class_docstr: Cost of mask assignments based on dice losses.
  
  Args:
      weight (int | float, optional): loss_weight. Defaults to 1.
      pred_act (bool, optional): Whether to apply sigmoid to mask_pred.
          Defaults to False.
      eps (float, optional): default 1e-12.
code: def __init__(self, weight=1.0, pred_act=False, eps=1e-3):
      self.weight = weight
      self.pred_act = pred_act
      self.eps = eps
  
file_path: dinov2/dinov2/eval/segmentation_m2f/models/losses/match_costs.py
imports: import torch
  import torch.nn.functional
  from ..builder import MATCH_COST
label_desc: Use image node_id 1 to create a new DiceCost object  with example: obj = DiceCost(weight, pred_act, eps)