tests cleaning

tests/activation.cpp

@@ -4,8 +4,13 @@
 #include <NeuralNetwork/ActivationFunction/HyperbolicTangent.h>
 #include <NeuralNetwork/ActivationFunction/Linear.h>
 
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Weffc++"
+
 #include <gtest/gtest.h>
 
+#pragma GCC diagnostic pop
+
 union SSE {
     __m128 sse;    // SSE 4 x float vector
     float floats[4];  // scalar array of 4 floats

tests/backpropagation.cpp

@@ -1,8 +1,13 @@
 #include <NeuralNetwork/FeedForward/Network.h>
 #include <NeuralNetwork/Learning/BackPropagation.h>
+#include <NeuralNetwork/ActivationFunction/HyperbolicTangent.h>
+
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Weffc++"
 
 #include <gtest/gtest.h>
 
+#pragma GCC diagnostic pop
 TEST(BackProp,XOR) {
 	NeuralNetwork::FeedForward::Network n(2);
 	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
@@ -41,10 +46,47 @@ TEST(BackProp,XOR) {
 	}
 }
 
+TEST(BackProp,XORHyperbolicTangent) {
+	NeuralNetwork::FeedForward::Network n(2);
+	NeuralNetwork::ActivationFunction::HyperbolicTangent a(-1);
+	n.appendLayer(2,a);
+	n.appendLayer(1,a);
+
+	n.randomizeWeights();
+
+	NeuralNetwork::Learning::BackPropagation prop(n);
+
+	for(int i=0;i<10000;i++) {
+		prop.teach({1,0},{1});
+		prop.teach({1,1},{0});
+		prop.teach({0,0},{0});
+		prop.teach({0,1},{1});
+	}
+
+	{
+		std::vector<float> ret =n.computeOutput({1,1});
+		ASSERT_LT(ret[0], 0.1);
+	}
+
+	{
+		std::vector<float> ret =n.computeOutput({0,1});
+		ASSERT_GT(ret[0], 0.9);
+	}
+
+	{
+		std::vector<float> ret =n.computeOutput({1,0});
+		ASSERT_GT(ret[0], 0.9);
+	}
+
+	{
+		std::vector<float> ret =n.computeOutput({0,0});
+		ASSERT_LT(ret[0], 0.1);
+	}
+}
+
 TEST(BackProp,AND) {
 	NeuralNetwork::FeedForward::Network n(2);
 	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
-	n.appendLayer(2,a);
 	n.appendLayer(1,a);
 
 	n.randomizeWeights();

tests/feedforward.cpp

@@ -1,7 +1,12 @@
 #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);

tests/optical_backpropagation.cpp

@@ -2,8 +2,12 @@
 
 #include <NeuralNetwork/Learning/OpticalBackPropagation.h>
 
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Weffc++"
+
 #include <gtest/gtest.h>
 
+#pragma GCC diagnostic pop
 
 TEST(OpticalBackPropagation,XOR) {
 	NeuralNetwork::FeedForward::Network n(2);

tests/perceptron.cpp

@@ -1,7 +1,12 @@
 #include <NeuralNetwork/FeedForward/Perceptron.h>
 
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Weffc++"
+
 #include <gtest/gtest.h>
 
+#pragma GCC diagnostic pop
+
 TEST(Perceptron,Test) {
 	NeuralNetwork::FeedForward::Perceptron p(2,1);
 

tests/perceptron_learning.cpp

@@ -1,7 +1,11 @@
 #include <NeuralNetwork/Learning/PerceptronLearning.h>
 
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Weffc++"
+
 #include <gtest/gtest.h>
 
+#pragma GCC diagnostic pop
 
 TEST(PerceptronLearning,XOR) {
 	NeuralNetwork::FeedForward::Perceptron n(2,1);

tests/quickpropagation.cpp

@@ -1,19 +1,25 @@
 #include <NeuralNetwork/FeedForward/Network.h>
 #include <NeuralNetwork/Learning/QuickPropagation.h>
+#include <NeuralNetwork/ActivationFunction/HyperbolicTangent.h>
+
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Weffc++"
 
