public void Activator(double[] i, double[] w)
{
double sum = w[0];
for (int l = 0; l < i.Length; ++l)
{
sum += i[l] * w[l + 1];
}
switch (type)
{
case NeuronType.Convolution:
LReLU relu = new LReLU();
output = relu.f(sum);
derivative = relu.df(sum);
break;
case NeuronType.Pooling:
break;
case NeuronType.FullyConnected:
output = Exp(sum);
break;
}
}
public Layer(int nCount, int index, ActivationSettings activationSettings)
{
NCount = nCount;
Index = index;
ActivationType = activationSettings.Type();
// Activation Setup
switch (activationSettings.Type())
{
case EActivationType.Invalid:
Activation = null;
throw new ArgumentException("Activation Type Invalid.");
case EActivationType.Arctan:
Activation = new Arctan();
break;
case EActivationType.BinaryStep:
Activation = new BinaryStep();
break;
case EActivationType.BipolarSigmoid:
Activation = new BipolarSigmoid();
break;
case EActivationType.ELU:
Activation = new ELU((ELUSettings)activationSettings);
break;
case EActivationType.HardSigmoid:
Activation = new HardSigmoid();
break;
case EActivationType.HardTanh:
Activation = new HardTanh();
break;
case EActivationType.Identity:
Activation = new Identity();
break;
case EActivationType.Logit:
Activation = new Logit();
break;
case EActivationType.LReLU:
Activation = new LReLU((LReLUSettings)activationSettings);
break;
case EActivationType.Mish:
Activation = new Mish();
break;
case EActivationType.ReLU:
Activation = new ReLU();
break;
case EActivationType.SeLU:
Activation = new SeLU();
break;
case EActivationType.Sigmoid:
Activation = new Sigmoid();
break;
case EActivationType.Softmax:
Activation = new Softmax();
break;
case EActivationType.Softplus:
Activation = new Softplus();
break;
case EActivationType.Softsign:
Activation = new Softsign();
break;
case EActivationType.Tanh:
Activation = new Tanh();
break;
default:
throw new ArgumentException("Activation Type Invalid.");
}
}
