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())
