pmlpp/mlpp/hidden_layer/hidden_layer.h

#ifndef MLPP_HIDDEN_LAYER_H
#define MLPP_HIDDEN_LAYER_H

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

#include "../activation/activation.h"

#include <map>
#include <string>
#include <vector>

namespace MLPP {
class HiddenLayer {
public:
	HiddenLayer(int n_hidden, std::string activation, std::vector<std::vector<double>> input, std::string weightInit, std::string reg, double lambda, double alpha);

	int n_hidden;
	std::string activation;

	std::vector<std::vector<double>> input;

	std::vector<std::vector<double>> weights;
	std::vector<double> bias;

	std::vector<std::vector<double>> z;
	std::vector<std::vector<double>> a;

	std::map<std::string, std::vector<std::vector<double>> (Activation::*)(std::vector<std::vector<double>>, bool)> activation_map;
	std::map<std::string, std::vector<double> (Activation::*)(std::vector<double>, bool)> activationTest_map;

	std::vector<double> z_test;
	std::vector<double> a_test;

	std::vector<std::vector<double>> delta;

	// Regularization Params
	std::string reg;
	double lambda; /* Regularization Parameter */
	double alpha; /* This is the controlling param for Elastic Net*/

	std::string weightInit;

	void forwardPass();
	void Test(std::vector<double> x);
};
} //namespace MLPP

#endif /* HiddenLayer_hpp */