class_docstr: Base class for all pipeline objects.
  
  Notes
  -----
  This class should not be instantiated, only subclassed.
code: def set_hyperparameters(
      self,
      configuration,
      feat_type: Optional[FEAT_TYPE_TYPE] = None,
      init_params=None,
  ):
      self.config = configuration
  
      for node_idx, n_ in enumerate(self.steps):
          node_name, node = n_
  
          sub_configuration_space = (
              node.get_hyperparameter_search_space(
                  feat_type=feat_type,
                  dataset_properties=self.dataset_properties,
              )
          )
          sub_config_dict = {}
          for param in configuration:
              if param.startswith("%s:" % node_name):
                  value = configuration[param]
                  new_name = param.replace("%s:" % node_name, "", 1)
                  sub_config_dict[new_name] = value
  
          sub_configuration = Configuration(
              sub_configuration_space, values=sub_config_dict
          )
  
          if init_params is not None:
              sub_init_params_dict = {}
              for param in init_params:
                  if param.startswith("%s:" % node_name):
                      value = init_params[param]
                      new_name = param.replace("%s:" % node_name, "", 1)
                      sub_init_params_dict[new_name] = value
          else:
              sub_init_params_dict = None
  
          if isinstance(
              node,
              (AutoSklearnChoice, AutoSklearnComponent, BasePipeline),
          ):
              node.set_hyperparameters(
                  feat_type=feat_type,
                  configuration=sub_configuration,
                  init_params=sub_init_params_dict,
              )
          else:
              raise NotImplementedError("Not supported yet!")
  
      # In-code check to make sure init params
      # is checked after pipeline creation
      self._check_init_params_honored(init_params)
  
      return self
  
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 11 for calling the BasePipeline obj's underlying member method code with example usage: obj.set_hyperparameters(configuration, feat_type, init_params) and returns: self