Leaky ReLU#

Leaky Rectified Linear Units are activation functions that output x when x is greater or equal to 0 or x scaled by a small leakage coefficient when the input is less than 0. Leaky rectifiers have the benefit of allowing a small gradient to flow through during backpropagation even though they might not have activated during the forward pass.


# Param Default Type Description
1 leakage 0.1 float The amount of leakage as a proportion of the input value to allow to pass through when not inactivated.


use Rubix\ML\NeuralNet\ActivationFunctions\LeakyReLU;

$activationFunction = new LeakyReLU(0.3);


  • A. L. Maas et al. (2013). Rectifier Nonlinearities Improve Neural Network Acoustic Models.