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SiLU

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

Applies the Sigmoid Linear Unit (SiLU) function, element-wise. The SiLU function is also known as the swish function.

silu(x)=xσ(x),where σ(x) is the logistic sigmoid.\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,)(N, *) where * means, any number of additional dimensions

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

Examples:

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

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