using namespace TMVA::Experimental;
void TMVA_CNN_RReader()
{
   const std::string filename = "images_data_16x16.root";

   // Next, we load the model from the TMVA XML file.
   RReader model("dataset/weights/TMVA_CNN_Classification_TMVA_CNN_GPU.weights.xml");

   auto variables = model.GetVariableNames();
   cout<<"Variables names: "<<variables[0]<<endl; // This is not giving the right name, just prints "[0]"

   auto ComputeVec = [&](ROOT::RVecF & vars) {
      std::vector<float> v(vars.begin(), vars.end());
      return model.Compute(v);
   };
   auto make_histo = [&](const std::string &treename) {
      ROOT::RDataFrame df(treename, filename);
      auto df2 = df.Define("y", ComputeVec, {"vars"});
      return df2.Histo1D({treename.c_str(), ";CNN_GPU response;N_{Events}", 100, -0.1, 1.1}, "y");
   };
   auto sig = make_histo("sig_tree");

   sig->DrawClone();
}