code: def __init__(self, alpha=0.8, beta=0.2):
      super().__init__()
      self.alpha = alpha
      self.beta = beta
      self.mask_score = dice_score
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from scipy.optimize import linear_sum_assignment
  from torch.cuda.amp import autocast
  from mmdet.registry import MODELS, TASK_UTILS
  from mmdet.utils import reduce_mean
label_desc: Use image node_id 1 to create a new SparseInstMatcher object from inherited base classes: nn with example: obj = SparseInstMatcher(alpha, beta)