code: def realtime_learning_curves(runs):
      """
      example how to extract a different kind of learning curve.
  
      The x values are now the time the runs finished, not the budget anymore.
      We no longer plot the validation loss on the y axis, but now the test accuracy.
  
      This is just to show how to get different information into the interactive plot.
  
      """
      sr = sorted(runs, key=lambda r: r.budget)
      lc = list(
          filter(
              lambda t: not t[1] is None,
              [
                  (r.time_stamps["finished"], r.info["test accuracy"])
                  for r in sr
              ],
          )
      )
      return [
          lc,
      ]
  
imports: import matplotlib.pyplot
  import hpbandster.core.result
  import hpbandster.visualization
label_desc: Use image node_id 1 for calling a global function with example usage: realtime_learning_curves(runs) and returns: list