code: def test_auto_arima_model_pyfunc_output(
      auto_arima_model, model_path, serialization_format
  ):
      """Test auto arima prediction of loaded pyfunc model."""
      flavor.save_model(
          sktime_model=auto_arima_model,
          path=model_path,
          serialization_format=serialization_format,
      )
      loaded_pyfunc = flavor.pyfunc.load_model(model_uri=model_path)
  
      model_predict = auto_arima_model.predict(fh=FH)
      predict_conf = pd.DataFrame(
          [{"fh": FH, "predict_method": "predict"}]
      )
      pyfunc_predict = loaded_pyfunc.predict(predict_conf)
      np.testing.assert_array_equal(model_predict, pyfunc_predict)
  
      model_predict_interval = auto_arima_model.predict_interval(
          fh=FH, coverage=COVERAGE
      )
      predict_interval_conf = pd.DataFrame(
          [
              {
                  "fh": FH,
                  "predict_method": "predict_interval",
                  "coverage": COVERAGE,
              }
          ]
      )
      pyfunc_predict_interval = loaded_pyfunc.predict(
          predict_interval_conf
      )
      np.testing.assert_array_equal(
          model_predict_interval.values, pyfunc_predict_interval.values
      )
  
      model_predict_quantiles = auto_arima_model.predict_quantiles(
          fh=FH, alpha=ALPHA
      )
      predict_quantiles_conf = pd.DataFrame(
          [
              {
                  "fh": FH,
                  "predict_method": "predict_quantiles",
                  "alpha": ALPHA,
              }
          ]
      )
      pyfunc_predict_quantiles = loaded_pyfunc.predict(
          predict_quantiles_conf
      )
      np.testing.assert_array_equal(
          model_predict_quantiles.values,
          pyfunc_predict_quantiles.values,
      )
  
      model_predict_var = auto_arima_model.predict_var(fh=FH, cov=COV)
      predict_var_conf = pd.DataFrame(
          [{"fh": FH, "predict_method": "predict_var", "cov": COV}]
      )
      pyfunc_predict_var = loaded_pyfunc.predict(predict_var_conf)
      np.testing.assert_array_equal(
          model_predict_var.values, pyfunc_predict_var.values
      )
  
imports: import os
  from pathlib import Path
  from unittest import mock
  import boto3
  import flavor
  import moto
  import numpy
  import pandas
  import pytest
  from botocore.config import Config
  from sktime.datasets import load_airline, load_longley
  from sktime.datatypes import convert
  from sktime.forecasting.arima import AutoARIMA
  from sktime.forecasting.model_selection import temporal_train_test_split
  from sktime.forecasting.naive import NaiveForecaster
  import mlflow
  from mlflow import pyfunc
  from mlflow.exceptions import MlflowException
  from mlflow.models import Model, infer_signature
  from mlflow.models.utils import _read_example
  from mlflow.store.artifact.s3_artifact_repo import S3ArtifactRepository
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.environment import _mlflow_conda_env
label_desc: Use image node_id 9 for calling a global function with example usage: test_auto_arima_model_pyfunc_output(auto_arima_model, model_path, serialization_format) without return types