1a73a1367fedfa8368b6c42103e60e1b370bc14a,catalyst/contrib/criterion/focal_loss.py,FocalLoss,forward,#FocalLoss#Any#Any#,11

Before Change

            )

        max_val = (-outputs).clamp(min=0)
        log_ = ((-max_val).exp() + (-outputs - max_val).exp()).log()
        loss = outputs - outputs * targets + max_val + log_

        invprobs = F.logsigmoid(-outputs * (targets * 2.0 - 1.0))
        loss = (invprobs * self.gamma).exp() * loss

        return loss.sum(dim=1).mean()

After Change

        
        num_classes = logits.size(1)
        loss = 0
        targets = targets.view(-1)
        logits = logits.view(-1, num_classes)

        for cls in range(num_classes):
            // Filter anchors with -1 label from loss computation
            if cls == self.ignore:
                continue

            cls_label_target = targets[..., cls].long()
            cls_label_input = logits[..., cls]

            loss += sigmoid_focal_loss(
                cls_label_input,
                cls_label_target,
                gamma=self.gamma,
                alpha=self.alpha
            )

        return loss


__all__ = ["FocalLossBinary", "FocalLossMultiClass", "FocalLossMultiLabel"]

Instances