#include <NeuralNetwork/Learning/PerceptronLearning.h>

#include <cassert>
#include <iostream>

int main() {
	{	// XOR problem
		NeuralNetwork::FeedForward::Perceptron n(2,1);

		n.randomizeWeights();

		NeuralNetwork::Learning::PerceptronLearning learn(n);

		for(int i=0;i<10;i++) {
			learn.teach({1,0},{1});
			learn.teach({1,1},{1});
			learn.teach({0,0},{0});
			learn.teach({0,1},{1});
		}

		{
			std::vector<float> ret =n.computeOutput({1,1});
			assert(ret[0] > 0.9);
		}

		{
			std::vector<float> ret =n.computeOutput({0,1});
			assert(ret[0] > 0.9);
		}

		{
			std::vector<float> ret =n.computeOutput({1,0});
			assert(ret[0] > 0.9);
		}

		{
			std::vector<float> ret =n.computeOutput({0,0});
			assert(ret[0] < 0.1);
		}
	}
}