torch: nnf_max_pool1d – R documentation

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torch

nnf_max_pool1d

Max_pool1d

Description

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

Usage

nnf_max_pool1d(
  input,
  kernel_size,
  stride = NULL,
  padding = 0,
  dilation = 1,
  ceil_mode = FALSE,
  return_indices = FALSE
)

Arguments

`input`	input tensor of shape (minibatch , 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
`dilation`	controls the spacing between the kernel points; also known as the à trous algorithm.
`ceil_mode`	when True, will use `ceil` instead of `floor` to compute the output shape. Default: `FALSE`
`return_indices`	whether to return the indices where the max occurs.

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

nnf_max_pool1d

Description

Usage

Arguments

torch

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