code: def test_model_save_load(
      sklearn_knn_model, iris_data, tmp_path, model_path
  ):
      sk_model_path = os.path.join(tmp_path, "knn.pkl")
      with open(sk_model_path, "wb") as f:
          pickle.dump(sklearn_knn_model, f)
  
      model_config = Model(run_id="test", artifact_path="testtest")
      mlflow.pyfunc.save_model(
          path=model_path,
          data_path=sk_model_path,
          loader_module=__name__,
          code_path=[__file__],
          mlflow_model=model_config,
      )
  
      reloaded_model_config = Model.load(
          os.path.join(model_path, "MLmodel")
      )
      assert model_config.__dict__ == reloaded_model_config.__dict__
      assert mlflow.pyfunc.FLAVOR_NAME in reloaded_model_config.flavors
      assert (
          mlflow.pyfunc.PY_VERSION
          in reloaded_model_config.flavors[mlflow.pyfunc.FLAVOR_NAME]
      )
      reloaded_model = mlflow.pyfunc.load_model(model_path)
      np.testing.assert_array_equal(
          sklearn_knn_model.predict(iris_data[0]),
          reloaded_model.predict(iris_data[0]),
      )
  
imports: import os
  import pickle
  import numpy
  import pytest
  import sklearn.datasets
  import sklearn.linear_model
  import sklearn.neighbors
  import yaml
  import mlflow
  import mlflow.pyfunc
  import mlflow.pyfunc.model
  import mlflow.sklearn
  from mlflow.exceptions import MlflowException
  from mlflow.models import Model, infer_signature
  from mlflow.models.utils import _read_example
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.environment import _mlflow_conda_env
  from mlflow.utils.file_utils import TempDir
  from mlflow.utils.model_utils import _get_flavor_configuration
  from tests.helper_functions import _assert_pip_requirements
label_desc: Use image node_id 7 for calling a global function with example usage: test_model_save_load(sklearn_knn_model, iris_data, tmp_path, model_path) without return types