The problem of 'shufflenet.py' about pytorch-cifar HOT 7 OPEN

I know the reason. in 27 line, it should be
'int (mid_planes = out_planes/4)'

from pytorch-cifar.

However, I couldn't understand the shuffle operation in the 'ShuffleBlock' absolutely, I hope someone could discuss this with me.

from pytorch-cifar.

Let's say you want to shuffle [1, 2, 3, 4, 5, 6] into [1, 4, 2, 5, 3, 6], just do:
torch.Tensor([1, 2, 3, 4, 5, 6]).view(2, 3).permute(1, 0).contiguous().view(6)

To shuffle it into [1, 3, 5, 2, 4, 6], similarly do:
torch.Tensor([1, 2, 3, 4, 5, 6]).view(3, 2).permute(1, 0).contiguous().view(6)

from pytorch-cifar.

Can you solved it? I have the same problem...

from pytorch-cifar.

I have the same problem. --

from pytorch-cifar.

As @flexibility2 mentioned in his reply
you should change the 27th line in shufflenet.py from
mid_planes = out_planes/4 --> cause float type value
to
mid_planes = int(out_planes/4) --> force to integer

from pytorch-cifar.

`class Bottleneck(nn.Module):
def init(self, in_planes, out_planes, stride, groups):

mid_planes = int(out_planes/4)`

from pytorch-cifar.