class_docstr: Base class for all pipeline objects.
  
  Notes
  -----
  This class should not be instantiated, only subclassed.
docstr: Return the configuration space for the CASH problem.
  
  Returns
  -------
  cs : ConfigSpace.configuration_space.Configuration
      The configuration space describing the AutoSklearnClassifier.
docstr_tok: ["Return","the","configuration","space","for","the","CASH","problem",".","Returns","--","--","--","-","cs",":","ConfigSpace.configuration_space.Configuration","The","configuration","space","describing","the","AutoSklearnClassifier","."]
code: def get_hyperparameter_search_space(
      self,
      feat_type: Optional[FEAT_TYPE_TYPE] = None,
      dataset_properties=None,
  ):
      """Return the configuration space for the CASH problem.
  
      Returns
      -------
      cs : ConfigSpace.configuration_space.Configuration
          The configuration space describing the AutoSklearnClassifier.
  
      """
      if not hasattr(self, "config_space") or self.config_space is None:
          self.config_space = self._get_hyperparameter_search_space(
              feat_type=feat_type,
              include=self.include,
              exclude=self.exclude,
              dataset_properties=self.dataset_properties,
          )
      return self.config_space
  
imports: from abc import ABCMeta
  from typing import Dict, Optional, Union
  import numpy
  import scipy.sparse
  from ConfigSpace import Configuration
  from sklearn.pipeline import Pipeline
  import autosklearn.pipeline.create_searchspace_util
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from .components.base import AutoSklearnChoice, AutoSklearnComponent
label_desc: Use image node_id 12 for calling the BasePipeline obj's underlying member method code with example usage: obj.get_hyperparameter_search_space(feat_type, dataset_properties) and returns: self