def test_should_be_deserializable_when_fitted_without_slots(self):
# Given
dataset = {
"language": "en",
"intents": {
"intent1": {
"utterances": [{
"data": [{
"text":
"This is an utterance without "
"slots"
}]
}]
}
},
"entities": {}
}
shared = self.get_shared_data(dataset)
slot_filler = CRFSlotFiller(**shared)
slot_filler.fit(dataset, intent="intent1")
slot_filler.persist(self.tmp_file_path)
loaded_slot_filler = CRFSlotFiller.from_path(self.tmp_file_path,
**shared)
# When
slots = loaded_slot_filler.get_slots(
"This is an utterance without slots")
# Then
self.assertListEqual([], slots)
def test_should_be_deserializable_before_fit(self):
# Given
features_factories = [
{
"factory_name": ShapeNgramFactory.name,
"args": {"n": 1},
"offsets": [0]
},
{
"factory_name": IsDigitFactory.name,
"args": {},
"offsets": [-1, 0]
}
]
slot_filler_config = CRFSlotFillerConfig(
feature_factory_configs=features_factories)
slot_filler_dict = {
"unit_name": "crf_slot_filler",
"crf_model_file": None,
"language_code": None,
"intent": None,
"slot_name_mapping": None,
"config": slot_filler_config.to_dict()
}
metadata = {"unit_name": "crf_slot_filler"}
self.tmp_file_path.mkdir()
self.writeJsonContent(self.tmp_file_path / "metadata.json", metadata)
self.writeJsonContent(self.tmp_file_path / "slot_filler.json",
slot_filler_dict)
# When
slot_filler = CRFSlotFiller.from_path(self.tmp_file_path)
# Then
expected_features_factories = [
{
"factory_name": ShapeNgramFactory.name,
"args": {"n": 1},
"offsets": [0]
},
{
"factory_name": IsDigitFactory.name,
"args": {},
"offsets": [-1, 0]
}
]
expected_language = None
expected_config = CRFSlotFillerConfig(
feature_factory_configs=expected_features_factories)
expected_intent = None
expected_slot_name_mapping = None
expected_crf_model = None
self.assertEqual(slot_filler.crf_model, expected_crf_model)
self.assertEqual(slot_filler.language, expected_language)
self.assertEqual(slot_filler.intent, expected_intent)
self.assertEqual(slot_filler.slot_name_mapping,
expected_slot_name_mapping)
self.assertDictEqual(expected_config.to_dict(),
slot_filler.config.to_dict())
def test_should_get_slots_after_deserialization(self):
# Given
dataset_stream = io.StringIO("""
---
type: intent
name: MakeTea
utterances:
- make me [number_of_cups:snips/number](one) cup of tea
- i want [number_of_cups] cups of tea please
- can you prepare [number_of_cups] cups of tea ?""")
dataset = Dataset.from_yaml_files("en", [dataset_stream]).json
intent = "MakeTea"
shared = self.get_shared_data(dataset)
shared[RANDOM_STATE] = 42
slot_filler = CRFSlotFiller(**shared)
slot_filler.fit(dataset, intent)
slot_filler.persist(self.tmp_file_path)
deserialized_slot_filler = CRFSlotFiller.from_path(
self.tmp_file_path, **shared)
# When
slots = deserialized_slot_filler.get_slots("make me two cups of tea")
# Then
expected_slots = [
unresolved_slot(match_range={
START: 8,
END: 11
},
value='two',
entity='snips/number',
slot_name='number_of_cups')
]
self.assertListEqual(expected_slots, slots)
def test_should_get_slots_after_deserialization(self):
# Given
dataset = BEVERAGE_DATASET
config = CRFSlotFillerConfig(random_seed=42)
intent = "MakeTea"
slot_filler = CRFSlotFiller(config)
slot_filler.fit(dataset, intent)
slot_filler.persist(self.tmp_file_path)
custom_entity_parser = slot_filler.custom_entity_parser
builtin_entity_parser = slot_filler.builtin_entity_parser
deserialized_slot_filler = CRFSlotFiller.from_path(
self.tmp_file_path,
custom_entity_parser=custom_entity_parser,
builtin_entity_parser=builtin_entity_parser)
# When
slots = deserialized_slot_filler.get_slots("make me two cups of tea")
# Then
expected_slots = [
unresolved_slot(match_range={
START: 8,
END: 11
},
value='two',
entity='snips/number',
slot_name='number_of_cups')
]
self.assertListEqual(expected_slots, slots)
def test_should_be_deserializable(self):
# Given
language = LANGUAGE_EN
feature_factories = [{
"factory_name": ShapeNgramFactory.name,
"args": {
"n": 1,
"language_code": language
},
"offsets": [0]
}, {
"factory_name": IsDigitFactory.name,
"args": {},
"offsets": [-1, 0]
}]
slot_filler_config = CRFSlotFillerConfig(
feature_factory_configs=feature_factories)
slot_filler_dict = {
"unit_name": "crf_slot_filler",
"crf_model_file": "foobar.crfsuite",
"language_code": "en",
"intent": "dummy_intent_1",
"slot_name_mapping": {
"dummy_intent_1": {
"dummy_slot_name": "dummy_entity_1",
}
},
"config": slot_filler_config.to_dict()
}
metadata = {"unit_name": "crf_slot_filler"}
self.tmp_file_path.mkdir()
self.writeJsonContent(self.tmp_file_path / "metadata.json", metadata)
self.writeJsonContent(self.tmp_file_path / "slot_filler.json",
slot_filler_dict)
self.writeFileContent(self.tmp_file_path / "foobar.crfsuite",
"foo bar")
# When
slot_filler = CRFSlotFiller.from_path(self.tmp_file_path)
# Then
expected_language = LANGUAGE_EN
expected_feature_factories = [{
"factory_name": ShapeNgramFactory.name,
"args": {
"n": 1,
"language_code": language
},
"offsets": [0]
}, {
"factory_name": IsDigitFactory.name,
"args": {},
"offsets": [-1, 0]
}]
expected_config = CRFSlotFillerConfig(
feature_factory_configs=expected_feature_factories)
expected_intent = "dummy_intent_1"
expected_slot_name_mapping = {
"dummy_intent_1": {
"dummy_slot_name": "dummy_entity_1",
}
}
self.assertEqual(slot_filler.language, expected_language)
self.assertEqual(slot_filler.intent, expected_intent)
self.assertEqual(slot_filler.slot_name_mapping,
expected_slot_name_mapping)
self.assertDictEqual(expected_config.to_dict(),
slot_filler.config.to_dict())
crf_path = Path(slot_filler.crf_model.modelfile.name)
self.assertFileContent(crf_path, "foo bar")
