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Merge branch 'tests'

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Shin
2016-04-18 16:15:35 +02:00
parent 17cbf5effe 9f1f0fe763
commit 66516ceb87
14 changed files with 629 additions and 594 deletions
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171
tests/activation.cpp
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@@ -1,103 +1,106 @@
#include <NeuralNetwork/Network.h>
#include <NeuralNetwork/ActivationFunction/Heaviside.h>
#include <NeuralNetwork/ActivationFunction/Sigmoid.h>
#include <NeuralNetwork/ActivationFunction/HyperbolicTangent.h>
#include <NeuralNetwork/ActivationFunction/Linear.h>
#include <NeuralNetwork/Network.h>
#include <gtest/gtest.h>
#include <cassert>
union {
__m128 v; // SSE 4 x float vector
float a[4]; // scalar array of 4 floats
} U;
union SSE {
__m128 sse; // SSE 4 x float vector
float floats[4]; // scalar array of 4 floats
};
NEURAL_NETWORK_INIT();
int main() {
{
NeuralNetwork::ActivationFunction::Heaviside h(1.0);
assert(h(0.2) == 0);
assert(h(1.2) == 1);
}
TEST(Heaviside, ParamOne) {
NeuralNetwork::ActivationFunction::Heaviside h(1.0);
ASSERT_EQ(h(0.2), 0);
ASSERT_EQ(h(1.2), 1);
}
{
NeuralNetwork::ActivationFunction::Heaviside h(0.7);
assert(h(0.2) == 0);
assert(h(0.8) == 1);
}
TEST(Heaviside, ParamZeroPointSeven) {
NeuralNetwork::ActivationFunction::Heaviside h(0.7);
ASSERT_EQ(h(0.2), 0);
ASSERT_EQ(h(0.8), 1);
}
{
NeuralNetwork::ActivationFunction::Sigmoid s(0.7);
assert(s(0.1) > 0.482407);
assert(s(0.1) < 0.482607);
TEST(Sigmoid, ParamZeroPointSeven) {
NeuralNetwork::ActivationFunction::Sigmoid s(0.7);
ASSERT_GT(s(0.1), 0.482407);
ASSERT_LT(s(0.1), 0.482607);
assert(s(10) > 0.000901051);
assert(s(10) < 0.000921051);
}
{
NeuralNetwork::ActivationFunction::Sigmoid s(-5);
assert(s(0.1) > 0.622359);
assert(s(0.1) < 0.622559);
assert(s(0.7) > 0.970588);
assert(s(0.7) < 0.970788);
}
{
NeuralNetwork::ActivationFunction::Sigmoid s(-0.7);
U.a[0]=0.1;
U.a[1]=10;
U.v=s(U.v);
ASSERT_GT(s(10), 0.000901051);
ASSERT_LT(s(10), 0.000921051);
}
assert(U.a[0] > 0.517483);
assert(U.a[0] < 0.51750);
TEST(Sigmoid, ParamMinusFive) {
NeuralNetwork::ActivationFunction::Sigmoid s(-5);
ASSERT_GT(s(0.1), 0.622359);
ASSERT_LT(s(0.1), 0.622559);
assert(U.a[1] > 0.998989);
assert(U.a[1] < 0.999189);
}
{
NeuralNetwork::ActivationFunction::Linear s(1.0);
assert(s(0.5) > 0.4999);
assert(s(0.5) < 0.5001);
ASSERT_GT(s(0.7), 0.970588);
ASSERT_LT(s(0.7), 0.970788);
}
assert(s(0.0) == 0.0);
}
{
NeuralNetwork::ActivationFunction::Linear s(0.7);
assert(s(0.0) == 0.0);
TEST(SigmoidSSE, ParamMinusZeroPointSeven) {
NeuralNetwork::ActivationFunction::Sigmoid s(-0.7);
SSE comp;
comp.floats[0] = 0.1;
comp.floats[1] = 10;
comp.sse = s(comp.sse);
assert(s(1.0) > 0.6999);
assert(s(1.0) < 0.7001);
}
ASSERT_GT(comp.floats[0], 0.517483);
ASSERT_LT(comp.floats[0], 0.51750);
{
NeuralNetwork::ActivationFunction::Linear l(2.5);
const std::string tmp = l.serialize().serialize();
