code: def mape_score(y_true, y_pred):
      """returns Mean Absolute Percentage Error"""
      epsilon = np.finfo(np.float64).eps
      absolute_percentage_errors = np.abs(y_pred - y_true) / np.maximum(
          np.abs(y_true), epsilon
      )
      mape = np.average(absolute_percentage_errors)
      return mape
  
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 4 for calling a global function with example usage: mape_score(y_true, y_pred) and returns: mape