torch: nn_adaptive_max_pool3d – R documentation

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nn_adaptive_max_pool3d

Applies a 3D adaptive max pooling over an input signal composed of several input planes.

Description

The output is of size D x H x W, for any input size. The number of output features is equal to the number of input planes.

Usage

nn_adaptive_max_pool3d(output_size, return_indices = FALSE)

Arguments

`output_size`	the target output size of the image of the form D x H x W. Can be a tuple (D, H, W) or a single D for a cube D x D x D. D, H and W can be either a `int`, or `None` which means the size will be the same as that of the input.
`return_indices`	if `TRUE`, will return the indices along with the outputs. Useful to pass to `nn_max_unpool3d()`. Default: `FALSE`

Examples

if (torch_is_installed()) {
# target output size of 5x7x9
m <- nn_adaptive_max_pool3d(c(5,7,9))
input <- torch_randn(1, 64, 8, 9, 10)
output <- m(input)
# target output size of 7x7x7 (cube)
m <- nn_adaptive_max_pool3d(7)
input <- torch_randn(1, 64, 10, 9, 8)
output <- m(input)

}

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