Activation Layers
ELU
Applies the Exponential Linear Unit (ELU) activation.
GELU
Applies the Gaussian Error Linear Unit (GELU) activation.
GLU
GLU (Gated Linear Unit) activation.
Hardsigmoid
Hardsigmoid activation — piecewise linear approximation of sigmoid.
Hardswish
Hardswish activation — piecewise linear approximation of swish.
Hardtanh
Applies the HardTanh activation function.
LeakyReLU
Applies the Leaky Rectified Linear Unit (Leaky ReLU) activation.
LogSoftmax
Applies the Log Softmax activation function.
Mish
Applies the Mish activation function.
PReLU
PReLU (Parametric ReLU) activation with learnable slope parameter.
ReLU
Applies the Rectified Linear Unit (ReLU) activation function element-wise.
SELU
SELU (Scaled Exponential Linear Unit) activation for self-normalizing networks.
Sigmoid
Applies the Sigmoid activation function element-wise.
SiLU
SiLU (Sigmoid Linear Unit) activation — alias for Swish.
Softmax
Applies the Softmax activation function.
Softmax2d
Applies the Softmax2d activation function over spatial dimensions.
Softmin
Applies the Softmin activation function.
Softplus
Applies the Softplus activation function.
Softsign
Softsign activation function.
Swish
Applies the Swish activation function (also known as SiLU).
Tanh
Applies the Hyperbolic Tangent (Tanh) activation function element-wise.
Tanhshrink
Applies the Tanhshrink activation function element-wise.
import { GELU, GLU, Mish, ReLU, Softmax, Swish } from "deepbox/nn";console.log(new ReLU(), new GELU(), new Swish(), new Mish(), new Softmax(), new GLU());