code: def build_automl(self):
      initial_configs = self.initial_configurations_via_metalearning
      automl = self._get_automl_class()(
          temporary_directory=self.tmp_folder,
          delete_tmp_folder_after_terminate=self.delete_tmp_folder_after_terminate,
          time_left_for_this_task=self.time_left_for_this_task,
          per_run_time_limit=self.per_run_time_limit,
          initial_configurations_via_metalearning=initial_configs,
          ensemble_class=self.ensemble_class,
          ensemble_kwargs=self.ensemble_kwargs,
          ensemble_nbest=self.ensemble_nbest,
          max_models_on_disc=self.max_models_on_disc,
          seed=self.seed,
          memory_limit=self.memory_limit,
          include=self.include,
          exclude=self.exclude,
          resampling_strategy=self.resampling_strategy,
          resampling_strategy_arguments=self.resampling_strategy_arguments,
          n_jobs=self._n_jobs,
          dask_client=self.dask_client,
          get_smac_object_callback=self.get_smac_object_callback,
          disable_evaluator_output=self.disable_evaluator_output,
          smac_scenario_args=self.smac_scenario_args,
          logging_config=self.logging_config,
          metadata_directory=self.metadata_directory,
          metrics=[self.metric]
          if isinstance(self.metric, Scorer)
          else self.metric,
          scoring_functions=self.scoring_functions,
          get_trials_callback=self.get_trials_callback,
          dataset_compression=self.dataset_compression,
          allow_string_features=self.allow_string_features,
          disable_progress_bar=self.disable_progress_bar,
      )
  
      return automl
  
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 3 for calling the AutoSklearnEstimator obj's underlying member method code with example usage: obj.build_automl() and returns: automl