code: def fowlkes_mallows_index(preds: Tensor, target: Tensor) -> Tensor:
      """Compute Fowlkes-Mallows index between two clusterings.
  
      Args:
          preds: predicted cluster labels
          target: ground truth cluster labels
  
      Returns:
          Scalar tensor with Fowlkes-Mallows index
  
      Example:
          >>> import torch
          >>> from torchmetrics.functional.clustering import fowlkes_mallows_index
          >>> preds = torch.tensor([2, 2, 0, 1, 0])
          >>> target = torch.tensor([2, 2, 1, 1, 0])
          >>> fowlkes_mallows_index(preds, target)
          tensor(0.5000)
  
      """
      contingency, n = _fowlkes_mallows_index_update(preds, target)
      return _fowlkes_mallows_index_compute(contingency, n)
  
imports: from typing import Tuple
  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: fowlkes_mallows_index(preds, target) and returns: _fowlkes_mallows_index_compute