example_fcnn_training.cpp

Programa para el testeo de las funciones Fully Connected Layer.Para compilar o código example_fcnn_training.cpp:

g++ -static -o example_fcnn_training example_fcnn_training.cpp -lpdsramm -lpdsnnmm 

Para executar o programa:

./example_fcnn_training

Retornando por consola:

Test[0] Accuracy %: 50
Test[1] Accuracy %: 50
...
Test[997]       Accuracy %: 82.7
Test[998]       Accuracy %: 82.7
Test[999]       Accuracy %: 82.7
...

Datos de treinamento.

Datos despues del treinamento.

Datos de Accuracy.

Código example_fcnn_training.cpp:

 
#include <Pds/Ra>
#include <Pds/Nn>
    
int main(void)
{
    unsigned int M=1000;
    Pds::Vector Acc(M);
    
    Pds::Matrix X(Pds::Ra::TextFormat,"../test/data_x_yinyang.txt");
    Pds::Matrix Y(Pds::Ra::TextFormat,"../test/data_y_yinyang.txt");
    Pds::Matrix Ys(Y.Size());
    
    std::vector<unsigned int> N={2,512,64,8,1};
    Pds::FCNn NN0=Pds::FCNn(N,Pds::Sigmoid,Pds::DSigmoid);
    
    for(unsigned int k=0;k<M;k++)
    {
        NN0.Training(X,Y,0.1,0.01);
        
        NN0.Evaluate(X,Ys);
        
        Acc.Set(k,100.0*Pds::Accuracy(Ys.Geq(0.5),Y));
        std::cout<<"Test["<<k<<"]\t";
        std::cout<<"Accuracy %: "<<Acc.At(k)<<std::endl;
    }
    
    NN0.Save("../test/NeuralNettwork1.txt"); 
    return 0;
}