torch_avg_pool1d

NA input tensor of shape \((\mbox{minibatch} , \mbox{in\_channels} , iW)\)

input

NA the size of the window. Can be a single number or a tuple <code>(kW,)</code>

kernel_size

NA the stride of the window. Can be a single number or a tuple <code>(sW,)</code>. Default: <code>kernel_size</code>

stride

NA implicit zero paddings on both sides of the input. Can be a single number or a tuple <code>(padW,)</code>. Default: 0

padding

NA when True, will use <code>ceil</code> instead of <code>floor</code> to compute the output shape. Default: <code>False</code>

ceil_mode

NA when True, will include the zero-padding in the averaging calculation. Default: <code>True</code>

count_include_pad

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

 RStudio

torch_avg_pool1d function

Applies a 1D average pooling over an input signal composed of several
input planes.
See <code>~torch.nn.AvgPool1d</code> for details and output shape.

torch_avg_pool1d: Avg_pool1d

Description

Arguments

avg_pool1d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True) -> Tensor

Description

Arguments

avg_pool1d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True) -&gt; Tensor

avg_pool1d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True) -> Tensor