code: def _get_regression_configuration_space(
      datamanager: AbstractDataManager,
      include: Optional[Dict[str, List[str]]],
      exclude: Optional[Dict[str, List[str]]],
      random_state: Optional[Union[int, np.random.RandomState]] = None,
  ) -> ConfigurationSpace:
      """Get the configuration of a regression pipeline given some dataset info
  
      Parameters
      ----------
      datamanager: AbstractDataManager
          AbstractDataManager object storing all important information about the dataset
  
      include: Optional[Dict[str, List[str]]] = None
          A dictionary of what components to include for each pipeline step
  
      exclude: Optional[Dict[str, List[str]]] = None
          A dictionary of what components to exclude for each pipeline step
  
      random_state: Optional[Union[int, np.random.Randomstate]] = None
          The random state to use for seeding the ConfigSpace
  
      Returns
      -------
      ConfigurationSpace
          The configuration space for the regression pipeline
      """
      task_type = datamanager.info["task"]
      sparse = False
      multioutput = False
      if task_type == MULTIOUTPUT_REGRESSION:
          multioutput = True
  
      if datamanager.info["is_sparse"] == 1:
          sparse = True
  
      dataset_properties = {
          "multioutput": multioutput,
          "sparse": sparse,
      }
  
      configuration_space = SimpleRegressionPipeline(
          feat_type=datamanager.feat_type,
          dataset_properties=dataset_properties,
          include=include,
          exclude=exclude,
          random_state=random_state,
      ).get_hyperparameter_search_space(feat_type=datamanager.feat_type)
      return configuration_space
  
file_path: auto-sklearn/autosklearn/util/pipeline.py
imports: from typing import Dict, List, Optional, Union
  import numpy
  from ConfigSpace.configuration_space import ConfigurationSpace
  from autosklearn.constants import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, MULTILABEL_CLASSIFICATION, MULTIOUTPUT_REGRESSION, REGRESSION_TASKS
  from autosklearn.data.abstract_data_manager import AbstractDataManager
  from autosklearn.pipeline.classification import SimpleClassificationPipeline
  from autosklearn.pipeline.regression import SimpleRegressionPipeline
label_desc: Use image node_id 2 for calling a global function with example usage: _get_regression_configuration_space(datamanager, include, exclude, random_state) and returns: configuration_space