torch: torch_avg_pool1d – R documentation

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torch

torch_avg_pool1d

Avg_pool1d

Description

Avg_pool1d

Usage

torch_avg_pool1d(
  self,
  kernel_size,
  stride = list(),
  padding = 0L,
  ceil_mode = FALSE,
  count_include_pad = TRUE
)

Arguments

`self`	input tensor of shape (\mbox{minibatch} , \mbox{in\_channels} , iW)
`kernel_size`	the size of the window. Can be a single number or a tuple `(kW,)`
`stride`	the stride of the window. Can be a single number or a tuple `(sW,)`. Default: `kernel_size`
`padding`	implicit zero paddings on both sides of the input. Can be a single number or a tuple `(padW,)`. Default: 0
`ceil_mode`	when `TRUE`, will use `ceil` instead of `floor` to compute the output shape. Default: `FALSE`
`count_include_pad`	when `TRUE`, will include the zero-padding in the averaging calculation. Default: `TRUE`

avg_pool1d(input, kernel_size, stride=NULL, padding=0, ceil_mode=FALSE, count_include_pad=TRUE) -> Tensor

Applies a 1D average pooling over an input signal composed of several input planes.

See nn_avg_pool1d() for details and output shape.

torch

Tensors and Neural Networks with 'GPU' Acceleration

v0.3.0

MIT + file LICENSE

Authors

Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], RStudio [cph]

Initial release

torch_avg_pool1d

Description

Usage

Arguments

avg_pool1d(input, kernel_size, stride=NULL, padding=0, ceil_mode=FALSE, count_include_pad=TRUE) -> Tensor

torch

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