#include "Classifier.hpp" #include "util.hpp" #include "OneWordNetwork.hpp" #include "ConcatWordsNetwork.hpp" #include "RTLSTMNetwork.hpp" #include "CNNNetwork.hpp" Classifier::Classifier(const std::string & name, const std::string & topology, const std::string & tsFile) { this->name = name; this->transitionSet.reset(new TransitionSet(tsFile)); initNeuralNetwork(topology); } TransitionSet & Classifier::getTransitionSet() { return *transitionSet; } NeuralNetwork & Classifier::getNN() { return reinterpret_cast<NeuralNetwork&>(nn); } const std::string & Classifier::getName() const { return name; } void Classifier::initNeuralNetwork(const std::string & topology) { static std::vector<std::tuple<std::regex, std::string, std::function<void(const std::smatch &)>>> initializers { { std::regex("OneWord\\(([+\\-]?\\d+)\\)"), "OneWord(focusedIndex) : Only use the word embedding of the focused word.", [this,topology](auto sm) { this->nn.reset(new OneWordNetworkImpl(this->transitionSet->size(), std::stoi(sm[1]))); } }, { std::regex("ConcatWords\\(([+\\-]?\\d+),([+\\-]?\\d+),([+\\-]?\\d+)\\)"), "ConcatWords(leftBorder,rightBorder,nbStack) : Concatenate embeddings of words in context.", [this,topology](auto sm) { this->nn.reset(new ConcatWordsNetworkImpl(this->transitionSet->size(), std::stoi(sm[1]), std::stoi(sm[2]), std::stoi(sm[3]))); } }, { std::regex("CNN\\(([+\\-]?\\d+),([+\\-]?\\d+),([+\\-]?\\d+)\\)"), "CNN(leftBorder,rightBorder,nbStack) : 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::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) if (util::doIfNameMatch(std::get<0>(initializer),topology,std::get<2>(initializer))) return; std::string errorMessage = fmt::format("Unknown neural network '{}', available networks :\n", topology); for (auto & initializer : initializers) errorMessage += std::get<1>(initializer) + "\n"; util::myThrow(errorMessage); }