code: def _leaderboard_columns(
      num_metrics: int,
  ) -> Dict[Literal["all", "simple", "detailed"], List[str]]:
      if num_metrics == 1:
          cost_list = ["cost"]
      else:
          cost_list = [f"cost_{i}" for i in range(num_metrics)]
      all = (
          [
              "model_id",
              "rank",
              "ensemble_weight",
              "type",
          ]
          + cost_list
          + [
              "duration",
              "config_id",
              "train_loss",
              "seed",
              "start_time",
              "end_time",
              "budget",
              "status",
              "data_preprocessors",
              "feature_preprocessors",
              "balancing_strategy",
              "config_origin",
          ]
      )
      simple = (
          ["model_id", "rank", "ensemble_weight", "type"]
          + cost_list
          + ["duration"]
      )
      detailed = all
      return {"all": all, "detailed": detailed, "simple": simple}
  
imports: from __future__ import annotations
  from typing import Any, Dict, Iterable, List, Mapping, Optional, Sequence, Tuple, Type, Union
  import warnings
  import dask.distributed
  import joblib
  import numpy
  import pandas
  from ConfigSpace.configuration_space import Configuration, ConfigurationSpace
  from scipy.sparse import spmatrix
  from sklearn.base import BaseEstimator, ClassifierMixin, RegressorMixin
  from sklearn.ensemble import VotingClassifier, VotingRegressor
  from sklearn.utils.multiclass import type_of_target
  from smac.runhistory.runhistory import RunInfo, RunValue
  from typing_extensions import Literal
  from autosklearn.automl import AutoML, AutoMLClassifier, AutoMLRegressor
  from autosklearn.data.validation import SUPPORTED_FEAT_TYPES, SUPPORTED_TARGET_TYPES, convert_if_sparse
  from autosklearn.ensembles.abstract_ensemble import AbstractEnsemble
  from autosklearn.ensembles.ensemble_selection import EnsembleSelection
  from autosklearn.ensembles.multiobjective_dummy_ensemble import MultiObjectiveDummyEnsemble
  from autosklearn.metrics import Scorer
  from autosklearn.pipeline.base import BasePipeline
  from autosklearn.util.smac_wrap import SMACCallback
label_desc: Use image node_id 20 for calling the AutoSklearnEstimator obj's underlying member method code with example usage: obj._leaderboard_columns(num_metrics) and returns: dict