unknownValueThreshold is now an argument of CNNNetwork constructor

reading_machine/src/Classifier.cpp

@@ -48,25 +48,25 @@ void Classifier::initNeuralNetwork(const std::string & topology)
       }
     },
     {
-      std::regex("CNN\\((\\d+),(\\d+),(\\d+),\\{(.*)\\},\\{(.*)\\},\\{(.*)\\},\\{(.*)\\},\\{(.*)\\}\\,([+\\-]?\\d+)\\,([+\\-]?\\d+)\\)"),
-      "CNN(leftBorder,rightBorder,nbStack,{columns},{focusedBuffer},{focusedStack},{focusedColumns},{maxNbElements},leftBorderRawInput, rightBorderRawInput) : CNN to capture context.",
+      std::regex("CNN\\((\\d+),(\\d+),(\\d+),(\\d+),\\{(.*)\\},\\{(.*)\\},\\{(.*)\\},\\{(.*)\\},\\{(.*)\\}\\,([+\\-]?\\d+)\\,([+\\-]?\\d+)\\)"),
+      "CNN(unknownValueThreshold,leftBorder,rightBorder,nbStack,{columns},{focusedBuffer},{focusedStack},{focusedColumns},{maxNbElements},leftBorderRawInput, rightBorderRawInput) : CNN to capture context.",
       [this,topology](auto sm)
       {
         std::vector<int> focusedBuffer, focusedStack, maxNbElements;
         std::vector<std::string> focusedColumns, columns;
-        for (auto s : util::split(std::string(sm[4]), ','))
-          columns.emplace_back(s);
         for (auto s : util::split(std::string(sm[5]), ','))
-          focusedBuffer.push_back(std::stoi(std::string(s)));
+          columns.emplace_back(s);
         for (auto s : util::split(std::string(sm[6]), ','))
-          focusedStack.push_back(std::stoi(std::string(s)));
+          focusedBuffer.push_back(std::stoi(std::string(s)));
         for (auto s : util::split(std::string(sm[7]), ','))
-          focusedColumns.emplace_back(s);
+          focusedStack.push_back(std::stoi(std::string(s)));
         for (auto s : util::split(std::string(sm[8]), ','))
+          focusedColumns.emplace_back(s);
+        for (auto s : util::split(std::string(sm[9]), ','))
           maxNbElements.push_back(std::stoi(std::string(s)));
         if (focusedColumns.size() != maxNbElements.size())
           util::myThrow("focusedColumns.size() != maxNbElements.size()");
-        this->nn.reset(new CNNNetworkImpl(this->transitionSet->size(), std::stoi(sm[1]), std::stoi(sm[2]), std::stoi(sm[3]), columns, focusedBuffer, focusedStack, focusedColumns, maxNbElements, std::stoi(sm[9]), std::stoi(sm[10])));
+        this->nn.reset(new CNNNetworkImpl(this->transitionSet->size(), std::stoi(sm[1]), std::stoi(sm[2]), std::stoi(sm[3]), std::stoi(sm[4]), columns, focusedBuffer, focusedStack, focusedColumns, maxNbElements, std::stoi(sm[10]), std::stoi(sm[11])));
       }
     },
     {

torch_modules/include/CNNNetwork.hpp

@@ -9,8 +9,8 @@ class CNNNetworkImpl : public NeuralNetworkImpl
   private :
 
   static constexpr int maxNbEmbeddings = 50000;
-  static constexpr int unknownValueThreshold = 0;
 
+  int unknownValueThreshold;
   std::vector<int> focusedBufferIndexes;
   std::vector<int> focusedStackIndexes;
   std::vector<std::string> focusedColumns;
@@ -31,7 +31,7 @@ class CNNNetworkImpl : public NeuralNetworkImpl
 
   public :
 
-  CNNNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, int nbStackElements, std::vector<std::string> columns, std::vector<int> focusedBufferIndexes, std::vector<int> focusedStackIndexes, std::vector<std::string> focusedColumns, std::vector<int> maxNbElements, int leftWindowRawInput, int rightWindowRawInput);
+  CNNNetworkImpl(int nbOutputs, int unknownValueThreshold, int leftBorder, int rightBorder, int nbStackElements, std::vector<std::string> columns, std::vector<int> focusedBufferIndexes, std::vector<int> focusedStackIndexes, std::vector<std::string> focusedColumns, std::vector<int> maxNbElements, int leftWindowRawInput, int rightWindowRawInput);
   torch::Tensor forward(torch::Tensor input) override;
   std::vector<long> extractContext(Config & config, Dict & dict) const override;
 };

torch_modules/src/CNNNetwork.cpp

 #include "CNNNetwork.hpp"
 
-CNNNetworkImpl::CNNNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, int nbStackElements, std::vector<std::string> columns, std::vector<int> focusedBufferIndexes, std::vector<int> focusedStackIndexes, std::vector<std::string> focusedColumns, std::vector<int> maxNbElements, int leftWindowRawInput, int rightWindowRawInput) : focusedBufferIndexes(focusedBufferIndexes), focusedStackIndexes(focusedStackIndexes), focusedColumns(focusedColumns), maxNbElements(maxNbElements), leftWindowRawInput(leftWindowRawInput), rightWindowRawInput(rightWindowRawInput)
+CNNNetworkImpl::CNNNetworkImpl(int nbOutputs, int unknownValueThreshold, int leftBorder, int rightBorder, int nbStackElements, std::vector<std::string> columns, std::vector<int> focusedBufferIndexes, std::vector<int> focusedStackIndexes, std::vector<std::string> focusedColumns, std::vector<int> maxNbElements, int leftWindowRawInput, int rightWindowRawInput) : unknownValueThreshold(unknownValueThreshold), focusedBufferIndexes(focusedBufferIndexes), focusedStackIndexes(focusedStackIndexes), focusedColumns(focusedColumns), maxNbElements(maxNbElements), leftWindowRawInput(leftWindowRawInput), rightWindowRawInput(rightWindowRawInput)
 {
   constexpr int embeddingsSize = 64;
   constexpr int hiddenSize = 1024;