Hardshrink# class torch.nn.Hardshrink(lambd=0.5)[source]# Applies the Hard Shrinkage (Hardshrink) function element-wise. Hardshrink is defined as: HardShrink(x)={x, if x>λx, if x<−λ0, otherwise \text{HardShrink}(x) = \begin{cases} x, & \text{ if } x > \lambda \\ x, & \text{ if } x < -\lambda \\ 0, & \text{ otherwise } \end{cases} HardShrink(x)=⎩⎨⎧x,x,0, if x>λ if x<−λ otherwise Parameters lambd (float) – the λ\lambdaλ value for the Hardshrink formulation. Default: 0.5 Shape: Input: (∗)(*)(∗), where ∗*∗ means any number of dimensions. Output: (∗)(*)(∗), same shape as the input. Examples: >>> m = nn.Hardshrink() >>> input = torch.randn(2) >>> output = m(input) extra_repr()[source]# Return the extra representation of the module. Return type str forward(input)[source]# Run forward pass. Return type Tensor