nn_rrelu: RReLU module

In torch: Tensors and Neural Networks with 'GPU' Acceleration

RReLU module

Description

Applies the randomized leaky rectified liner unit function, element-wise, as described in the paper:

Usage

nn_rrelu(lower = 1/8, upper = 1/3, inplace = FALSE)

Arguments

lower	lower bound of the uniform distribution. Default: \frac{1}{8}
upper	upper bound of the uniform distribution. Default: \frac{1}{3}
inplace	can optionally do the operation in-place. Default: FALSE

Details

⁠Empirical Evaluation of Rectified Activations in Convolutional Network⁠.

The function is defined as:

\mbox{RReLU}(x) = \left\{ \begin{array}{ll} x & \mbox{if } x \geq 0 \\ ax & \mbox{ otherwise } \end{array} \right.

where a is randomly sampled from uniform distribution \mathcal{U}(\mbox{lower}, \mbox{upper}). See: https://arxiv.org/pdf/1505.00853.pdf

Shape

• Input: (N, *) where * means, any number of additional dimensions

• Output: (N, *), same shape as the input

Examples

if (torch_is_installed()) {
m <- nn_rrelu(0.1, 0.3)
input <- torch_randn(2)
m(input)
}

torch documentation built on June 7, 2023, 6:19 p.m.