Added Adagrad optimizer

reading_machine/include/Classifier.hpp

@@ -9,11 +9,16 @@ class Classifier
 {
   private :
 
+  std::vector<std::string> knownOptimizers{
+    "Adam {lr beta1 beta2 eps decay amsgrad}",
+    "Adagrad {lr lr_decay weight_decay eps}",
+  };
+
   std::string name;
   std::map<std::string, std::unique_ptr<TransitionSet>> transitionSets;
   std::map<std::string, float> lossMultipliers;
   std::shared_ptr<NeuralNetworkImpl> nn;
-  std::unique_ptr<torch::optim::Adam> optimizer;
+  std::unique_ptr<torch::optim::Optimizer> optimizer;
   std::string optimizerType, optimizerParameters;
   std::string state;
 
@@ -32,7 +37,7 @@ class Classifier
   void resetOptimizer();
   void loadOptimizer(std::filesystem::path path);
   void saveOptimizer(std::filesystem::path path);
-  torch::optim::Adam & getOptimizer();
+  torch::optim::Optimizer & getOptimizer();
   void setState(const std::string & state);
   float getLossMultiplier();
 };

reading_machine/src/Classifier.cpp

@@ -117,7 +117,7 @@ void Classifier::initNeuralNetwork(const std::vector<std::string> & definition)
           optimizerType = sm.str(1);
           optimizerParameters = sm.str(2);
         }))
-    util::myThrow(fmt::format("Invalid line '{}', expected '{}'\n", curIndex < definition.size() ? definition[curIndex] : "", "(Optimizer :) Adam {lr beta1 beta2 eps decay amsgrad}"));
+    util::myThrow(fmt::format("Invalid line '{}', expected '{}'\n", curIndex < definition.size() ? definition[curIndex] : "", "(Optimizer :) " + util::join("|", knownOptimizers)));
 }
 
 void Classifier::loadOptimizer(std::filesystem::path path)
@@ -130,7 +130,7 @@ void Classifier::saveOptimizer(std::filesystem::path path)
   torch::save(*optimizer, path);
 }
 
-torch::optim::Adam & Classifier::getOptimizer()
+torch::optim::Optimizer & Classifier::getOptimizer()
 {
   return *optimizer;
 }
@@ -162,7 +162,7 @@ void Classifier::initModular(const std::vector<std::string> & definition, std::s
 
 void Classifier::resetOptimizer()
 {
-  std::string expected = "expected '(Optimizer :) Adam {lr beta1 beta2 eps decay amsgrad}'";
+  std::string expected = "expected '(Optimizer :) " + util::join("| ", knownOptimizers);
   if (optimizerType == "Adam")
   {
     auto splited = util::split(optimizerParameters, ' ');
@@ -171,6 +171,14 @@ void Classifier::resetOptimizer()
  
     optimizer.reset(new torch::optim::Adam(getNN()->parameters(), torch::optim::AdamOptions(std::stof(splited[0])).amsgrad(splited.back() == "true").betas({std::stof(splited[1]),std::stof(splited[2])}).eps(std::stof(splited[3])).weight_decay(std::stof(splited[4]))));
   }
+  else if (optimizerType == "Adagrad")
+  {
+    auto splited = util::split(optimizerParameters, ' ');
+    if (splited.size() != 4)
+      util::myThrow(expected);
+ 
+    optimizer.reset(new torch::optim::Adagrad(getNN()->parameters(), torch::optim::AdagradOptions(std::stof(splited[0])).lr_decay(std::stof(splited[1])).eps(std::stof(splited[3])).weight_decay(std::stof(splited[2]))));
+  }
   else
     util::myThrow(expected);
 }