code: def mutual_info_score(preds: Tensor, target: Tensor) -> Tensor:
      """Compute mutual information between two clusterings.
  
      Args:
          preds: predicted cluster labels
          target: ground truth cluster labels
  
      Example:
          >>> from torchmetrics.functional.clustering import mutual_info_score
          >>> target = torch.tensor([0, 3, 2, 2, 1])
          >>> preds = torch.tensor([1, 3, 2, 0, 1])
          >>> mutual_info_score(preds, target)
          tensor(1.0549)
  
      """
      contingency = _mutual_info_score_update(preds, target)
      return _mutual_info_score_compute(contingency)
  
imports: import torch
  from torch import Tensor, tensor
  from torchmetrics.functional.clustering.utils import calculate_contingency_matrix, check_cluster_labels
label_desc: Use image node_id 3 for calling a global function with example usage: mutual_info_score(preds, target) and returns: _mutual_info_score_compute