Files
NeuralNetworkLib/tests/activation.cpp

72 lines
1.4 KiB
C++

#include <NeuralNetwork/ActivationFunction/Heaviside.h>
#include <NeuralNetwork/ActivationFunction/Sigmoid.h>
#include <NeuralNetwork/ActivationFunction/HyperbolicTangent.h>
#include <NeuralNetwork/ActivationFunction/Linear.h>
#include <iostream>
#include <cassert>
#include <chrono>
union {
__m128 v; // SSE 4 x float vector
float a[4]; // scalar array of 4 floats
} U;
int main() {
{
NeuralNetwork::ActivationFunction::Heaviside h(1.0);
assert(h(0.2) == 0);
assert(h(1.2) == 1);
}
{
NeuralNetwork::ActivationFunction::Heaviside h(0.7);
assert(h(0.2) == 0);
assert(h(0.8) == 1);
}
{
NeuralNetwork::ActivationFunction::Sigmoid s(0.7);
assert(s(0.1) > 0.482407);
assert(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(U.a[0] > 0.517483);
assert(U.a[0] < 0.51750);
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(s(0.0) == 0.0);
}
{
NeuralNetwork::ActivationFunction::Linear s(0.7);
assert(s(0.0) == 0.0);
assert(s(1.0) > 0.6999);
assert(s(1.0) < 0.7001);
}
return 0;
}