torch: nnf_conv_transpose3d – R documentation

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nnf_conv_transpose3d

Conv_transpose3d

Description

Applies a 3D transposed convolution operator over an input image composed of several input planes, sometimes also called "deconvolution"

Usage

nnf_conv_transpose3d(
  input,
  weight,
  bias = NULL,
  stride = 1,
  padding = 0,
  output_padding = 0,
  groups = 1,
  dilation = 1
)

Arguments

`input`	input tensor of shape (minibatch, in_channels , iT , iH , iW)
`weight`	filters of shape (out_channels , in_channels/groups, kT , kH , kW)
`bias`	optional bias tensor of shape (out_channels). Default: `NULL`
`stride`	the stride of the convolving kernel. Can be a single number or a tuple `(sT, sH, sW)`. Default: 1
`padding`	implicit paddings on both sides of the input. Can be a single number or a tuple `(padT, padH, padW)`. Default: 0
`output_padding`	padding applied to the output
`groups`	split input into groups, `in_channels` should be divisible by the number of groups. Default: 1
`dilation`	the spacing between kernel elements. Can be a single number or a tuple `(dT, dH, dW)`. Default: 1

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_conv_transpose3d

Description

Usage

Arguments

torch

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