code: def test_optional_method_present(self):
      (
          X_train,
          X_test,
          y_train,
          y_test,
      ) = create_tiny_forecasting_dataset()
  
      model = RandomForecastingModelWithQuantiles()
      X_train = X_train.copy()
      X_test = X_test.copy()
      X_train[TARGET] = y_train
      X_test[TARGET] = y_test
  
      RAIInsights(
          model=model,
          train=X_train,
          test=X_test,
          target_column=TARGET,
          task_type="forecasting",
          feature_metadata=FeatureMetadata(
              datetime_features=["time"], time_series_id_features=["id"]
          ),
          forecasting_enabled=True,
      )
  
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 11 for calling the TestCounterfactualUserConfigValidations obj's underlying member method code with example usage: obj.test_optional_method_present() without return types