Enum RnnActivation
Options for activation functions to apply in a recurrent layer.
Syntax
public enum RnnActivation
Fields
Name |
Description |
Value |
Relu |
Use Relu activation: f(x) = max(0, x).
|
0 |
Tanh |
Use Tanh activation: f(x) = (1 - e^{-2x}) / (1 + e^{-2x}).
|
1 |
Sigmoid |
Use Sigmoid activation: f(x) = 1 / (1 + e^{-x}).
|
2 |
Affine |
Use Affine activation: f(x) = alpha * x + beta.
|
3 |
LeakyRelu |
Use LeakyRelu activation: f(x) = x if x >= 0, otherwise f(x) = alpha * x.
|
4 |
ThresholdedRelu |
Use ThresholdedRelu activation: f(x) = x if x >= alpha, otherwise f(x) = 0.
|
5 |
ScaledTanh |
Use ScaledTanh activation: f(x) = alpha * tanh(beta * x).
|
6 |
HardSigmoid |
Use HardSigmoid activation: f(x) = clamp(alpha * x + beta, 0, 1).
|
7 |
Elu |
Use Elu activation: f(x) = x if x >= 0, otherwise f(x) = alpha * (e^x - 1).
|
8 |
Softsign |
Use Softsign activation: f(x) = x / (1 + |x|).
|
9 |
Softplus |
Use Softplus activation: f(x) = log(1 + e^x).
|
10 |