code: def _clone_and_score_clusterer(clusterer, X, n_clusters):
      start = time.time()
      clusterer = clone(clusterer)
      setattr(clusterer, "n_clusters", n_clusters)
  
      return clusterer.fit(X).score(X), time.time() - start
  
file_path: wandb/wandb/sklearn/calculate/elbow_curve.py
imports: import time
  from warnings import simplefilter
  import numpy
  from joblib import Parallel, delayed
  from sklearn.base import clone
  import wandb
label_desc: Use image node_id 4 for calling a global function with example usage: _clone_and_score_clusterer(clusterer, X, n_clusters) and returns: clusterer,  unknown