NeuralNetwork::ActivationFunction::ActivationFunction* deserialized = NeuralNetwork::ActivationFunction::Factory::deserialize(l.serialize()).release();
assert(tmp == deserialized->serialize().serialize());
delete deserialized;
}
{
NeuralNetwork::ActivationFunction::Heaviside l(2.5);
const std::string tmp = l.serialize().serialize();
NeuralNetwork::ActivationFunction::ActivationFunction* deserialized = NeuralNetwork::ActivationFunction::Factory::deserialize(l.serialize()).release();
assert(tmp == deserialized->serialize().serialize());
delete deserialized;
}
{
NeuralNetwork::ActivationFunction::HyperbolicTangent l(2.5);
const std::string tmp = l.serialize().serialize();
NeuralNetwork::ActivationFunction::ActivationFunction* deserialized = NeuralNetwork::ActivationFunction::Factory::deserialize(l.serialize()).release();
assert(tmp == deserialized->serialize().serialize());
delete deserialized;
}
{
NeuralNetwork::ActivationFunction::Sigmoid l(2.5);
const std::string tmp = l.serialize().serialize();
NeuralNetwork::ActivationFunction::ActivationFunction* deserialized = NeuralNetwork::ActivationFunction::Factory::deserialize(l.serialize()).release();
assert(tmp == deserialized->serialize().serialize());
delete deserialized;
}
ASSERT_GT(comp.floats[1], 0.998989);
ASSERT_LT(comp.floats[1], 0.999189);
}
return 0;
TEST(Linear, ParamOne) {
NeuralNetwork::ActivationFunction::Linear s(1.0);
ASSERT_GT(s(0.5), 0.4999);
ASSERT_LT(s(0.5), 0.5001);
ASSERT_EQ(s(0.0), 0.0);
}
TEST(Linear, ParamZeroPointSeven) {
NeuralNetwork::ActivationFunction::Linear s(0.7);
ASSERT_GT(s(1.0), 0.6999);
ASSERT_LT(s(1.0), 0.7001);
ASSERT_EQ(s(0.0), 0.0);
}
TEST(Linear, Serialize) {
NeuralNetwork::ActivationFunction::Linear l(2.5);
const std::string tmp = l.serialize().serialize();
NeuralNetwork::ActivationFunction::ActivationFunction* deserialized = NeuralNetwork::ActivationFunction::Factory::deserialize(l.serialize()).release();
ASSERT_EQ(tmp, deserialized->serialize().serialize());
delete deserialized;
}
TEST(Heaviside, Serialize) {
NeuralNetwork::ActivationFunction::Heaviside l(2.5);
const std::string tmp = l.serialize().serialize();
NeuralNetwork::ActivationFunction::ActivationFunction* deserialized = NeuralNetwork::ActivationFunction::Factory::deserialize(l.serialize()).release();
ASSERT_EQ(tmp, deserialized->serialize().serialize());
delete deserialized;
}
TEST(HyperbolicTangent, Serialize) {
NeuralNetwork::ActivationFunction::HyperbolicTangent l(2.5);
const std::string tmp = l.serialize().serialize();
NeuralNetwork::ActivationFunction::ActivationFunction* deserialized = NeuralNetwork::ActivationFunction::Factory::deserialize(l.serialize()).release();
ASSERT_EQ(tmp, deserialized->serialize().serialize());
delete deserialized;
}
TEST(Sigmoid, Serialize) {
NeuralNetwork::ActivationFunction::Sigmoid l(2.5);
const std::string tmp = l.serialize().serialize();
NeuralNetwork::ActivationFunction::ActivationFunction* deserialized = NeuralNetwork::ActivationFunction::Factory::deserialize(l.serialize()).release();
ASSERT_EQ(tmp, deserialized->serialize().serialize());
delete deserialized;
}