code: def test_sktime_save_model_raises_invalid_serialization_format(
      auto_arima_model, model_path
  ):
      """Test save_model call raises error with invalid serialization format."""
      with pytest.raises(
          MlflowException, match="Unrecognized serialization format: "
      ):
          flavor.save_model(
              sktime_model=auto_arima_model,
              path=model_path,
              serialization_format="json",
          )
  
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 20 for calling a global function with example usage: test_sktime_save_model_raises_invalid_serialization_format(auto_arima_model, model_path) without return types