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84 lines
2.5 KiB
C++
84 lines
2.5 KiB
C++
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#ifndef MLPP_GAN_H
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#define MLPP_GAN_H
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//
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// GAN.hpp
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//
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// Created by Marc Melikyan on 11/4/20.
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//
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#include "core/math/math_defs.h"
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#include "core/object/reference.h"
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#include "../hidden_layer/hidden_layer.h"
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#include "../output_layer/output_layer.h"
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#include "../hidden_layer/hidden_layer_old.h"
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#include "../output_layer/output_layer_old.h"
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#include <string>
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#include <tuple>
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#include <vector>
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class MLPPGAN : public Reference {
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GDCLASS(MLPPGAN, Reference);
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public:
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/*
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Ref<MLPPMatrix> get_input_set();
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void set_input_set(const Ref<MLPPMatrix> &val);
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Ref<MLPPVector> get_output_set();
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void set_output_set(const Ref<MLPPVector> &val);
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int get_k();
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void set_k(const int val);
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*/
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std::vector<std::vector<real_t>> generate_example(int n);
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void gradient_descent(real_t learning_rate, int max_epoch, bool ui = false);
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real_t score();
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void save(std::string file_name);
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void add_layer(int n_hidden, std::string activation, std::string weight_init = "Default", std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5);
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void add_output_layer(std::string weight_init = "Default", std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5);
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MLPPGAN(real_t k, std::vector<std::vector<real_t>> output_set);
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MLPPGAN();
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~MLPPGAN();
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protected:
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std::vector<std::vector<real_t>> model_set_test_generator(std::vector<std::vector<real_t>> X); // Evaluator for the generator of the gan.
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std::vector<real_t> model_set_test_discriminator(std::vector<std::vector<real_t>> X); // Evaluator for the discriminator of the gan.
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real_t cost(std::vector<real_t> y_hat, std::vector<real_t> y);
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void forward_pass();
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void update_discriminator_parameters(std::vector<std::vector<std::vector<real_t>>> hidden_layer_updations, std::vector<real_t> output_layer_updation, real_t learning_rate);
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void update_generator_parameters(std::vector<std::vector<std::vector<real_t>>> hidden_layer_updations, real_t learning_rate);
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std::tuple<std::vector<std::vector<std::vector<real_t>>>, std::vector<real_t>> compute_discriminator_gradients(std::vector<real_t> y_hat, std::vector<real_t> output_set);
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std::vector<std::vector<std::vector<real_t>>> compute_generator_gradients(std::vector<real_t> y_hat, std::vector<real_t> output_set);
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void print_ui(int epoch, real_t cost_prev, std::vector<real_t> y_hat, std::vector<real_t> output_set);
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static void _bind_methods();
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std::vector<std::vector<real_t>> _output_set;
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std::vector<real_t> _y_hat;
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std::vector<MLPPOldHiddenLayer> _network;
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MLPPOldOutputLayer *_output_layer;
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int _n;
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int _k;
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};
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#endif /* GAN_hpp */ |