr(machine.getClassifier()->getNbParameters()));

trainer/src/Trainer.cpp

@@ -155,7 +155,6 @@ float Trainer::processDataset(DataLoader & loader, bool train, bool printAdvance
 
   torch::AutoGradMode useGrad(train);
   machine.trainMode(train);
-  machine.setDictsState(Dict::State::Closed);
 
   auto lossFct = torch::nn::CrossEntropyLoss();