code: def iris_binary_string_split_dataset_and_model(
      iris,
  ) -> Tuple[Dataset, Dataset, DecisionTreeClassifier]:
      """Return Iris train and test datasets and trained DecisionTreeClassifier model."""
      iris = iris.copy()
      iris.loc[iris["target"] != 2, "target"] = "a"
      iris.loc[iris["target"] == 2, "target"] = "b"
      train, test = train_test_split(
          iris, test_size=0.33, random_state=42
      )
      train_ds = Dataset(train, label="target")
      test_ds = Dataset(test, label="target")
      clf = DecisionTreeClassifier(random_state=0)
      clf.fit(train_ds.features_columns, train_ds.label_col)
      return train_ds, test_ds, clf
  
imports: import logging
  import random
  from typing import Any, Dict, Optional, Tuple
  import numpy
  import pandas
  import pytest
  from catboost import CatBoostClassifier, CatBoostRegressor
  from hamcrest import any_of, assert_that, instance_of, only_contains
  from hamcrest.core.matcher import Matcher
  from lightgbm import LGBMClassifier, LGBMRegressor
  from sklearn.compose import ColumnTransformer
  from sklearn.ensemble import AdaBoostClassifier, AdaBoostRegressor
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import FunctionTransformer, OrdinalEncoder
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.utils import shuffle
  from xgboost import XGBClassifier, XGBRegressor
  from deepchecks.core.check_result import CheckFailure, CheckResult
  from deepchecks.core.checks import SingleDatasetBaseCheck
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.core.errors import DeepchecksBaseError
  from deepchecks.core.suite import BaseSuite, SuiteResult
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.datasets.classification import adult, phishing
  from deepchecks.tabular.datasets.regression import avocado
  from deepchecks.utils.logger import set_verbosity
label_desc: Use image node_id 22 for calling a global function with example usage: iris_binary_string_split_dataset_and_model(iris) and returns: train_ds,  test_ds,  clf