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 )

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