def test_featurizer(self, trained_policy: Policy, tmp_path: Path):
assert isinstance(trained_policy.featurizer, MaxHistoryTrackerFeaturizer)
assert trained_policy.featurizer.state_featurizer is None
trained_policy.persist(str(tmp_path))
loaded = trained_policy.__class__.load(str(tmp_path))
assert isinstance(loaded.featurizer, MaxHistoryTrackerFeaturizer)
assert loaded.featurizer.state_featurizer is None
async def test_persist_and_load(
self,
trained_policy: Policy,
default_domain: Domain,
tmp_path: Path,
should_finetune: bool,
stories_path: Text,
):
trained_policy.persist(str(tmp_path))
loaded = trained_policy.__class__.load(
str(tmp_path), should_finetune=should_finetune
)
assert loaded.finetune_mode == should_finetune
trackers = await train_trackers(
default_domain, stories_path, augmentation_factor=20
)
for tracker in trackers:
predicted_probabilities = loaded.predict_action_probabilities(
tracker, default_domain, RegexInterpreter()
)
actual_probabilities = trained_policy.predict_action_probabilities(
tracker, default_domain, RegexInterpreter()
)
assert predicted_probabilities == actual_probabilities
def test_featurizer(self, trained_policy: Policy, tmp_path: Path):
assert isinstance(trained_policy.featurizer,
FullDialogueTrackerFeaturizer)
assert isinstance(
trained_policy.featurizer.state_featurizer,
LabelTokenizerSingleStateFeaturizer,
)
trained_policy.persist(str(tmp_path))
loaded = trained_policy.__class__.load(str(tmp_path))
assert isinstance(loaded.featurizer, FullDialogueTrackerFeaturizer)
assert isinstance(loaded.featurizer.state_featurizer,
LabelTokenizerSingleStateFeaturizer)
async def test_persist_and_load(self, trained_policy: Policy,
default_domain: Domain, tmp_path: Path):
trained_policy.persist(str(tmp_path))
loaded = trained_policy.__class__.load(str(tmp_path))
trackers = await train_trackers(default_domain, augmentation_factor=20)
for tracker in trackers:
predicted_probabilities = loaded.predict_action_probabilities(
tracker, default_domain)
actual_probabilities = trained_policy.predict_action_probabilities(
tracker, default_domain)
assert predicted_probabilities == actual_probabilities
def test_featurizer(self, trained_policy: Policy, tmp_path: Path):
assert isinstance(trained_policy.featurizer,
MaxHistoryTrackerFeaturizer)
assert trained_policy.featurizer.max_history == self.max_history
assert isinstance(trained_policy.featurizer.state_featurizer,
BinarySingleStateFeaturizer)
trained_policy.persist(str(tmp_path))
loaded = trained_policy.__class__.load(str(tmp_path))
assert isinstance(loaded.featurizer, MaxHistoryTrackerFeaturizer)
assert loaded.featurizer.max_history == self.max_history
assert isinstance(loaded.featurizer.state_featurizer,
BinarySingleStateFeaturizer)
def test_featurizer(self, trained_policy: Policy, tmp_path: Path):
assert trained_policy.featurizer is None
trained_policy.persist(str(tmp_path))
loaded = trained_policy.__class__.load(str(tmp_path))
assert loaded.featurizer is None
