514a64431476407d55878bd0c1b332bd84b4022a,mmdet/models/dense_heads/fsaf_head.py,FSAFHead,loss,#FSAFHead#Any#Any#Any#Any#Any#Any#,148

Before Change

            list(range(len(losses_cls))),
            min_levels=argmin)
        // Clamp num_pos to 1e-3 to prevent 0/0
        num_pos = torch.cat(pos_inds, 0).sum().float().clamp(min=1e-3)
        acc = self.calculate_accuracy(cls_scores, labels_list, pos_inds)
        for i in range(len(losses_cls)):
            losses_cls[i] /= num_pos
            losses_bbox[i] /= num_pos

After Change

        num_pos = torch.cat(pos_inds, 0).sum().float()
        acc = self.calculate_accuracy(cls_scores, labels_list, pos_inds)

        if num_pos == 0:  // No gt
            avg_factor = num_pos + float(num_total_neg)
        else:
            avg_factor = num_pos
        for i in range(len(losses_cls)):
            losses_cls[i] /= avg_factor
            losses_bbox[i] /= avg_factor
        return dict(

Instances