code: def get_hyperparameter_search_space(
      feat_type: Optional[FEAT_TYPE_TYPE] = None,
      dataset_properties=None,
  ):
      cs = ConfigurationSpace()
  
      penalty = Constant("penalty", "l1")
      loss = CategoricalHyperparameter(
          "loss",
          ["hinge", "squared_hinge"],
          default_value="squared_hinge",
      )
      dual = Constant("dual", "False")
      # This is set ad-hoc
      tol = UniformFloatHyperparameter(
          "tol", 1e-5, 1e-1, default_value=1e-4, log=True
      )
      C = UniformFloatHyperparameter(
          "C", 0.03125, 32768, log=True, default_value=1.0
      )
      multi_class = Constant("multi_class", "ovr")
      # These are set ad-hoc
      fit_intercept = Constant("fit_intercept", "True")
      intercept_scaling = Constant("intercept_scaling", 1)
  
      cs.add_hyperparameters(
          [
              penalty,
              loss,
              dual,
              tol,
              C,
              multi_class,
              fit_intercept,
              intercept_scaling,
          ]
      )
  
      penalty_and_loss = ForbiddenAndConjunction(
          ForbiddenEqualsClause(penalty, "l1"),
          ForbiddenEqualsClause(loss, "hinge"),
      )
      cs.add_forbidden_clause(penalty_and_loss)
      return cs
  
file_path: auto-sklearn/autosklearn/pipeline/components/feature_preprocessing/liblinear_svc_preprocessor.py
imports: from typing import Optional
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.forbidden import ForbiddenAndConjunction, ForbiddenEqualsClause
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, Constant, UniformFloatHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
  from autosklearn.pipeline.constants import DENSE, INPUT, SPARSE, UNSIGNED_DATA
  from autosklearn.util.common import check_for_bool, check_none
label_desc: Use image node_id 5 for calling the LibLinear_Preprocessor obj's underlying member method code with example usage: obj.get_hyperparameter_search_space(feat_type, dataset_properties) and returns: cs