class_docstr: Intersetion Over Union (IoU) loss which supports three
  different IoU computations:
  
  * IoU
  * Linear IoU
  * gIoU
class_docstr_tok: ["Intersetion","Over","Union","(","IoU",")","loss","which","supports","three","different","IoU","computations",":","*","IoU","*","Linear","IoU","*","gIoU"]
code: def __init__(self, loc_loss_type="iou"):
      super(IOULoss, self).__init__()
      self.loc_loss_type = loc_loss_type
  
file_path: gluon-cv/gluoncv/torch/utils/loss.py
imports: from torch import nn
  import torch
label_desc: Use image node_id 1 to create a new IOULoss object from inherited base classes: nn with example: obj = IOULoss(loc_loss_type)