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I also don't think
the expand_as in weight = (weight - weight_mean) / std.expand_as(weight) is necessary since std should have the same number of dimensions as weight
Hi in the Conv2d with WS, you computed the mean as
weight_mean = weight.mean(dim=1, keepdim=True).mean(dim=2, keepdim=True).mean(dim=3, keepdim=True)
why don't you do something like
weight_mean = weight.view(weight.shape[0], -1).mean(dim=1).view(-1, 1, 1, 1)
it would be consistent with what you did with the standard deviation as well
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