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

[image]
Examples:
  >>> m = nn.SiLU()
  >>> input = torch.randn(2)
  >>> output = m(input)
