code: def render_fairness_indicator(
      slicing_metrics=None,
      multi_slicing_metrics=None,
      event_handlers=None,
  ):
      """Renders the fairness indicator view in Colab.
  
      Args:
        slicing_metrics: A dictionary containing data for visualization.
        multi_slicing_metrics: A dictionary that maps eval name to the
          slicing_metrics. Only two eval results will be accepted.
        event_handlers: The event handler callback.
  
      Returns:
        FairnessIndicatorViewer object
      """
      if (slicing_metrics and multi_slicing_metrics) or (
          not slicing_metrics and not multi_slicing_metrics
      ):
          raise ValueError(
              'Exactly one of the "slicing_metrics" and "multi_slicing_metrics" '
              "parameters must be set."
          )
  
      view = widget.FairnessIndicatorViewer()
      if slicing_metrics:
          view.slicingMetrics = slicing_metrics
      else:  # multi_slicing_metrics
          eval_name, eval_name_compare = multi_slicing_metrics.keys()
          slicing_metrics = multi_slicing_metrics[eval_name]
          slicing_metrics_compare = multi_slicing_metrics[
              eval_name_compare
          ]
          view.slicingMetrics = slicing_metrics
          view.slicingMetricsCompare = slicing_metrics_compare
          view.evalName = eval_name
          view.evalNameCompare = eval_name_compare
  
      view.eventHandlers = event_handlers
      return view
  
label_desc: Use image node_id 1 for calling a global function with example usage: render_fairness_indicator(slicing_metrics, multi_slicing_metrics, event_handlers) and returns: view