code: def _prepare_inputs(self, X, y=None, type_of_inputs='classic',
                        **kwargs):
      
      self.check_preprocessor()
      return check_input(X, y,
                         type_of_inputs=type_of_inputs,
                         preprocessor=self.preprocessor_,
                         estimator=self,
                         tuple_size=getattr(self, '_tuple_size', None),
                         **kwargs)
docs: Initializes the preprocessor and processes inputs. See `check_input`
      for more details.
  
      Parameters
      ----------
      input: array-like
        The input data array to check.
  
      y : array-like
        The input labels array to check.
  
      type_of_inputs: `str` {'classic', 'tuples'}
        The type of inputs to check. If 'classic', the input should be
        a 2D array-like of points or a 1D array like of indicators of points. If
        'tuples', the input should be a 3D array-like of tuples or a 2D
        array-like of indicators of tuples.
  
      **kwargs: dict
        Arguments to pass to check_input.
  
      Returns
      -------
      X : `numpy.ndarray`
        The checked input data array.
  
      y: `numpy.ndarray` (optional)
        The checked input labels array.