class_docstr: IoULoss.
  
  Computing the IoU loss between a set of predicted bboxes and target bboxes.
  
  Args:
      eps (float): Eps to avoid log(0).
      reduction (str): Options are "none", "mean" and "sum".
      loss_weight (float): Weight of loss.
code: def __init__(self, eps=1e-6, reduction="mean", loss_weight=1.0):
      super(IoULoss, self).__init__()
      self.eps = eps
      self.reduction = reduction
      self.loss_weight = loss_weight
  
imports: import math
  import torch
  import torch.nn
  from mmdet.core import bbox_overlaps
  from ..builder import LOSSES
  from .utils import weighted_loss
label_desc: Use image node_id 1 to create a new IoULoss object from inherited base classes: nn with example: obj = IoULoss(eps, reduction, loss_weight)