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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