SiLU¶

class torch.nn.SiLU(inplace=False)[source][source]¶

Applies the Sigmoid Linear Unit (SiLU) function, element-wise.

The SiLU function is also known as the swish function.

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

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: $(*)$, where $*$ means any number of dimensions.

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

Examples:

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