nnf_conv_transpose2d: Conv_transpose2d

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Conv_transpose2d

Description

Applies a 2D transposed convolution operator over an input image composed of several input planes, sometimes also called "deconvolution".

Usage

nnf_conv_transpose2d(
  input,
  weight,
  bias = NULL,
  stride = 1,
  padding = 0,
  output_padding = 0,
  groups = 1,
  dilation = 1
)

Arguments

input	input tensor of shape (minibatch, in_channels, iH , iW)
weight	filters of shape (out_channels , in_channels/groups, 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 ⁠(sH, sW)⁠. Default: 1
padding	implicit paddings on both sides of the input. Can be a single number or a tuple ⁠(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 ⁠(dH, dW)⁠. Default: 1

torch documentation built on June 7, 2023, 6:19 p.m.