 #include <gtest/gtest.h>
 
+#pragma GCC diagnostic pop
+
 TEST(QuickPropagation,XOR) {
 	NeuralNetwork::FeedForward::Network n(2);
 	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
-	n.appendLayer(2,a);
+	n.appendLayer(10,a);
 	n.appendLayer(1,a);
 
 	n.randomizeWeights();
 
 	NeuralNetwork::Learning::QuickPropagation prop(n);
 
-	for(int i=0;i<10000;i++) {
+	for(int i=0;i<400;i++) {
 		prop.teach({1,0},{1});
 		prop.teach({1,1},{0});
 		prop.teach({0,0},{0});
@@ -43,7 +49,7 @@ TEST(QuickPropagation,XOR) {
 
 TEST(QuickPropagation,AND) {
 	NeuralNetwork::FeedForward::Network n(2);
-	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
+	NeuralNetwork::ActivationFunction::Sigmoid a(1.0);
 	n.appendLayer(2,a);
 	n.appendLayer(1,a);
 
@@ -51,11 +57,11 @@ TEST(QuickPropagation,AND) {
 
 	NeuralNetwork::Learning::QuickPropagation prop(n);
 
-	for(int i=0;i<10000;i++) {
+	for(int i=0;i<400;i++) {
 		prop.teach({1,1},{1});
+		prop.teach({1,0},{0});
 		prop.teach({0,0},{0});
 		prop.teach({0,1},{0});
-		prop.teach({1,0},{0});
 	}
 
 	{
@@ -115,4 +121,41 @@ TEST(QuickPropagation,NOTAND) {
 		std::vector<float> ret =n.computeOutput({0,0});
 		ASSERT_GT(ret[0], 0.9);
 	}
+}
+TEST(QuickPropagation,NOTANDHyperbolicTangent) {
+	NeuralNetwork::FeedForward::Network n(2);
+	NeuralNetwork::ActivationFunction::HyperbolicTangent a(1);
+	n.appendLayer(2,a);
+	n.appendLayer(1,a);
+
+	n.randomizeWeights();
+
+	NeuralNetwork::Learning::QuickPropagation prop(n);
+
+	for(int i=0;i<10000;i++) {
+		prop.teach({1,1},{-1});
+		prop.teach({-1,0},{1});
+		prop.teach({-1,1},{1});
+		prop.teach({1,-1},{1});
+	}
+
+	{
+		std::vector<float> ret =n.computeOutput({1,1});
+		ASSERT_LT(ret[0], 0.1);
+	}
+
+	{
+		std::vector<float> ret =n.computeOutput({-1,1});
+		ASSERT_GT(ret[0], 0.9);
+	}
+
+	{
+		std::vector<float> ret =n.computeOutput({1,-1});
+		ASSERT_GT(ret[0], 0.9);
+	}
+
+	{
+		std::vector<float> ret =n.computeOutput({-1,-1});
+		ASSERT_GT(ret[0], 0.9);
+	}
 }

tests/recurrent.cpp

@@ -1,7 +1,12 @@
 #include <NeuralNetwork/Recurrent/Network.h>
 
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Weffc++"
+
 #include <gtest/gtest.h>
 
+#pragma GCC diagnostic pop
+
 TEST(Recurrent, Sample) {
 	NeuralNetwork::Recurrent::Network a(2,1,1);
 
@@ -18,7 +23,6 @@ TEST(Recurrent, Sample) {
 	}
 
 	std::string str = a.stringify();
-	std::cout << str << std::endl;;
 
 	//deserialize and check it!
 	NeuralNetwork::Recurrent::Network *deserialized = (NeuralNetwork::Recurrent::Network::Factory::deserialize(str).release());