fb5b85e7f4c9af0190019ea8a8bcaa3e4a1e6d6b,torchsample/constraints.py,MaxNorm,__call__,#MaxNorm#,121

Before Change

        if self.lagrangian:
            w = module.weight
            norm = th.norm(w,2,self.axis)
            return self.scale * th.sum(th.clamp(norm-self.value,0,1e-15))
        else:
            w = module.weight
            norm = th.norm(w,2,self.axis).expand_as(w) / float(self.value)

After Change

        if self.lagrangian:
            w = module.weight
            norm_diff = th.norm(w,2,self.axis).sub(self.value)
            return self.scale * th.sum(norm_diff.gt(0).float().mul(norm_diff))
        else:
            module.weight.data = th.renorm(module.weight.data, 2, self.axis, self.value)

Instances