Hardshrink

class torch.nn.Hardshrink(lambd=0.5) [source]

Applies the Hard Shrinkage (Hardshrink) function element-wise.

Hardshrink is defined as:

$$\text{HardShrink}(x) = \begin{cases} x, & \text{ if } x > \lambda \\ x, & \text{ if } x < -\lambda \\ 0, & \text{ otherwise } \end{cases}$$

Parameters

lambd (float) – the $\lambda$ 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