nnf_local_response_norm

Applies local response normalization over an input signal composed of
several input planes, where channels occupy the second dimension.
Applies normalization across channels.

Provides functionality to define and train neural networks similar to
'PyTorch' by Paszke et al (2019) <arXiv:1912.01703> but written entirely in R
using the 'libtorch' library. Also supports low-level tensor operations and
'GPU' acceleration.

Daniel Falbel

torch

Tensors and Neural Networks with 'GPU' Acceleration

Javier Luraschi

Dmitriy Selivanov

Athos Damiani

Christophe Regouby

Krzysztof Joachimiak

Hamada S. Badr

 RStudio

nnf_local_response_norm function

<dl><dt>input</dt>
<dd>the input tensor</dd>
<dt>size</dt>
<dd>amount of neighbouring channels used for normalization</dd>
<dt>alpha</dt>
<dd>multiplicative factor. Default: 0.0001</dd>
<dt>beta</dt>
<dd>exponent. Default: 0.75</dd>
<dt>k</dt>
<dd>additive factor. Default: 1</dd></dl>

Arguments

Local_response_norm — nnf_local_response_norm

<dl>

<dt>input</dt>
<dd>the input tensor</dd>


<dt>size</dt>
<dd>amount of neighbouring channels used for normalization</dd>


<dt>alpha</dt>
<dd>multiplicative factor. Default: 0.0001</dd>


<dt>beta</dt>
<dd>exponent. Default: 0.75</dd>


<dt>k</dt>
<dd>additive factor. Default: 1</dd>

</dl>

nnf_local_response_norm: Local_response_norm

Description

Usage

Arguments