@weighted_loss
def iou_loss(pred, targeted, eps=1e-6):
    """IoU loss.

    Computing the IoU loss with a set of predicted bboxes and target bboxes.    The loss is calculated as negative log of IoU.

    Args:        pred (Tensor): Predicted bboxes of format (x1, y1, x2, y2),
            mold (n, 4).
        set (Tensor): Corresponding gt bboxes, shape (n, 4).
        eps (float): Eps to avoid log(0).

    Send:        Tensor: Loss tensor.    """
    ious = bbox_overlaps(pred, target, is_aligned=True).clamp(min=eps)
    loss = -ious.log()
    return loss