code: def _save_model(model, path, serialization_format):
      _check_mlflow_dependencies(severity="error")
      from mlflow.exceptions import MlflowException
      from mlflow.protos.databricks_pb2 import INTERNAL_ERROR
  
      if serialization_format not in SUPPORTED_SERIALIZATION_FORMATS:
          raise MlflowException(
              message="Unrecognized serialization format: "
              f"{serialization_format}.",
              error_code=INTERNAL_ERROR,
          )
      model.save(path=path, serialization_format=serialization_format)
  
file_path: sktime/sktime/utils/mlflow_sktime.py
imports: import logging
  import os
  import pandas
  import yaml
  import sktime
  from sktime import utils
  from sktime.base._serialize import load
  from sktime.utils.multiindex import flatten_multiindex
  from sktime.utils.validation._dependencies import _check_mlflow_dependencies
label_desc: Use image node_id 6 for calling a global function with example usage: _save_model(model, path, serialization_format) without return types