class_docstr: Base class for all pipeline objects.
  
  Notes
  -----
  This class should not be instantiated, only subclassed.
code: def fit_transformer(self, X, y, fit_params=None):
      self.num_targets = 1 if len(y.shape) == 1 else y.shape[1]
      if fit_params is None:
          fit_params = {}
      fit_params = {
          key.replace(":", "__"): value
          for key, value in fit_params.items()
      }
      fit_params_steps = self._check_fit_params(**fit_params)
      Xt = self._fit(X, y, **fit_params_steps)
      return Xt, fit_params_steps[self.steps[-1][0]]
  
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 3 for calling the BasePipeline obj's underlying member method code with example usage: obj.fit_transformer(X, y, fit_params) and returns: Xt,  fit_params_steps