pmlpp/mlpp/auto_encoder/auto_encoder.h

#ifndef MLPP_AUTO_ENCODER_H
#define MLPP_AUTO_ENCODER_H

//
//  AutoEncoder.hpp
//
//  Created by Marc Melikyan on 11/4/20.
//

#include <string>
#include <tuple>
#include <vector>

class MLPPAutoEncoder {
public:
	MLPPAutoEncoder(std::vector<std::vector<double>> inputSet, int n_hidden);
	std::vector<std::vector<double>> modelSetTest(std::vector<std::vector<double>> X);
	std::vector<double> modelTest(std::vector<double> x);
	void gradientDescent(double learning_rate, int max_epoch, bool UI = 1);
	void SGD(double learning_rate, int max_epoch, bool UI = 1);
	void MBGD(double learning_rate, int max_epoch, int mini_batch_size, bool UI = 1);
	double score();
	void save(std::string fileName);

private:
	double Cost(std::vector<std::vector<double>> y_hat, std::vector<std::vector<double>> y);

	std::vector<std::vector<double>> Evaluate(std::vector<std::vector<double>> X);
	std::tuple<std::vector<std::vector<double>>, std::vector<std::vector<double>>> propagate(std::vector<std::vector<double>> X);
	std::vector<double> Evaluate(std::vector<double> x);
	std::tuple<std::vector<double>, std::vector<double>> propagate(std::vector<double> x);
	void forwardPass();

	std::vector<std::vector<double>> inputSet;
	std::vector<std::vector<double>> y_hat;

	std::vector<std::vector<double>> weights1;
	std::vector<std::vector<double>> weights2;

	std::vector<double> bias1;
	std::vector<double> bias2;

	std::vector<std::vector<double>> z2;
	std::vector<std::vector<double>> a2;

	int n;
	int k;
	int n_hidden;
};

#endif /* AutoEncoder_hpp */