Added classifier RTLSTM

reading_machine/src/Classifier.cpp

@@ -2,6 +2,7 @@
 #include "util.hpp"
 #include "OneWordNetwork.hpp"
 #include "ConcatWordsNetwork.hpp"
+#include "RTLSTMNetwork.hpp"
 
 Classifier::Classifier(const std::string & name, const std::string & topology, const std::string & tsFile)
 {
@@ -45,6 +46,14 @@ void Classifier::initNeuralNetwork(const std::string & topology)
         this->nn.reset(new ConcatWordsNetworkImpl(this->transitionSet->size(), std::stoi(sm[1]), std::stoi(sm[2]), std::stoi(sm[3])));
       }
     },
+    {
+      std::regex("RTLSTM\\(([+\\-]?\\d+),([+\\-]?\\d+),([+\\-]?\\d+)\\)"),
+      "RTLSTM(leftBorder,rightBorder,nbStack) : Recursive tree LSTM.",
+      [this,topology](auto sm)
+      {
+        this->nn.reset(new RTLSTMNetworkImpl(this->transitionSet->size(), std::stoi(sm[1]), std::stoi(sm[2]), std::stoi(sm[3])));
+      }
+    },
   };
 
   for (auto & initializer : initializers)

torch_modules/include/RTLSTMNetwork.hpp

+#ifndef RTLSTMNETWORK__H
+#define RTLSTMNETWORK__H
+
+#include "NeuralNetwork.hpp"
+
+class RTLSTMNetworkImpl : public NeuralNetworkImpl
+{
+  private :
+
+  torch::nn::Embedding wordEmbeddings{nullptr};
+  torch::nn::Linear linear1{nullptr};
+  torch::nn::Linear linear2{nullptr};
+  torch::nn::Dropout dropout{nullptr};
+  torch::nn::LSTM lstm{nullptr};
+
+  public :
+
+  RTLSTMNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, int nbStackElements);
+  torch::Tensor forward(torch::Tensor input) override;
+};
+
+#endif

torch_modules/src/RTLSTMNetwork.cpp

+#include "RTLSTMNetwork.hpp"
+
+RTLSTMNetworkImpl::RTLSTMNetworkImpl(int nbOutputs, int leftBorder, int rightBorder, int nbStackElements)
+{
+  constexpr int embeddingsSize = 100;
+  constexpr int lstmOutputSize = 500;
+  constexpr int hiddenSize = 500;
+  setLeftBorder(leftBorder);
+  setRightBorder(rightBorder);
+  setNbStackElements(nbStackElements);
+
+  wordEmbeddings = register_module("word_embeddings", torch::nn::Embedding(torch::nn::EmbeddingOptions(50000, embeddingsSize)));
+  linear1 = register_module("linear1", torch::nn::Linear(lstmOutputSize, hiddenSize));
+  linear2 = register_module("linear2", torch::nn::Linear(hiddenSize, nbOutputs));
+  dropout = register_module("dropout", torch::nn::Dropout(0.3));
+  lstm = register_module("lstm", torch::nn::LSTM(torch::nn::LSTMOptions(embeddingsSize, lstmOutputSize).batch_first(true)));
+}
+
+torch::Tensor RTLSTMNetworkImpl::forward(torch::Tensor input)
+{
+  // input dim = {batch, sequence, embeddings}
+  auto wordsAsEmb = wordEmbeddings(input);
+  if (wordsAsEmb.dim() == 2)
+    wordsAsEmb = torch::unsqueeze(wordsAsEmb, 0);
+  auto lstmOut = lstm(wordsAsEmb).output;
+  // reshaped dim = {sequence, batch, embeddings}
+  auto reshaped = lstmOut.permute({1,0,2});
+  auto res = linear2(torch::relu(linear1(reshaped[-1])));
+
+  return res;
+}
+