class_docstr: Variation from DiceLoss.
  The coverage and union are computed separately.
class_docstr_tok: ["Variation","from","DiceLoss",".","The","coverage","and","union","are","computed","separately","."]
code: def __init__(self, eps=1e-6, coverage_scale=5.0):
      super(LeakyDiceLoss, self).__init__()
      self.eps = eps
      self.coverage_scale = coverage_scale
  
imports: import torch
  import torch.nn
  import numpy
  import cv2
  from scipy import ndimage
label_desc: Use image node_id 1 to create a new LeakyDiceLoss object from inherited base classes: nn with example: obj = LeakyDiceLoss(eps, coverage_scale)