nnf_lp_pool1d

Applies a 1D power-average pooling over an input signal composed of
several input planes. If the sum of all inputs to the power of <code>p</code> is
zero, the gradient is set to zero as well.

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_lp_pool1d function

<dl><dt>input</dt>
<dd>the input tensor</dd>
<dt>norm_type</dt>
<dd>if inf than one gets max pooling if 0 you get sum pooling (
proportional to the avg pooling)</dd>
<dt>kernel_size</dt>
<dd>a single int, the size of the window</dd>
<dt>stride</dt>
<dd>a single int, the stride of the window. Default value is kernel_size</dd>
<dt>ceil_mode</dt>
<dd>when True, will use ceil instead of floor to compute the output shape</dd></dl>

Arguments

Lp_pool1d — nnf_lp_pool1d

<dl>

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


<dt>norm_type</dt>
<dd>if inf than one gets max pooling if 0 you get sum pooling (
proportional to the avg pooling)</dd>


<dt>kernel_size</dt>
<dd>a single int, the size of the window</dd>


<dt>stride</dt>
<dd>a single int, the stride of the window. Default value is kernel_size</dd>


<dt>ceil_mode</dt>
<dd>when True, will use ceil instead of floor to compute the output shape</dd>

</dl>

nnf_lp_pool1d: Lp_pool1d

Description

Usage

Arguments