Conv3d
Conv3d
torch_conv3d( input, weight, bias = list(), stride = 1L, padding = 0L, dilation = 1L, groups = 1L )
input |
input tensor of shape (\mbox{minibatch} , \mbox{in\_channels} , iT , iH , iW) |
weight |
filters of shape (\mbox{out\_channels} , \frac{\mbox{in\_channels}}{\mbox{groups}} , kT , kH , kW) |
bias |
optional bias tensor of shape (\mbox{out\_channels}). Default: NULL |
stride |
the stride of the convolving kernel. Can be a single number or a tuple |
padding |
implicit paddings on both sides of the input. Can be a single number or a tuple |
dilation |
the spacing between kernel elements. 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 |
Applies a 3D convolution over an input image composed of several input planes.
See nn_conv3d() for details and output shape.
if (torch_is_installed()) {
# filters = torch_randn(c(33, 16, 3, 3, 3))
# inputs = torch_randn(c(20, 16, 50, 10, 20))
# nnf_conv3d(inputs, filters)
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