def test_persist_and_load(
training_data: TrainingData,
default_sklearn_intent_classifier: SklearnIntentClassifier,
default_model_storage: ModelStorage,
default_execution_context: ExecutionContext,
train_and_preprocess: Callable[..., Tuple[TrainingData, List[GraphComponent]]],
spacy_nlp_component: SpacyNLP,
spacy_model: SpacyModel,
):
training_data = spacy_nlp_component.process_training_data(
training_data, spacy_model
)
training_data, loaded_pipeline = train_and_preprocess(
pipeline=[{"component": SpacyTokenizer}, {"component": SpacyFeaturizer}],
training_data=training_data,
)
default_sklearn_intent_classifier.train(training_data)
loaded = SklearnIntentClassifier.load(
SklearnIntentClassifier.get_default_config(),
default_model_storage,
Resource("sklearn"),
default_execution_context,
)
predicted = copy.deepcopy(training_data)
actual = copy.deepcopy(training_data)
loaded_messages = loaded.process(predicted.training_examples)
trained_messages = default_sklearn_intent_classifier.process(
actual.training_examples
)
for m1, m2 in zip(loaded_messages, trained_messages):
assert m1.get("intent") == m2.get("intent")
def default_sklearn_intent_classifier(
default_model_storage: ModelStorage,
default_execution_context: ExecutionContext):
return SklearnIntentClassifier.create(
SklearnIntentClassifier.get_default_config(),
default_model_storage,
Resource("sklearn"),
default_execution_context,
)
def test_loading_from_storage_fail(
training_data: TrainingData,
default_model_storage: ModelStorage,
default_execution_context: ExecutionContext,
caplog: LogCaptureFixture,
):
with caplog.at_level(logging.DEBUG):
loaded = SklearnIntentClassifier.load(
SklearnIntentClassifier.get_default_config(),
default_model_storage,
Resource("test"),
default_execution_context,
)
assert isinstance(loaded, SklearnIntentClassifier)
assert any("Resource 'test' doesn't exist." in message
for message in caplog.messages)
def test_process_unfeaturized_input(
training_data: TrainingData,
default_sklearn_intent_classifier: SklearnIntentClassifier,
default_model_storage: ModelStorage,
default_execution_context: ExecutionContext,
train_and_preprocess: Callable[..., Tuple[TrainingData,
List[GraphComponent]]],
spacy_nlp_component: SpacyNLP,
spacy_model: SpacyModel,
):
training_data = spacy_nlp_component.process_training_data(
training_data, spacy_model)
training_data, loaded_pipeline = train_and_preprocess(
pipeline=[
{
"component": SpacyTokenizer
},
{
"component": SpacyFeaturizer
},
],
training_data=training_data,
)
default_sklearn_intent_classifier.train(training_data)
classifier = SklearnIntentClassifier.load(
SklearnIntentClassifier.get_default_config(),
default_model_storage,
Resource("sklearn"),
default_execution_context,
)
message_text = "message text"
message = Message(data={TEXT: message_text})
processed_message = classifier.process([message])[0]
assert processed_message.get(TEXT) == message_text
assert not processed_message.get(INTENT)