b6443232013e8d248fe26f59630d43bc9688df06,losses.py,,loss,#Any#Any#Any#Any#,25

Before Change

        targets = torch.stack((targets_dx, targets_dy, targets_dw, targets_dh))
        targets = targets.t()

        targets = targets/torch.Tensor([[0.2, 0.2, 0.3, 0.3]]).cuda()

        negative_indices = 1 - positive_indices

        //import pdb

After Change

        if positive_indices.sum() > 0:
            regression_losses.append(regression_loss[positive_indices, :].mean())
        else:
            regression_losses.append(torch.Tensor([0]).float().cuda())

    return torch.stack(classification_losses).mean(), torch.stack(regression_losses).mean()

Instances