def test_resolve_callbacks_multi_error(tmpdir): model = DummyClassifier() trainer = Trainer(fast_dev_run=True, default_root_dir=tmpdir) task = MultiFinetuneClassificationTask(model, loss_fn=F.nll_loss) with pytest.raises(MisconfigurationException, match="should create a list with only 1 callback"): trainer._resolve_callbacks(task, None)
def test_resolve_callbacks_override_warning(tmpdir): model = DummyClassifier() trainer = Trainer(fast_dev_run=True, default_root_dir=tmpdir) task = FinetuneClassificationTask(model, loss_fn=F.nll_loss) with pytest.warns(UserWarning, match="The model contains a default finetune callback"): trainer._resolve_callbacks(task, "test")
def test_resolve_callbacks_invalid_strategy(tmpdir): model = DummyClassifier() trainer = Trainer(fast_dev_run=True, default_root_dir=tmpdir) task = ClassificationTask(model, loss_fn=F.nll_loss) with pytest.raises( MisconfigurationException, match="should be a ``pytorch_lightning.callbacks.BaseFinetuning``" ): trainer._resolve_callbacks(task, EarlyStopping())