code: def lending_club_split_dataset_and_model() -> (
      Tuple[Dataset, Dataset, Pipeline]
  ):
      """Return Adult train and val datasets and trained RandomForestClassifier model."""
      train_ds, test_ds = lending_club.load_data(as_train_test=True)
      model = lending_club.load_fitted_model()
      return train_ds, test_ds, model
  
imports: import logging
  import random
  from typing import Tuple
  import matplotlib.pyplot
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import load_diabetes, load_iris
  from sklearn.ensemble import AdaBoostClassifier, GradientBoostingRegressor, RandomForestClassifier
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import KBinsDiscretizer
  from deepchecks.core.check_result import CheckResult
  from deepchecks.tabular import Context, Dataset, TrainTestCheck
  from deepchecks.tabular.datasets.classification import lending_club
  from deepchecks.utils.logger import set_verbosity
label_desc: Use image node_id 17 for calling a global function with example usage: lending_club_split_dataset_and_model() and returns: train_ds,  test_ds,  model