#ifndef CORE_H
#define CORE_H

#include "typedef.h"
#include <vector>
#include <cmath>
#include <iostream>
#include <cstdlib>

class NeuralNetwork {
private:
    int numLayers;
    std::vector<int> layerSizes;
    std::vector<std::vector<std::vector<double>>> weights; // weights[layer][to_node][from_node]
    std::vector<std::vector<double>> biases;             // biases[layer][node]
    std::vector<std::vector<double>> outputs;            // Храним выходы слоев для backprop

    double sigmoid(double x) { return 1.0 / (1.0 + exp(-x)); }
    double sigmoidDerivative(double x) { return x * (1.0 - x); }

public:
    NeuralNetwork(LayerStructure_t layers[], int count);
    
    std::vector<double> feedForward(std::vector<double> input);
    void train(std::vector<double> input, std::vector<double> target, double learningRate);
};

#endif