pmlpp/mlpp/gan/gan_old.h

59 lines
2.1 KiB
C++

#ifndef MLPP_GAN_OLD_hpp
#define MLPP_GAN_OLD_hpp
//
// GAN.hpp
//
// Created by Marc Melikyan on 11/4/20.
//
#include "core/math/math_defs.h"
#include "../hidden_layer/hidden_layer.h"
#include "../output_layer/output_layer.h"
#include "../hidden_layer/hidden_layer_old.h"
#include "../output_layer/output_layer_old.h"
#include <string>
#include <tuple>
#include <vector>
class MLPPGAN {
public:
MLPPGAN(real_t k, std::vector<std::vector<real_t>> outputSet);
~MLPPGAN();
std::vector<std::vector<real_t>> generateExample(int n);
void gradientDescent(real_t learning_rate, int max_epoch, bool UI = false);
real_t score();
void save(std::string fileName);
void addLayer(int n_hidden, std::string activation, std::string weightInit = "Default", std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5);
void addOutputLayer(std::string weightInit = "Default", std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5);
private:
std::vector<std::vector<real_t>> modelSetTestGenerator(std::vector<std::vector<real_t>> X); // Evaluator for the generator of the gan.
std::vector<real_t> modelSetTestDiscriminator(std::vector<std::vector<real_t>> X); // Evaluator for the discriminator of the gan.
real_t Cost(std::vector<real_t> y_hat, std::vector<real_t> y);
void forwardPass();
void updateDiscriminatorParameters(std::vector<std::vector<std::vector<real_t>>> hiddenLayerUpdations, std::vector<real_t> outputLayerUpdation, real_t learning_rate);
void updateGeneratorParameters(std::vector<std::vector<std::vector<real_t>>> hiddenLayerUpdations, real_t learning_rate);
std::tuple<std::vector<std::vector<std::vector<real_t>>>, std::vector<real_t>> computeDiscriminatorGradients(std::vector<real_t> y_hat, std::vector<real_t> outputSet);
std::vector<std::vector<std::vector<real_t>>> computeGeneratorGradients(std::vector<real_t> y_hat, std::vector<real_t> outputSet);
void UI(int epoch, real_t cost_prev, std::vector<real_t> y_hat, std::vector<real_t> outputSet);
std::vector<std::vector<real_t>> outputSet;
std::vector<real_t> y_hat;
std::vector<MLPPOldHiddenLayer> network;
MLPPOldOutputLayer *outputLayer;
int n;
int k;
};
#endif /* GAN_hpp */