CNNNetwork takes new parameters

reading_machine/src/Classifier.cpp

@@ -48,11 +48,21 @@ void Classifier::initNeuralNetwork(const std::string & topology)
       }
     },
     {
-      std::regex("CNN\\(([+\\-]?\\d+),([+\\-]?\\d+),([+\\-]?\\d+)\\)"),
-      "CNN(leftBorder,rightBorder,nbStack) : CNN to capture context.",
+      std::regex("CNN\\((\\d+),(\\d+),(\\d+),\\{(.*)\\},\\{(.*)\\},\\{(.*)\\},\\{(.*)\\}\\)"),
+      "CNN(leftBorder,rightBorder,nbStack,{focusedBuffer},{focusedStack},{focusedColumns}) : CNN to capture context.",
       [this,topology](auto sm)
       {
-        this->nn.reset(new CNNNetworkImpl(this->transitionSet->size(), std::stoi(sm[1]), std::stoi(sm[2]), std::stoi(sm[3])));
+        std::vector<long> focusedBuffer, focusedStack;
+        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)));
+        for (auto s : util::split(std::string(sm[6]), ','))
+          focusedStack.push_back(std::stoi(std::string(s)));
+        for (auto s : util::split(std::string(sm[7]), ','))
+          focusedColumns.emplace_back(s);
+        this->nn.reset(new CNNNetworkImpl(this->transitionSet->size(), std::stoi(sm[1]), std::stoi(sm[2]), std::stoi(sm[3]), columns, focusedBuffer, focusedStack, focusedColumns));
       }
     },
     {

torch_modules/include/CNNNetwork.hpp

@@ -7,11 +7,15 @@ class CNNNetworkImpl : public NeuralNetworkImpl
 {
   private :
 
-  static inline std::vector<long> focusedBufferIndexes{0,1};
-  static inline std::vector<long> focusedStackIndexes{0,1};
   static inline std::vector<long> windowSizes{2,3,4};
   static constexpr unsigned int maxNbLetters = 10;
 
+  private :
+
+  std::vector<long> focusedBufferIndexes;
+  std::vector<long> focusedStackIndexes;
+  std::vector<std::string> focusedColumns;
+
   torch::nn::Embedding wordEmbeddings{nullptr};
   torch::nn::Linear linear1{nullptr};
   torch::nn::Linear linear2{nullptr};
@@ -20,7 +24,7 @@ class CNNNetworkImpl : public NeuralNetworkImpl
 
   public :
 
-  CNNNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, int nbStackElements);
+  CNNNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, int nbStackElements, std::vector<std::string> columns, std::vector<long> focusedBufferIndexes, std::vector<long> focusedStackIndexes, std::vector<std::string> focusedColumns);
   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)
+CNNNetworkImpl::CNNNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, int nbStackElements, std::vector<std::string> columns, std::vector<long> focusedBufferIndexes, std::vector<long> focusedStackIndexes, std::vector<std::string> focusedColumns) : focusedBufferIndexes(focusedBufferIndexes), focusedStackIndexes(focusedStackIndexes), focusedColumns(focusedColumns)
 {
   constexpr int embeddingsSize = 64;
   constexpr int hiddenSize = 512;
@@ -10,7 +10,7 @@ CNNNetworkImpl::CNNNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, i
   setLeftBorder(leftBorder);
   setRightBorder(rightBorder);
   setNbStackElements(nbStackElements);
-  setColumns({"FORM", "UPOS"});
+  setColumns(columns);
 
   wordEmbeddings = register_module("word_embeddings", torch::nn::Embedding(torch::nn::EmbeddingOptions(50000, embeddingsSize)));
   linear1 = register_module("linear1", torch::nn::Linear(nbFilters*windowSizes.size()+nbFiltersLetters*windowSizes.size()*(focusedBufferIndexes.size()+focusedStackIndexes.size()), hiddenSize));