code: def test_explain_catboost_catboost_wrong_importance_type(
      iris_train, importance_type
  ):
      x, y, feature_names, target = iris_train
      train = Pool(x, y)
      catb = CatBoostClassifier(
          iterations=10,
          learning_rate=1,
          depth=2,
          loss_function="MultiClass",
      )
      catb.fit(train)
      with pytest.raises(ValueError):
          res = explain_weights(
              catb, importance_type=importance_type, pool=train
          )
  
file_path: eli5/tests/test_catboost.py
imports: from __future__ import absolute_import
  import pytest
  from catboost import CatBoostClassifier, CatBoostRegressor, CatBoost, Pool
  import numpy
  from eli5.explain import explain_weights
  from .utils import format_as_all
  from eli5.catboost import _is_regression
label_desc: Use image node_id 4 for calling a global function with example usage: test_explain_catboost_catboost_wrong_importance_type(iris_train, importance_type) without return types