code: def test_pyfunc_predict_proba_raises_invalid_dict_value(
      auto_arima_model, model_path
  ):
      """Test pyfunc predict_proba raises exception with invalid dict value."""
      from mlflow.exceptions import MlflowException
  
      from sktime.utils import mlflow_sktime
  
      auto_arima_model.pyfunc_predict_conf = {
          "predict_method": {"predict_proba": {"marginal": True}}
      }
      mlflow_sktime.save_model(
          sktime_model=auto_arima_model, path=model_path
      )
      loaded_pyfunc = mlflow_sktime.pyfunc.load_model(
          model_uri=model_path
      )
  
      with pytest.raises(
          MlflowException,
          match=f"Method {mlflow_sktime.SKTIME_PREDICT_PROBA} requires passing "
          f"quantile values.",
      ):
          loaded_pyfunc.predict(pd.DataFrame())
  
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 29 for calling a global function with example usage: test_pyfunc_predict_proba_raises_invalid_dict_value(auto_arima_model, model_path) without return types