# Copyright The PyTorch Lightning team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from functools import partial, wraps from unittest.mock import Mock import pytest from pytorch_lightning import LightningDataModule from pytorch_lightning.utilities.model_helpers import is_overridden from tests.helpers import BoringDataModule, BoringModel def test_is_overridden(): model = BoringModel() datamodule = BoringDataModule() # edge cases assert not is_overridden("whatever", None) with pytest.raises(ValueError, match="Expected a parent"): is_overridden("whatever", object()) assert not is_overridden("whatever", model) assert not is_overridden("whatever", model, parent=LightningDataModule) class TestModel(BoringModel): def foo(self): pass def bar(self): return 1 with pytest.raises(ValueError, match="The parent should define the method"): is_overridden("foo", TestModel()) # normal usage assert is_overridden("training_step", model) assert is_overridden("train_dataloader", datamodule) class WrappedModel(TestModel): def __new__(cls, *args, **kwargs): obj = super().__new__(cls) obj.foo = cls.wrap(obj.foo) obj.bar = cls.wrap(obj.bar) return obj @staticmethod def wrap(fn): @wraps(fn) def wrapper(): fn() return wrapper def bar(self): return 2 # `functools.wraps()` support assert not is_overridden("foo", WrappedModel(), parent=TestModel) assert is_overridden("bar", WrappedModel(), parent=TestModel) # `Mock` support mock = Mock(spec=BoringModel, wraps=model) assert is_overridden("training_step", mock) mock = Mock(spec=BoringDataModule, wraps=datamodule) assert is_overridden("train_dataloader", mock) # `partial` support model.training_step = partial(model.training_step) assert is_overridden("training_step", model)