code: def test_random_metric(self):
      kND = KNearestDatasets(
          logger=self.logger, metric=get_random_metric(random_state=1)
      )
      kND.fit(
          pd.DataFrame([self.krvskp, self.labor]),
          self.runs.loc[:, [233, 234]],
      )
      distances = []
      for i in range(20):
          neighbor = kND.kBestSuggestions(self.anneal, 1)
          distances.append(neighbor[0][1])
      self.assertEqual(len(np.unique(distances)), 20)
  
file_path: auto-sklearn/test/test_metalearning/pyMetaLearn/metalearning/test_kND.py
imports: import logging
  import numpy
  import pandas
  from autosklearn.metalearning.metalearning.kNearestDatasets.kND import KNearestDatasets
  from autosklearn.metalearning.metalearning.metrics.misc import get_random_metric
  import unittest
label_desc: Use image node_id 5 for calling the kNDTest obj's underlying member method code with example usage: obj.test_random_metric() without return types