code: def test_unwrap_python_model_from_pyfunc_class():
      class MyModel(PythonModel):
          def __init__(self, param_1: str, param_2: int):
              self.param_1 = param_1
              self.param_2 = param_2
  
          def predict(self, context, model_input, params=None):
              return model_input + self.param_2
  
          def upper_param_1(self):
              return self.param_1.upper()
  
      with mlflow.start_run():
          model = MyModel("this is test message", 2)
          model_uri = log_model(
              python_model=model, artifact_path="mlruns"
          ).model_uri
          loaded_model = load_model(model_uri).unwrap_python_model()
          assert isinstance(loaded_model, MyModel)
          assert loaded_model.param_1 == "this is test message"
          assert loaded_model.param_2 == 2
          assert loaded_model.predict(None, 1) == 3
          assert loaded_model.upper_param_1() == "THIS IS TEST MESSAGE"
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_unwrap_python_model_from_pyfunc_class() and returns: unknown, self