code: def maximum_weight_matching(logits):
      from scipy.optimize import linear_sum_assignment
  
      cost = -logits.cpu()
      value = linear_sum_assignment(cost.numpy())[1]
      value = torch.tensor(
          value, dtype=torch.long, device=logits.device
      )
      return value
  
imports: import itertools
  import logging
  import warnings
  import torch
  from torch.distributions import constraints
  from torch.distributions.utils import lazy_property
  from .torch import Categorical
  from .torch_distribution import TorchDistribution
label_desc: Use image node_id 1 for calling a global function with example usage: maximum_weight_matching(logits) and returns: value