code: def get_encoded_and_regular_cols(cols, onehot_dict):
      """return a list of onehot encoded cols and a list of remainder cols."""
      encoded_cols = []
      for enc_cols in onehot_dict.values():
          if len(enc_cols) > 1:
              encoded_cols.extend(enc_cols)
      regular_cols = [col for col in cols if col not in encoded_cols]
      return encoded_cols, regular_cols
  
imports: from functools import partial
  import re
  from collections import Counter
  from typing import List, Union
  import warnings
  import numpy
  import pandas
  from pandas.api.types import is_numeric_dtype, is_categorical_dtype
  from dtreeviz.trees import ShadowDecTree
  from sklearn.metrics import make_scorer
  from sklearn.base import clone
  from sklearn.pipeline import Pipeline
  from sklearn.model_selection import KFold, StratifiedKFold
  from joblib import Parallel, delayed
label_desc: Use image node_id 6 for calling a global function with example usage: get_encoded_and_regular_cols(cols, onehot_dict) and returns: encoded_cols,  regular_cols