addapting more tests to gtest

CMakeLists.txt

@@ -89,21 +89,20 @@ IF(ENABLE_TESTS)
 	add_test(activation tests/backpropagation)
 	set_property(TEST activation PROPERTY LABELS unit)
 
-
-#[[
-
 	add_test(backpropagation tests/backpropagation)
 	set_property(TEST backpropagation PROPERTY LABELS unit)
 
-	add_test(backpropagation_function_cmp tests/backpropagation_function_cmp)
-	set_property(TEST backpropagation_function_cmp PROPERTY LABELS unit)
-
 	add_test(basis tests/basis)
 	set_property(TEST basis PROPERTY LABELS unit)
 
 	add_test(feedforward tests/feedforward)
 	set_property(TEST feedforward PROPERTY LABELS unit)
 
+	#[[
+
+		add_test(backpropagation_function_cmp tests/backpropagation_function_cmp)
+		set_property(TEST backpropagation_function_cmp PROPERTY LABELS unit)
+
 		add_test(recurrent tests/recurrent)
 		set_property(TEST recurrent PROPERTY LABELS unit)
 
@@ -131,5 +130,5 @@ IF(ENABLE_TESTS)
 		add_test(recurrent_perf tests/recurrent_perf)
 		set_property(TEST recurrent_perf PROPERTY LABELS perf)
 
-]]
+	]]
 ENDIF(ENABLE_TESTS)

tests/CMakeLists.txt

@@ -5,17 +5,18 @@ project(NeuralNetworkTests CXX)
 set(CMAKE_CXX_FLAGS " --std=c++14")
 
 add_executable(activation activation.cpp)
-target_link_libraries(activation NeuralNetwork)
+target_link_libraries(activation NeuralNetwork gtest gtest_main)
-target_link_libraries(activation gtest gtest_main)
 
 add_executable(basis basis.cpp)
-target_link_libraries(basis NeuralNetwork)
+target_link_libraries(basis NeuralNetwork gtest gtest_main)
-target_link_libraries(basis gtest gtest_main)
-
-#[[
 
 add_executable(backpropagation backpropagation.cpp)
-target_link_libraries(backpropagation NeuralNetwork)
+target_link_libraries(backpropagation NeuralNetwork gtest gtest_main)
+
+add_executable(feedforward feedforward.cpp)
+target_link_libraries(feedforward NeuralNetwork gtest gtest_main)
+
+#[[
 
 add_executable(backpropagation_function_cmp backpropagation_function_cmp.cpp)
 target_link_libraries(backpropagation_function_cmp NeuralNetwork)
@@ -23,9 +24,6 @@ target_link_libraries(backpropagation_function_cmp NeuralNetwork)
 add_executable(backpropagation_perf backpropagation_perf.cpp)
 target_link_libraries(backpropagation_perf NeuralNetwork)
 
-add_executable(feedforward feedforward.cpp)
-target_link_libraries(feedforward NeuralNetwork)
-
 add_executable(feedforward_perf feedforward_perf.cpp)
 target_link_libraries(feedforward_perf NeuralNetwork)
 

tests/backpropagation.cpp

@@ -1,11 +1,9 @@
 #include <NeuralNetwork/FeedForward/Network.h>
+#include <NeuralNetwork/Learning/BackPropagation.h>
 
-#include <cassert>
+#include "gtest/gtest.h"
-#include <iostream>
-#include "../include/NeuralNetwork/Learning/BackPropagation.h"
 
-int main() {
+TEST(BackProp,XOR) {
-	{	// XOR problem
 	NeuralNetwork::FeedForward::Network n(2);
 	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
 	n.appendLayer(2,a);
@@ -14,6 +12,7 @@ int main() {
 	n.randomizeWeights();
 
 	NeuralNetwork::Learning::BackPropagation prop(n);
+
 	for(int i=0;i<10000;i++) {
 		prop.teach({1,0},{1});
 		prop.teach({1,1},{0});
@@ -23,25 +22,26 @@ int main() {
 
