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Add logging header file.

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davidjacnogueira
2016-11-03 23:05:54 +00:00
parent 7965d7b748
commit f647b05f70
9 changed files with 6812 additions and 134 deletions
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46
src/MLPTest.cpp
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@@ -11,9 +11,12 @@
#include <vector>
#include <algorithm>
#include "microunit.h"
#include "easylogging++.h"
INITIALIZE_EASYLOGGINGPP
UNIT(LearnAND) {
std::cout << "Train AND function with mlp." << std::endl;
LOG(INFO) << "Train AND function with mlp." << std::endl;
std::vector<TrainingSample> training_set =
{
@@ -49,12 +52,11 @@ UNIT(LearnAND) {
ASSERT_TRUE(predicted_output == correct_output);
}
}
std::cout << "Trained with success." << std::endl;
std::cout << std::endl;
LOG(INFO) << "Trained with success." << std::endl;
}
UNIT(LearnNAND) {
std::cout << "Train NAND function with mlp." << std::endl;
LOG(INFO) << "Train NAND function with mlp." << std::endl;
std::vector<TrainingSample> training_set =
{
@@ -90,12 +92,11 @@ UNIT(LearnNAND) {
ASSERT_TRUE(predicted_output == correct_output);
}
}
std::cout << "Trained with success." << std::endl;
std::cout << std::endl;
LOG(INFO) << "Trained with success." << std::endl;
}
UNIT(LearnOR) {
std::cout << "Train OR function with mlp." << std::endl;
LOG(INFO) << "Train OR function with mlp." << std::endl;
std::vector<TrainingSample> training_set =
{
@@ -131,12 +132,11 @@ UNIT(LearnOR) {
ASSERT_TRUE(predicted_output == correct_output);
}
}
std::cout << "Trained with success." << std::endl;
std::cout << std::endl;
LOG(INFO) << "Trained with success." << std::endl;
}
UNIT(LearnNOR) {
std::cout << "Train NOR function with mlp." << std::endl;
LOG(INFO) << "Train NOR function with mlp." << std::endl;
std::vector<TrainingSample> training_set =
{
@@ -172,12 +172,11 @@ UNIT(LearnNOR) {
ASSERT_TRUE(predicted_output == correct_output);
}
}
std::cout << "Trained with success." << std::endl;
std::cout << std::endl;
LOG(INFO) << "Trained with success." << std::endl;
}
UNIT(LearnXOR) {
std::cout << "Train XOR function with mlp." << std::endl;
LOG(INFO) << "Train XOR function with mlp." << std::endl;
std::vector<TrainingSample> training_set =
{
@@ -211,12 +210,11 @@ UNIT(LearnXOR) {
ASSERT_TRUE(predicted_output == correct_output);
}
}
std::cout << "Trained with success." << std::endl;
std::cout << std::endl;
LOG(INFO) << "Trained with success." << std::endl;
}
UNIT(LearnNOT) {
std::cout << "Train NOT function with mlp." << std::endl;
LOG(INFO) << "Train NOT function with mlp." << std::endl;
std::vector<TrainingSample> training_set =
{
@@ -248,12 +246,11 @@ UNIT(LearnNOT) {
ASSERT_TRUE(predicted_output == correct_output);
}
}
std::cout << "Trained with success." << std::endl;
std::cout << std::endl;
LOG(INFO) << "Trained with success." << std::endl;
}
UNIT(LearnX1) {
std::cout << "Train X1 function with mlp." << std::endl;
LOG(INFO) << "Train X1 function with mlp." << std::endl;
std::vector<TrainingSample> training_set =
{
@@ -287,12 +284,11 @@ UNIT(LearnX1) {
ASSERT_TRUE(predicted_output == correct_output);
}
}
std::cout << "Trained with success." << std::endl;
std::cout << std::endl;
LOG(INFO) << "Trained with success." << std::endl;
}
UNIT(LearnX2) {
std::cout << "Train X2 function with mlp." << std::endl;
LOG(INFO) << "Train X2 function with mlp." << std::endl;
std::vector<TrainingSample> training_set =
{
@@ -326,11 +322,11 @@ UNIT(LearnX2) {
ASSERT_TRUE(predicted_output == correct_output);
}
}
std::cout << "Trained with success." << std::endl;
std::cout << std::endl;
LOG(INFO) << "Trained with success." << std::endl;
}
int main() {
int main(int argc, char* argv[]) {
START_EASYLOGGINGPP(argc, argv);
microunit::UnitTester::Run();
return 0;
}