Hi everyone!
Since I use custom weights in my network I often rely on torch.nn.functional.conv3d rather than torch.nn.Conv3d.
Today I wanted to start to experiment with different group sizes, however there seems to be a bug in the current pytorch 0.2 version?
Following code snippet for example doesn’t work for me:
import torch
myX = torch.autograd.Variable(torch.randn(1,2,5,5,5))
myW = torch.autograd.Variable(torch.randn(4, 2, 3, 3, 3))
y = torch.nn.functional.conv3d(myX, myW, groups=2)

The resulting error:

in conv3d

return f(input, weight, bias)
RuntimeError: size mismatch, m1: [2 x 54], m2: [27 x 27] at /opt/conda/conda-bld/pytorch_1502008109146/work/torch/lib/TH/generic/THTensorMath.c:1293

If I use

c3d = torch.nn.Conv3d(2,4,3,groups=2)
y = c3d(myX)

everything works fine. Nevertheless I would like to be able to use the nn.functional.conv3d interface.
Does anyone face the same problem? Is this a bug for which I should open an issue on github?
Greetings!