 	{
 		std::vector<float> ret =n.computeOutput({1,1});
-			assert(ret[0] < 0.1);
+		ASSERT_LT(ret[0], 0.1);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({0,1});
-			assert(ret[0] > 0.9);
+		ASSERT_GT(ret[0], 0.9);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({1,0});
-			assert(ret[0] > 0.9);
+		ASSERT_GT(ret[0], 0.9);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({0,0});
-			assert(ret[0] < 0.1);
+		ASSERT_LT(ret[0], 0.1);
 	}
-	}
+}
-	{	// AND problem
+
+TEST(BackProp,AND) {
 	NeuralNetwork::FeedForward::Network n(2);
 	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
 	n.appendLayer(2,a);
@@ -50,6 +50,7 @@ int main() {
 	n.randomizeWeights();
 
 	NeuralNetwork::Learning::BackPropagation prop(n);
+
 	for(int i=0;i<10000;i++) {
 		prop.teach({1,1},{1});
 		prop.teach({0,0},{0});
@@ -59,25 +60,26 @@ int main() {
 
 	{
 		std::vector<float> ret =n.computeOutput({1,1});
-			assert(ret[0] > 0.9);
+		ASSERT_GT(ret[0], 0.9);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({0,1});
-			assert(ret[0] < 0.1);
+		ASSERT_LT(ret[0], 0.1);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({1,0});
-			assert(ret[0] < 0.1);
+		ASSERT_LT(ret[0], 0.1);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({0,0});
-			assert(ret[0] < 0.1);
+		ASSERT_LT(ret[0], 0.1);
 	}
-	}
+}
-	{	// NOT AND problem
+
+TEST(BackProp,NOTAND) {
 	NeuralNetwork::FeedForward::Network n(2);
 	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
 	n.appendLayer(2,a);
@@ -86,6 +88,7 @@ int main() {
 	n.randomizeWeights();
 
 	NeuralNetwork::Learning::BackPropagation prop(n);
+
 	for(int i=0;i<10000;i++) {
 		prop.teach({1,1},{0});
 		prop.teach({0,0},{1});
@@ -95,22 +98,21 @@ int main() {
 
 	{
 		std::vector<float> ret =n.computeOutput({1,1});
-			assert(ret[0] < 0.1);
+		ASSERT_LT(ret[0], 0.1);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({0,1});
-			assert(ret[0] > 0.9);
+		ASSERT_GT(ret[0], 0.9);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({1,0});
-			assert(ret[0] > 0.9);
+		ASSERT_GT(ret[0], 0.9);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({0,0});
-			assert(ret[0] > 0.9);
+		ASSERT_GT(ret[0], 0.9);
-		}
 	}
 }

tests/feedforward.cpp

@@ -1,10 +1,8 @@
 #include <NeuralNetwork/FeedForward/Network.h>
 
-#include <cassert>
+#include "gtest/gtest.h"
-#include <iostream>
 
-int main() {
+TEST(FeedForward, XOR) {
-	{	// XOR problem
 	NeuralNetwork::FeedForward::Network n(2);
 	NeuralNetwork::ActivationFunction::Sigmoid a(-1);
 	NeuralNetwork::FeedForward::Layer &hidden=n.appendLayer(2,a);
@@ -25,23 +23,21 @@ int main() {
 
 	{
 		std::vector<float> ret =n.computeOutput({1,1});
-			assert(ret[0] < 0.5);
+		ASSERT_LT(ret[0], 0.5);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({0,1});
-			assert(ret[0] > 0.5);
+		ASSERT_GT(ret[0], 0.5);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({1,0});
-			assert(ret[0] > 0.5);
+		ASSERT_GT(ret[0], 0.5);
 	}
 
 	{
 		std::vector<float> ret =n.computeOutput({0,0});
-			assert(ret[0] < 0.5);
+		ASSERT_LT(ret[0], 0.5);
-		}
 	}
 }
-