chore: import upstream snapshot with attribution

tests/pyfunc/test_pyfunc_class_methods.py

@@ -0,0 +1,25 @@
+import mlflow
+from mlflow.pyfunc import PythonModel, load_model, log_model
+
+
+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("mlruns", python_model=model).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"