class_docstr: Base class for all pipeline objects.
  
  Notes
  -----
  This class should not be instantiated, only subclassed.
code: def __repr__(self):
      class_name = self.__class__.__name__
  
      configuration = {}
      self.config._populate_values()
      for hp_name in self.config:
          if self.config[hp_name] is not None:
              configuration[hp_name] = self.config[hp_name]
  
      configuration_string = "".join(
          [
              "configuration={\n  ",
              ",\n  ".join(
                  [
                      "'%s': %s"
                      % (hp_name, repr(configuration[hp_name]))
                      for hp_name in sorted(configuration)
                  ]
              ),
              "}",
          ]
      )
  
      if len(self.dataset_properties) > 0:
          dataset_properties_string = []
          dataset_properties_string.append("dataset_properties={")
          for i, item in enumerate(self.dataset_properties.items()):
              if i != 0:
                  dataset_properties_string.append(",\n  ")
              else:
                  dataset_properties_string.append("\n  ")
  
              if isinstance(item[1], str):
                  dataset_properties_string.append(
                      "'%s': '%s'" % (item[0], item[1])
                  )
              else:
                  dataset_properties_string.append(
                      "'%s': %s" % (item[0], item[1])
                  )
          dataset_properties_string.append("}")
          dataset_properties_string = "".join(dataset_properties_string)
  
          return_value = "%s(%s,\n%s)" % (
              class_name,
              configuration,
              dataset_properties_string,
          )
      else:
          return_value = "%s(%s)" % (class_name, configuration_string)
  
      return return_value
  
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 16 for calling the BasePipeline obj's underlying member method code with example usage: obj.__repr__() and returns: return_value