code: def elbow_curve(
      clusterer, X, cluster_ranges, n_jobs, show_cluster_time
  ):
      if cluster_ranges is None:
          cluster_ranges = range(1, 10, 2)
      else:
          cluster_ranges = sorted(cluster_ranges)
  
      clfs, times = _compute_results_parallel(
          n_jobs, clusterer, X, cluster_ranges
      )
  
      clfs = np.absolute(clfs)
  
      table = make_table(cluster_ranges, clfs, times)
      chart = wandb.visualize("wandb/elbow/v1", table)
  
      return chart
  
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 1 for calling a global function with example usage: elbow_curve(clusterer, X, cluster_ranges, n_jobs, show_cluster_time) and returns: chart