code: def roc(
      y_true=None,
      y_probas=None,
      labels=None,
      plot_micro=True,
      plot_macro=True,
      classes_to_plot=None,
  ):
      """Log the receiver-operating characteristic curve.
  
      Arguments:
          y_true: (arr) Test set labels.
          y_probas: (arr) Test set predicted probabilities.
          labels: (list) Named labels for target variable (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.
  
      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_roc(y_true, y_probas, labels)
      ```
      """
      roc_chart = wandb.plots.roc.roc(
          y_true,
          y_probas,
          labels,
          plot_micro,
          plot_macro,
          classes_to_plot,
      )
      wandb.log({"roc": roc_chart})
  
file_path: wandb/wandb/sklearn/plot/classifier.py
imports: from warnings import simplefilter
  import numpy
  from sklearn import naive_bayes
  import wandb
  import wandb.plots
  from wandb.sklearn import calculate, utils
  from .None import shared
label_desc: Use image node_id 2 for calling a global function with example usage: roc(y_true, y_probas, labels, plot_micro, plot_macro, classes_to_plot) without return types