code: def test_naive_forecaster_model_with_regressor_pyfunc_output(
      naive_forecaster_model_with_regressor,
      model_path,
      test_data_longley,
  ):
      """Test naive forecaster prediction of loaded pyfunc model."""
      from sktime.utils import mlflow_sktime
  
      _, _, _, X_test = test_data_longley
  
      naive_forecaster_model_with_regressor.pyfunc_predict_conf = {
          "predict_method": [
              "predict",
              "predict_interval",
              "predict_quantiles",
              "predict_var",
          ]
      }
      mlflow_sktime.save_model(
          sktime_model=naive_forecaster_model_with_regressor,
          path=model_path,
      )
      loaded_pyfunc = mlflow_sktime.pyfunc.load_model(
          model_uri=model_path
      )
  
      model_predict = naive_forecaster_model_with_regressor.predict(
          X=X_test
      )
      model_predict_interval = (
          naive_forecaster_model_with_regressor.predict_interval(
              X=X_test
          )
      )
      model_predict_interval.columns = flatten_multiindex(
          model_predict_interval
      )
      model_predict_quantiles = (
          naive_forecaster_model_with_regressor.predict_quantiles(
              X=X_test
          )
      )
      model_predict_quantiles.columns = flatten_multiindex(
          model_predict_quantiles
      )
      model_predict_var = (
          naive_forecaster_model_with_regressor.predict_var(X=X_test)
      )
      model_predictions = pd.concat(
          [
              model_predict,
              model_predict_interval,
              model_predict_quantiles,
              model_predict_var,
          ],
          axis=1,
          keys=[
              "model_predict",
              "model_predict_interval",
              "model_predict_quantiles",
              "model_predict_var",
          ],
      )
  
      pyfunc_predict = loaded_pyfunc.predict(X_test)
      np.testing.assert_array_equal(
          model_predictions.values, pyfunc_predict.values
      )
  
imports: import os
  import sys
  from pathlib import Path
  from unittest import mock
  import numpy
  import pandas
  import pytest
  from sktime.datasets import load_airline, load_arrow_head, load_longley
  from sktime.forecasting.arima import AutoARIMA
  from sktime.forecasting.naive import NaiveForecaster
  from sktime.split import temporal_train_test_split
  from sktime.utils.multiindex import flatten_multiindex
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 16 for calling a global function with example usage: test_naive_forecaster_model_with_regressor_pyfunc_output(naive_forecaster_model_with_regressor, model_path, test_data_longley) without return types