Is the operation in SGE-Block equivalent to GroupNorm ?

[mrT23]

Hi.
I have two questions:

Question 1:

        t = t - t.mean(dim=1, keepdim=True)
        std = t.std(dim=1, keepdim=True) + 1e-5
        t = t / std
        t = t.view(b, self.groups, h, w)
        t = t * self.weight + self.bias

it this code equivalent to batchNorm (or GroupNorm) ?
if so, shouldn't we use running_mean and running_var to stabilize the statistics and improve convergence ?

Question 2:
xn = xn.sum(dim=1, keepdim=True)
what it is logic behind this line ? why are summing along the groups ?

thanks a lot
Tal

[Haus226]

For question 2, I think it is used to reduce the weighted channels in each group to obtain the attention map $a$