maxNbEmbeddings is now part of NeuralNetwork

torch_modules/include/CNNNetwork.hpp

@@ -8,8 +8,6 @@ class CNNNetworkImpl : public NeuralNetworkImpl
 {
   private :
 
-  static constexpr int maxNbEmbeddings = 50000;
-
   int unknownValueThreshold;
   std::vector<std::string> focusedColumns;
   std::vector<int> maxNbElements;

torch_modules/include/LSTMNetwork.hpp

@@ -7,8 +7,6 @@ class LSTMNetworkImpl : public NeuralNetworkImpl
 {
   private :
 
-  static constexpr int maxNbEmbeddings = 50000;
-
   int unknownValueThreshold;
   std::vector<std::string> focusedColumns;
   std::vector<int> maxNbElements;

torch_modules/include/NeuralNetwork.hpp

@@ -13,6 +13,8 @@ class NeuralNetworkImpl : public torch::nn::Module
 
   protected : 
 
+  static constexpr int maxNbEmbeddings = 150000;
+
   std::vector<std::string> columns{"FORM"};
   std::vector<int> bufferContext{-3,-2,-1,0,1};
   std::vector<int> stackContext{};

torch_modules/src/ConcatWordsNetwork.cpp

@@ -9,7 +9,7 @@ ConcatWordsNetworkImpl::ConcatWordsNetworkImpl(int nbOutputs, const std::vector<
   setStackContext(stackContext);
   setColumns({"FORM", "UPOS"});
 
-  wordEmbeddings = register_module("word_embeddings", torch::nn::Embedding(torch::nn::EmbeddingOptions(50000, embeddingsSize)));
+  wordEmbeddings = register_module("word_embeddings", torch::nn::Embedding(torch::nn::EmbeddingOptions(maxNbEmbeddings, embeddingsSize)));
   linear1 = register_module("linear1", torch::nn::Linear(getContextSize()*embeddingsSize, hiddenSize));
   linear2 = register_module("linear2", torch::nn::Linear(hiddenSize, nbOutputs));
   dropout = register_module("dropout", torch::nn::Dropout(0.3));

torch_modules/src/RLTNetwork.cpp

@@ -14,7 +14,7 @@ RLTNetworkImpl::RLTNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, i
   setStackContext({});
   setColumns({"FORM", "UPOS"});
 
-  wordEmbeddings = register_module("word_embeddings", torch::nn::Embedding(torch::nn::EmbeddingOptions(50000, embeddingsSize)));
+  wordEmbeddings = register_module("word_embeddings", torch::nn::Embedding(torch::nn::EmbeddingOptions(maxNbEmbeddings, embeddingsSize)));
   linear1 = register_module("linear1", torch::nn::Linear(treeEmbeddingsSize*(focusedBufferIndexes.size()+focusedStackIndexes.size()), hiddenSize));
   linear2 = register_module("linear2", torch::nn::Linear(hiddenSize, nbOutputs));
   vectorBiLSTM = register_module("vector_lstm", torch::nn::LSTM(torch::nn::LSTMOptions(embeddingsSize*columns.size(), lstmOutputSize).batch_first(true).bidirectional(true)));