code: def test_predict_var_signature_saved_correctly(
      auto_arima_model, test_data_airline, model_path, use_signature
  ):
      """Test saving of mlflow signature for native sktime predict_var method."""
      from mlflow.models import Model, infer_signature
  
      from sktime.utils import mlflow_sktime
  
      # Note: Signature inference fails on native model predict_interval/predict_quantiles
      prediction = auto_arima_model.predict_var()
      signature = (
          infer_signature(test_data_airline, prediction)
          if use_signature
          else None
      )
      mlflow_sktime.save_model(
          auto_arima_model, path=model_path, signature=signature
      )
      mlflow_model = Model.load(model_path)
      assert signature == mlflow_model.signature
  
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 18 for calling a global function with example usage: test_predict_var_signature_saved_correctly(auto_arima_model, test_data_airline, model_path, use_signature) without return types