code: def test_serve_and_score_read_only_model_directory(
      sklearn_model, tmp_path
  ):
      model_path = str(tmp_path / "model")
      mlflow.sklearn.save_model(sklearn_model.model, path=model_path)
      os.chmod(
          model_path,
          S_IRUSR | S_IRGRP | S_IROTH | S_IXUSR | S_IXGRP | S_IXOTH,
      )
  
      scores = serve_and_score(model_path, sklearn_model.X_pred)
      np.testing.assert_array_almost_equal(scores, sklearn_model.y_pred)
  
imports: import os
  import sys
  from collections import namedtuple
  from io import BytesIO
  from pathlib import Path
  from stat import S_IRGRP, S_IROTH, S_IRUSR, S_IXGRP, S_IXOTH, S_IXUSR
  import numpy
  import pandas
  import pytest
  import sklearn
  from sklearn.datasets import load_iris
  from sklearn.linear_model import LogisticRegression
  import mlflow
  from mlflow.environment_variables import MLFLOW_ENV_ROOT
  from mlflow.pyfunc.scoring_server import CONTENT_TYPE_JSON
  from mlflow.utils.environment import _PYTHON_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME
  from mlflow.utils.virtualenv import _is_pyenv_available, _is_virtualenv_available
  from tests.helper_functions import pyfunc_serve_and_score_model
label_desc: Use image node_id 5 for calling a global function with example usage: test_serve_and_score_read_only_model_directory(sklearn_model, tmp_path) without return types