code: def test_model_does_not_handle_missing_values(self):
      (
          X_train,
          X_test,
          y_train,
          y_test,
          feature_names,
          classes,
      ) = create_iris_data()
  
      model = create_sklearn_svm_classifier(X_train, y_train)
      X_train.at[1, "sepal length"] = np.nan
      X_test.at[1, "sepal length"] = np.nan
      X_train[LABELS] = y_train
      X_test[LABELS] = y_test
  
      with pytest.raises(
          UserConfigValidationException,
          match="The passed model cannot be "
          "used for getting predictions via predict",
      ):
          RAIInsights(
              model, X_train, X_test, LABELS, task_type="classification"
          )
  
file_path: responsible-ai-toolbox/responsibleai/tests/rai_insights/test_rai_insights_missing_values.py
imports: from enum import Enum
  import numpy
  import pandas
  import pytest
  from ml_wrappers.model.predictions_wrapper import PredictionsModelWrapperClassification
  from tests.common_utils import create_iris_data
  from rai_test_utils.models.sklearn import create_complex_classification_pipeline, create_sklearn_svm_classifier
  from raiutils.exceptions import UserConfigValidationException
  from responsibleai import RAIInsights
  from responsibleai._internal.constants import ManagerNames
  from responsibleai.feature_metadata import FeatureMetadata
label_desc: Use image node_id 1 for calling the TestRAIInsightsMissingValues obj's underlying member method code with example usage: obj.test_model_does_not_handle_missing_values() without return types