code: def test_log_model_with_code_paths(shap_model):
      artifact_path = "model"
      with mlflow.start_run(), mock.patch(
          "mlflow.shap._add_code_from_conf_to_system_path"
      ) as add_mock:
          mlflow.shap.log_explainer(
              shap_model, artifact_path, code_paths=[__file__]
          )
          model_uri = mlflow.get_artifact_uri(artifact_path)
          _compare_logged_code_paths(
              __file__, model_uri, mlflow.shap.FLAVOR_NAME
          )
          mlflow.shap.load_explainer(model_uri)
          add_mock.assert_called()
  
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 15 for calling a global function with example usage: test_log_model_with_code_paths(shap_model) without return types