code: def _completeness_score_compute(
      preds: Tensor, target: Tensor
  ) -> Tuple[Tensor, Tensor]:
      """Computes the completeness score of a clustering given the predicted and target cluster labels."""
      (
          homogeneity,
          mutual_info,
          entropy_preds,
          _,
      ) = _homogeneity_score_compute(preds, target)
      completeness = (
          mutual_info / entropy_preds
          if entropy_preds
          else torch.ones_like(entropy_preds)
      )
      return completeness, homogeneity
  
file_path: torchmetrics/src/torchmetrics/functional/clustering/homogeneity_completeness_v_measure.py
imports: from typing import Tuple
  import torch
  from torch import Tensor
  from torchmetrics.functional.clustering.mutual_info_score import mutual_info_score
  from torchmetrics.functional.clustering.utils import calculate_entropy, check_cluster_labels
label_desc: Use image node_id 2 for calling a global function with example usage: _completeness_score_compute(preds, target) and returns: completeness,  homogeneity