#include <NeuralNetwork/FeedForward/Network.h>

#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Weffc++"

#include <gtest/gtest.h>

#pragma GCC diagnostic pop

TEST(FeedForward, XOR) {
	NeuralNetwork::FeedForward::Network n(2);
	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
	NeuralNetwork::FeedForward::Layer &hidden=n.appendLayer(2,a);
	NeuralNetwork::FeedForward::Layer &out = n.appendLayer(1,a);

	hidden[1].weight(n[0][0])=7;
	hidden[1].weight(n[0][1])=-4.7;
	hidden[1].weight(n[0][2])=-4.7;

	hidden[2].weight(n[0][0])=2.6;
	hidden[2].weight(n[0][1])=-6.4;
	hidden[2].weight(n[0][2])=-6.4;

	out[1].weight(hidden[0])=-4.5;
	out[1].weight(hidden[1])=9.6;
	out[1].weight(hidden[2])=-6.8;


	{
		std::vector<float> ret =n.computeOutput({1,1});
		ASSERT_LT(ret[0], 0.5);
	}

	{
		std::vector<float> ret =n.computeOutput({0,1});
		ASSERT_GT(ret[0], 0.5);
	}

	{
		std::vector<float> ret =n.computeOutput({1,0});
		ASSERT_GT(ret[0], 0.5);
	}

	{
		std::vector<float> ret =n.computeOutput({0,0});
		ASSERT_LT(ret[0], 0.5);
	}
}

TEST(FeedForward, Serialization) {
	NeuralNetwork::FeedForward::Network n(2);
	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
	NeuralNetwork::FeedForward::Layer &hidden=n.appendLayer(2,a);
	NeuralNetwork::FeedForward::Layer &out = n.appendLayer(1,a);

	hidden[1].weight(n[0][0])=7;
	hidden[1].weight(n[0][1])=-4.7;
	hidden[1].weight(n[0][2])=-4.7;

	hidden[2].weight(n[0][0])=2.6;
	hidden[2].weight(n[0][1])=-6.4;
	hidden[2].weight(n[0][2])=-6.4;

	out[1].weight(hidden[0])=-4.5;
	out[1].weight(hidden[1])=9.6;
	out[1].weight(hidden[2])=-6.8;
	std::string serialized = n.serialize().serialize();

	NeuralNetwork::FeedForward::Network *deserialized=NeuralNetwork::FeedForward::Network::Factory::deserialize(serialized).release();

	{
		std::vector<float> ret =deserialized->computeOutput({1,1});
		ASSERT_LT(ret[0], 0.5);
	}

	{
		std::vector<float> ret =deserialized->computeOutput({0,1});
		ASSERT_GT(ret[0], 0.5);
	}

	{
		std::vector<float> ret =deserialized->computeOutput({1,0});
		ASSERT_GT(ret[0], 0.5);
	}

	{
		std::vector<float> ret =deserialized->computeOutput({0,0});
		ASSERT_LT(ret[0], 0.5);
	}

	delete deserialized;
}