torch: nnf_avg_pool2d – R documentation

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nnf_avg_pool2d

Avg_pool2d

Description

Applies 2D average-pooling operation in kH * kW regions by step size sH * sW steps. The number of output features is equal to the number of input planes.

Usage

nnf_avg_pool2d(
  input,
  kernel_size,
  stride = NULL,
  padding = 0,
  ceil_mode = FALSE,
  count_include_pad = TRUE,
  divisor_override = NULL
)

Arguments

`input`	input tensor (minibatch, in_channels , iH , iW)
`kernel_size`	size of the pooling region. Can be a single number or a tuple `(kH, kW)`
`stride`	stride of the pooling operation. Can be a single number or a tuple `(sH, sW)`. Default: `kernel_size`
`padding`	implicit zero paddings on both sides of the input. Can be a single number or a tuple `(padH, padW)`. Default: 0
`ceil_mode`	when True, will use `ceil` instead of `floor` in the formula to compute the output shape. Default: `FALSE`
`count_include_pad`	when True, will include the zero-padding in the averaging calculation. Default: `TRUE`
`divisor_override`	if specified, it will be used as divisor, otherwise size of the pooling region will be used. Default: `NULL`

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_avg_pool2d

Description

Usage

Arguments

torch

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