#include "../src/NeuralNetwork/FeedForward.h"
#include "../src/NeuralNetwork/Learning/BackPropagation"

#include <iostream>
#include <vector>

//typedef Shin::NeuronNetwork::Problem X;

class X: public Shin::Problem
{
	public:
		X(const X& a) :Problem(a) {}
		X(const std::vector<bool> &a):Problem() { for (bool s:a) data.push_back((float)s);}
	protected:
};

int main(int argc,char**)
{
	srand(time(NULL));
	std::vector<Shin::Solution> s;
	std::vector<X> p;

	//
	s.push_back(Shin::Solution(std::vector<float>({1})));
	p.push_back(X(std::vector<bool>({0})));

	s.push_back(Shin::Solution(std::vector<float>({0})));
	p.push_back(X(std::vector<bool>({1})));

	NeuralNetwork::FeedForward q({1,5000,5000,15000,2});
	if(argc > 1)
	{
		std::cerr << "THREADING\n";
		q.setThreads(2);
	}
#include <chrono>
    auto t1 = std::chrono::high_resolution_clock::now();
	for(int i=0;i<1000;i++)
	{
		//b.teach(p[i%2],s[i%2]);
		q.solve(p[i%2])[0];
		//std::cerr << i%2 <<". FOR: [" << p[i%2].representation()[0] << "] res: " << q.solve(p[i%2])[0] << " should be " << s[i%2][0]<<"\n";
	}
    auto t2 = std::chrono::high_resolution_clock::now();
	std::cout << "Time: " << std::chrono::duration_cast<std::chrono::milliseconds>(t2-t1).count() << std::endl;

}