Conv_transpose3d
Conv_transpose3d
torch_conv_transpose3d( input, weight, bias = list(), stride = 1L, padding = 0L, output_padding = 0L, groups = 1L, dilation = 1L )
input |
input tensor of shape (\mbox{minibatch} , \mbox{in\_channels} , iT , iH , iW) |
weight |
filters of shape (\mbox{in\_channels} , \frac{\mbox{out\_channels}}{\mbox{groups}} , kT , kH , kW) |
bias |
optional bias of shape (\mbox{out\_channels}). Default: NULL |
stride |
the stride of the convolving kernel. Can be a single number or a tuple |
padding |
|
output_padding |
additional size added to one side of each dimension in the output shape. Can be a single number or a tuple |
groups |
split input into groups, \mbox{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 |
Applies a 3D transposed convolution operator over an input image composed of several input planes, sometimes also called "deconvolution"
See nn_conv_transpose3d()
for details and output shape.
if (torch_is_installed()) { ## Not run: inputs = torch_randn(c(20, 16, 50, 10, 20)) weights = torch_randn(c(16, 33, 3, 3, 3)) nnf_conv_transpose3d(inputs, weights) ## End(Not run) }
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.