def test_model_finetuning_nlu_new_label_already_in_domain(
tmp_path: Path,
monkeypatch: MonkeyPatch,
trained_rasa_model: Text,
default_nlu_data: Text,
default_config_path: Text,
default_domain_path: Text,
):
mocked_nlu_training = AsyncMock(return_value="")
monkeypatch.setattr(rasa.nlu, rasa.nlu.train.__name__, mocked_nlu_training)
(tmp_path / "models").mkdir()
output = str(tmp_path / "models")
old_nlu = rasa.shared.utils.io.read_yaml_file(default_nlu_data)
# This intent exists in `default_domain_path` but not yet in the nlu data
old_nlu["nlu"].append({"intent": "why", "examples": "whyy??"})
new_nlu_path = tmp_path / "new_nlu.yml"
rasa.shared.utils.io.write_yaml(old_nlu, new_nlu_path)
with pytest.raises(SystemExit):
train_nlu(
default_config_path,
str(new_nlu_path),
domain=default_domain_path,
output=output,
model_to_finetune=trained_rasa_model,
)
mocked_nlu_training.assert_not_called()
def test_model_finetuning_new_domain_label_stops_all_training(
tmp_path: Path,
monkeypatch: MonkeyPatch,
trained_moodbot_path: Text,
):
mocked_core_training = AsyncMock()
mocked_nlu_training = AsyncMock()
monkeypatch.setattr(rasa.core, rasa.core.train.__name__,
mocked_core_training)
monkeypatch.setattr(rasa.nlu, rasa.nlu.train.__name__, mocked_nlu_training)
(tmp_path / "models").mkdir()
output = str(tmp_path / "models")
old_domain = rasa.shared.utils.io.read_yaml_file(
"examples/moodbot/domain.yml")
old_domain["intents"].append("a_new_one")
new_domain_path = tmp_path / "new_domain.yml"
rasa.shared.utils.io.write_yaml(old_domain, new_domain_path)
with pytest.raises(SystemExit):
train(
domain=str(new_domain_path),
config="examples/moodbot/config.yml",
training_files=[
"examples/moodbot/data/stories.yml",
"examples/moodbot/data/nlu.yml",
],
output=output,
model_to_finetune=trained_moodbot_path,
)
mocked_core_training.assert_not_called()
mocked_nlu_training.assert_not_called()
def test_model_finetuning_nlu_new_entity(
tmp_path: Path,
monkeypatch: MonkeyPatch,
trained_nlu_moodbot_path: Text,
):
mocked_nlu_training = AsyncMock(return_value="")
monkeypatch.setattr(rasa.nlu, rasa.nlu.train.__name__, mocked_nlu_training)
(tmp_path / "models").mkdir()
output = str(tmp_path / "models")
old_nlu = rasa.shared.utils.io.read_yaml_file(
"examples/moodbot/data/nlu.yml")
old_nlu["nlu"][-1]["examples"] = "-[blah](something)"
new_nlu_path = tmp_path / "new_nlu.yml"
rasa.shared.utils.io.write_yaml(old_nlu, new_nlu_path)
with pytest.raises(SystemExit):
train_nlu(
"examples/moodbot/config.yml",
str(new_nlu_path),
domain="examples/moodbot/domain.yml",
output=output,
model_to_finetune=trained_nlu_moodbot_path,
)
mocked_nlu_training.assert_not_called()
def test_model_finetuning_with_invalid_model_nlu(
tmp_path: Path,
monkeypatch: MonkeyPatch,
default_domain_path: Text,
default_stack_config: Text,
default_nlu_data: Text,
model_to_fine_tune: Text,
capsys: CaptureFixture,
):
mocked_nlu_training = AsyncMock(return_value="")
monkeypatch.setattr(rasa.nlu, rasa.nlu.train.__name__, mocked_nlu_training)
(tmp_path / "models").mkdir()
output = str(tmp_path / "models")
with pytest.raises(SystemExit):
train_nlu(
default_stack_config,
default_nlu_data,
domain=default_domain_path,
output=output,
model_to_finetune=model_to_fine_tune,
finetuning_epoch_fraction=1,
)
mocked_nlu_training.assert_not_called()
assert "No NLU model for finetuning found" in capsys.readouterr().out