code: def test_classes_exceptions_prediction_labels(self):
      X_train, X_test, y_train, y_test, _, _ = create_cancer_data(
          return_dataframe=True
      )
  
      y_train[0] = 2
      y_test[0] = 2
  
      X_train[TARGET] = y_train
      X_test[TARGET] = y_test
  
      model = MagicMock()
      model.predict.return_value = np.array([0, 1])
  
      with pytest.raises(UserConfigValidationException) as ucve:
          RAIInsights(
              model=model,
              train=X_train,
              test=X_test,
              target_column=TARGET,
              task_type="classification",
              classes=[0, 1, 2],
          )
      assert (
          "The train labels and distinct values in "
          + "predictions (train data) do not match"
          in str(ucve.value)
      )
  
imports: import logging
  import random
  from unittest.mock import MagicMock
  import numpy
  import pandas
  import pytest
  from lightgbm import LGBMClassifier
  from tests.common_utils import RandomForecastingModel, RandomForecastingModelWithQuantiles, create_iris_data, create_tiny_forecasting_dataset
  from rai_test_utils.datasets.tabular import create_binary_classification_dataset, create_cancer_data, create_housing_data
  from rai_test_utils.models.lightgbm import create_lightgbm_classifier
  from rai_test_utils.models.sklearn import create_sklearn_random_forest_regressor
  from raiutils.exceptions import UserConfigValidationException
  from responsibleai import RAIInsights
  from responsibleai.feature_metadata import FeatureMetadata
  from responsibleai.rai_insights.rai_insights import _MODEL_METHOD_EXCEPTION_MESSAGE
label_desc: Use image node_id 15 for calling the TestRAIInsightsValidations obj's underlying member method code with example usage: obj.test_classes_exceptions_prediction_labels() without return types