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