docstr: Retrieve the leaderboard.
  Contrary to the default leaderboard attached to the instance, this one can return columns other than the metrics.
  
  :param extra_columns: a string or a list of string specifying which optional columns should be added to the leaderboard. Defaults to None.
      Currently supported extensions are:
      - 'ALL': adds all columns below.
      - 'training_time_ms': column providing the training time of each model in milliseconds (doesn't include the training of cross validation models).
      - 'predict_time_per_row_ms`: column providing the average prediction time by the model for a single row.
      - 'algo': column providing the algorithm name for each model.
  :return: An H2OFrame representing the leaderboard.
  
  :examples:
  
  >>> aml = H2OAutoML(max_runtime_secs=30)
  >>> aml.train(y=y, training_frame=train)
  >>> lb_all = aml.get_leaderboard('ALL')
  >>> lb_custom = aml.get_leaderboard(['predict_time_per_row_ms', 'training_time_ms'])
  >>> lb_custom_sorted = lb_custom.sort(by='predict_time_per_row_ms')
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code: def get_leaderboard(self, extra_columns=None):
      """
      Retrieve the leaderboard.
      Contrary to the default leaderboard attached to the instance, this one can return columns other than the metrics.
  
      :param extra_columns: a string or a list of string specifying which optional columns should be added to the leaderboard. Defaults to None.
          Currently supported extensions are:
          - 'ALL': adds all columns below.
          - 'training_time_ms': column providing the training time of each model in milliseconds (doesn't include the training of cross validation models).
          - 'predict_time_per_row_ms`: column providing the average prediction time by the model for a single row.
          - 'algo': column providing the algorithm name for each model.
      :return: An H2OFrame representing the leaderboard.
  
      :examples:
  
      >>> aml = H2OAutoML(max_runtime_secs=30)
      >>> aml.train(y=y, training_frame=train)
      >>> lb_all = aml.get_leaderboard('ALL')
      >>> lb_custom = aml.get_leaderboard(['predict_time_per_row_ms', 'training_time_ms'])
      >>> lb_custom_sorted = lb_custom.sort(by='predict_time_per_row_ms')
      """
      assert isinstance(self, Keyed)
      return _fetch_leaderboard(self.key, extra_columns)
  
imports: import h2o
  from h2o.base import Keyed
  from h2o.exceptions import H2OValueError
  from h2o.job import H2OJob
  from h2o.model import ModelBase
  from h2o.utils.compatibility import *
  from h2o.utils.typechecks import assert_is_type, is_type
label_desc: Use image node_id 9 for calling the H2OAutoMLBaseMixin obj's underlying member method code with example usage: obj.get_leaderboard(extra_columns) and returns: _fetch_leaderboard