code: def transform(self, X):
      if self.preprocessor is None:
          raise NotImplementedError()
      with warnings.catch_warnings():
          warnings.filterwarnings("error")
          X_new = self.preprocessor.transform(X)
  
          # TODO write a unittest for this case
          if X_new.shape[1] == 0:
              raise ValueError("KernelPCA removed all features!")
  
          return X_new
  
file_path: auto-sklearn/autosklearn/pipeline/components/feature_preprocessing/kernel_pca.py
imports: from typing import Optional
  import warnings
  import numpy
  from ConfigSpace.conditions import EqualsCondition, InCondition
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, UniformFloatHyperparameter, UniformIntegerHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
  from autosklearn.pipeline.constants import DENSE, SPARSE, UNSIGNED_DATA
label_desc: Use image node_id 3 for calling the KernelPCA obj's underlying member method code with example usage: obj.transform(X) and returns: X_new