ThresholdedReLU

class paddle.nn. ThresholdedReLU ( threshold=1.0, name=None ) [source]

Thresholded ReLU Activation

\[\begin{split}ThresholdedReLU(x) = \left\{ \begin{array}{rl} x,& \text{if } \ x > threshold \\ 0,& \text{otherwise} \end{array} \right.\end{split}\]
Parameters

  • threshold (float, optional) – The value of threshold for ThresholdedReLU. Default is 1.0

  • 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

x = paddle.to_tensor([2., 0., 1.])
m = paddle.nn.ThresholdedReLU()
out = m(x)
print(out)
# Tensor(shape=[3], dtype=float32, place=Place(gpu:0), stop_gradient=True,
#        [2., 0., 0.])
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.