def parse_ada_ood_logits()

in models/base.py [0:0]

• 18 lines of code
• 13 McCabe index (conditional complexity)

    def parse_ada_ood_logits(self, ood_logits, metric, project=True):
        if any(x in metric for x in ['bin_disc']):
            pass
        else:
            if any(x in metric for x in ['msp', 'oe']):
                ood_logits = F.softmax(ood_logits, dim=1).max(dim=1, keepdim=True).values - 1. / self.num_classes  # MSP
            elif any(x in metric for x in ['energy']):
                ood_logits = torch.logsumexp(ood_logits, dim=1, keepdim=True)
            elif any(x in metric for x in ['maha']):
                pass  # already calculated
            elif any(x in metric for x in ['gradnorm']):
                ood_logits = [self.calc_gradnorm_per_sample(f) for f in ood_logits]
                ood_logits = torch.tensor(ood_logits).view(-1, 1).cuda()
            else:
                raise NotImplementedError(metric)
            if project:
                ood_logits = self.forward_aux_classifier(ood_logits)

        return ood_logits.squeeze(1)