nnf_gelu

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_gelu function

<dl><dt>input</dt>
<dd>(N,*) tensor, where * means, any number of additional
dimensions</dd>
<dt>approximate</dt>
<dd>By default it's none, and applies element-wise x*pnorm(x),
if 'tanh', then GELU is estimated. See <a href="https://arxiv.org/abs/1606.08415">GELU</a> for
more info.</dd></dl>

Arguments

Applies element-wise the function
\(GELU(x) = x * \Phi(x)\)
where \(\Phi(x)\) is the Cumulative Distribution Function for
Gaussian Distribution.
See <a href="https://arxiv.org/abs/1606.08415">Gaussian Error Linear Units (GELUs)</a>.

gelu(input) -&gt; Tensor 

Gelu — nnf_gelu

<dl>

<dt>input</dt>
<dd>(N,*) tensor, where * means, any number of additional
dimensions</dd>


<dt>approximate</dt>
<dd>By default it's none, and applies element-wise x*pnorm(x),
if 'tanh', then GELU is estimated. See <a href='https://arxiv.org/abs/1606.08415'>GELU</a> for
more info.</dd>

</dl>

Applies element-wise the function
\(GELU(x) = x * \Phi(x)\)
where \(\Phi(x)\) is the Cumulative Distribution Function for
Gaussian Distribution.
See <a href='https://arxiv.org/abs/1606.08415'>Gaussian Error Linear Units (GELUs)</a>.

nnf_gelu: Gelu

Description

Usage

Arguments

gelu(input) -> Tensor

Description

Usage

Arguments

gelu(input) -&gt; Tensor

gelu(input) -> Tensor