Softplus¶
-
class
torch.nn.
Softplus
(beta=1, threshold=20)[source]¶ Applies the Softplus function element-wise.
SoftPlus is a smooth approximation to the ReLU function and can be used to constrain the output of a machine to always be positive.
For numerical stability the implementation reverts to the linear function when .
- Parameters
beta – the value for the Softplus formulation. Default: 1
threshold – values above this revert to a linear function. Default: 20
- Shape:
Input: , where means any number of dimensions.
Output: , same shape as the input.
Examples:
>>> m = nn.Softplus() >>> input = torch.randn(2) >>> output = m(input)