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about group normalization size #5

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alalbiol opened this issue Sep 24, 2019 · 0 comments
Open

about group normalization size #5

alalbiol opened this issue Sep 24, 2019 · 0 comments

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@alalbiol
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Hi
I am also implementing this algorithm and I want to check something with you...

I see that in your implementation you set the number of groups to 8:
num_groups=8
self.norm1 = nn.GroupNorm(num_groups=num_groups, num_channels=inChans)

But in the paper myronenko says literally:
GN stands for group normalization (with group size of 8)

so this can also understood that each group has 8 channels and therefore
num_groups = inChans/8

What do you think?

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