code: def test_load_pyfunc(tmp_path):
      X, y = get_housing_data()
  
      model = sklearn.ensemble.RandomForestRegressor(n_estimators=100)
      model.fit(X, y)
  
      explainer_original = shap.Explainer(
          model.predict, X, algorithm="permutation"
      )
      shap_values_original = explainer_original(X[:2])
      path = str(tmp_path.joinpath("pyfunc_test"))
      mlflow.shap.save_explainer(explainer_original, path)
  
      explainer_pyfunc = mlflow.shap._load_pyfunc(path)
      shap_values_new = explainer_pyfunc.predict(X[:2])
  
      np.testing.assert_allclose(
          shap_values_original.values,
          shap_values_new,
          rtol=100,
          atol=100,
      )
  
imports: import json
  from unittest import mock
  import numpy
  import pandas
  import pytest
  import shap
  import sklearn
  from numba import njit
  from packaging.version import Version
  from sklearn.datasets import fetch_california_housing, load_diabetes
  import mlflow
  import mlflow.pyfunc.scoring_server
  from mlflow import MlflowClient
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils import PYTHON_VERSION
  from mlflow.utils.model_utils import _get_flavor_configuration
  from tests.helper_functions import _assert_pip_requirements, _compare_logged_code_paths, _mlflow_major_version_string, pyfunc_serve_and_score_model
label_desc: Use image node_id 7 for calling a global function with example usage: test_load_pyfunc(tmp_path) without return types