code: def clusterer(
      model,
      X_train,
      cluster_labels,
      labels=None,
      model_name="Clusterer",
  ):
      """Generates all sklearn clusterer plots supported by W&B.
  
      The following plots are generated:
          elbow curve, silhouette plot.
  
      Should only be called with a fitted clusterer (otherwise an error is thrown).
  
      Arguments:
          model: (clusterer) Takes in a fitted clusterer.
          X_train: (arr) Training set features.
          cluster_labels: (list) Names for cluster labels. Makes plots easier to read
                              by replacing cluster indexes with corresponding names.
          labels: (list) Named labels for target varible (y). Makes plots easier to
                          read by replacing target values with corresponding index.
                          For example if `labels=['dog', 'cat', 'owl']` all 0s are
                          replaced by dog, 1s by cat.
          model_name: (str) Model name. Defaults to 'Clusterer'
  
      Returns:
          None: To see plots, go to your W&B run page then expand the 'media' tab
                under 'auto visualizations'.
  
      Example:
      ```python
      wandb.sklearn.plot_clusterer(kmeans, X, cluster_labels, labels, "KMeans")
      ```
      """
      wandb.termlog("\nPlotting %s." % model_name)
      if isinstance(model, sklearn.cluster.KMeans):
          elbow_curve(model, X_train)
          wandb.termlog("Logged elbow curve.")
  
          silhouette(
              model, X_train, cluster_labels, labels=labels, kmeans=True
          )
  
      else:
          silhouette(model, X_train, cluster_labels, kmeans=False)
  
      wandb.termlog("Logged silhouette plot.")
  
file_path: wandb/wandb/sklearn/plot/clusterer.py
imports: from warnings import simplefilter
  import pandas
  import sklearn
  import wandb
  from wandb.sklearn import calculate, utils
label_desc: Use image node_id 1 for calling a global function with example usage: clusterer(model, X_train, cluster_labels, labels, model_name) without return types