code: def test_signature_and_example_for_pyfunc_predict(
      auto_arima_model,
      model_path,
      test_data_airline,
      use_signature,
      use_example,
  ):
      """Test saving of mlflow signature and example for pyfunc predict."""
      from mlflow.models import Model, infer_signature
      from mlflow.models.utils import _read_example
  
      from sktime.utils import mlflow_sktime
  
      model_path_primary = model_path.joinpath("primary")
      model_path_secondary = model_path.joinpath("secondary")
      auto_arima_model.pyfunc_predict_conf = {
          "predict_method": {
              "predict": None,
              "predict_interval": {"coverage": [0.1, 0.9]},
              "predict_quantiles": {"alpha": [0.1, 0.9]},
              "predict_var": {"cov": False},
          }
      }
      mlflow_sktime.save_model(
          sktime_model=auto_arima_model, path=model_path_primary
      )
      loaded_pyfunc = mlflow_sktime.pyfunc.load_model(
          model_uri=model_path_primary
      )
  
      forecast = loaded_pyfunc.predict(pd.DataFrame())
      signature = (
          infer_signature(test_data_airline, forecast)
          if use_signature
          else None
      )
      example = (
          pd.DataFrame(test_data_airline[0:5].copy(deep=False))
          if use_example
          else None
      )
      mlflow_sktime.save_model(
          auto_arima_model,
          path=model_path_secondary,
          signature=signature,
          input_example=example,
      )
      mlflow_model = Model.load(model_path_secondary)
      assert signature == mlflow_model.signature
      if example is None:
          assert mlflow_model.saved_input_example_info is None
      else:
          r_example = _read_example(
              mlflow_model, model_path_secondary
          ).copy(deep=False)
          np.testing.assert_array_equal(r_example, example)
  
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 19 for calling a global function with example usage: test_signature_and_example_for_pyfunc_predict(auto_arima_model, model_path, test_data_airline, use_signature, use_example) without return types