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Softshrink

class torch.nn.Softshrink(lambd: float = 0.5) [source]

Applies the soft shrinkage function elementwise:

SoftShrinkage(x)={xλ, if x>λx+λ, if x<λ0, otherwise \text{SoftShrinkage}(x) = \begin{cases} x - \lambda, & \text{ if } x > \lambda \\ x + \lambda, & \text{ if } x < -\lambda \\ 0, & \text{ otherwise } \end{cases}
Parameters

lambd – the λ\lambda (must be no less than zero) value for the Softshrink formulation. Default: 0.5

Shape:
  • Input: (N,)(N, *) where * means, any number of additional dimensions
  • Output: (N,)(N, *) , same shape as the input
../_images/Softshrink.png

Examples:

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

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Licensed under the 3-clause BSD License.
https://pytorch.org/docs/1.7.0/generated/torch.nn.Softshrink.html