SiLU

class torch.nn.SiLU(inplace: bool = False)

Applies the silu function, element-wise.

$$\text{silu}(x) = x * \sigma(x), \text{where } \sigma(x) \text{ is the logistic sigmoid.}$$

Note

See Gaussian Error Linear Units (GELUs) where the SiLU (Sigmoid Linear Unit) was originally coined, and see Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning and Swish: a Self-Gated Activation Function where the SiLU was experimented with later.

Shape:

• Input: $(N, *)$ where * means, any number of additional dimensions

• Output: $(N, *)$ , same shape as the input

Examples:

>>> m = nn.SiLU()
>>> input = torch.randn(2)
>>> output = m(input)