Softplus¶

class paddle.nn. Softplus ( beta=1, threshold=20, name=None ) [source]

Softplus Activation

\[\begin{split}Softplus(x) = \frac{1}{beta} * \log(1 + e^{beta * x}) \\ \text{For numerical stability, the implementation reverts to the linear function when: beta * x > threshold.}\end{split}\]

Parameters

• beta (float, optional) – The value of beta for Softplus. Default is 1

• threshold (float, optional) – The value of threshold for Softplus. Default is 20

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Shape:

• input: Tensor with any shape.

• output: Tensor with the same shape as input.

Examples

import paddle
import numpy as np

x = paddle.to_tensor(np.array([-0.4, -0.2, 0.1, 0.3]))
m = paddle.nn.Softplus()
out = m(x) # [0.513015, 0.598139, 0.744397, 0.854355]

forward ( x )

forward¶

Defines the computation performed at every call. Should be overridden by all subclasses.

Parameters

• *inputs (tuple) – unpacked tuple arguments

• **kwargs (dict) – unpacked dict arguments

extra_repr ( )

extra_repr¶

Extra representation of this layer, you can have custom implementation of your own layer.