code: def get_generated_cols(X_original, X_transformed, to_transform):
      """
      Returns a list of the generated/transformed columns.
  
      Arguments:
          X_original: df
              the original (input) DataFrame.
          X_transformed: df
              the transformed (current) DataFrame.
          to_transform: [str]
              a list of columns that were transformed (as in the original DataFrame), commonly self.feature_names_in.
  
      Output:
          a list of columns that were transformed (as in the current DataFrame).
      """
      original_cols = list(X_original.columns)
  
      if len(to_transform) > 0:
          [original_cols.remove(c) for c in to_transform]
  
      current_cols = list(X_transformed.columns)
      if len(original_cols) > 0:
          [current_cols.remove(c) for c in original_cols]
  
      return current_cols
  
imports: from abc import abstractmethod
  from enum import Enum, auto
  import warnings
  import pandas
  import numpy
  import sklearn.base
  from pandas.api.types import is_object_dtype, is_string_dtype, is_numeric_dtype
  from pandas.core.dtypes.dtypes import CategoricalDtype
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.exceptions import NotFittedError
  from typing import Dict, List, Optional, Union
  from scipy.sparse import csr_matrix
  from sklearn.preprocessing import LabelEncoder
label_desc: Use image node_id 7 for calling a global function with example usage: get_generated_cols(X_original, X_transformed, to_transform) and returns: current_cols