def test_should_be_deserializable(self):
# When
register_processing_unit(TestIntentClassifier)
register_processing_unit(TestSlotFiller)
config = ProbabilisticIntentParserConfig(
intent_classifier_config=TestIntentClassifierConfig(),
slot_filler_config=TestSlotFillerConfig()
)
parser_dict = {
"unit_name": "probabilistic_intent_parser",
"slot_fillers": [
{
"intent": "MakeCoffee",
"slot_filler_name": "slot_filler_MakeCoffee"
},
{
"intent": "MakeTea",
"slot_filler_name": "slot_filler_MakeTea"
}
],
"config": config.to_dict(),
}
self.tmp_file_path.mkdir()
(self.tmp_file_path / "intent_classifier").mkdir()
(self.tmp_file_path / "slot_filler_MakeCoffee").mkdir()
(self.tmp_file_path / "slot_filler_MakeTea").mkdir()
self.writeJsonContent(self.tmp_file_path / "intent_parser.json",
parser_dict)
self.writeJsonContent(
self.tmp_file_path / "intent_classifier" / "metadata.json",
{"unit_name": "test_intent_classifier"})
self.writeJsonContent(
self.tmp_file_path / "slot_filler_MakeCoffee" / "metadata.json",
{"unit_name": "test_slot_filler"})
self.writeJsonContent(
self.tmp_file_path / "slot_filler_MakeTea" / "metadata.json",
{"unit_name": "test_slot_filler"})
# When
parser = ProbabilisticIntentParser.from_path(self.tmp_file_path)
# Then
self.assertDictEqual(parser.config.to_dict(), config.to_dict())
self.assertIsNotNone(parser.intent_classifier)
self.assertListEqual(sorted(parser.slot_fillers),
["MakeCoffee", "MakeTea"])
def test_should_be_deserializable(self):
# When
class TestIntentClassifierConfig(ProcessingUnitConfig):
unit_name = "test_intent_classifier"
def to_dict(self):
return {"unit_name": self.unit_name}
@classmethod
def from_dict(cls, obj_dict):
return TestIntentClassifierConfig()
class TestIntentClassifier(IntentClassifier):
unit_name = "test_intent_classifier"
config_type = TestIntentClassifierConfig
def get_intent(self, text, intents_filter):
return None
def fit(self, dataset):
return self
def to_dict(self):
return {
"unit_name": self.unit_name,
}
@classmethod
def from_dict(cls, unit_dict):
conf = cls.config_type()
return TestIntentClassifier(conf)
class TestSlotFillerConfig(ProcessingUnitConfig):
unit_name = "test_slot_filler"
def to_dict(self):
return {"unit_name": self.unit_name}
@classmethod
def from_dict(cls, obj_dict):
return TestSlotFillerConfig()
class TestSlotFiller(SlotFiller):
unit_name = "test_slot_filler"
config_type = TestSlotFillerConfig
def get_slots(self, text):
return []
def fit(self, dataset, intent):
return self
def to_dict(self):
return {
"unit_name": self.unit_name,
}
@classmethod
def from_dict(cls, unit_dict):
conf = cls.config_type()
return TestSlotFiller(conf)
register_processing_unit(TestIntentClassifier)
register_processing_unit(TestSlotFiller)
config = ProbabilisticIntentParserConfig(
intent_classifier_config=TestIntentClassifierConfig(),
slot_filler_config=TestSlotFillerConfig())
parser_dict = {
"unit_name": "probabilistic_intent_parser",
"intent_classifier": {
"unit_name": "test_intent_classifier"
},
"slot_fillers": {
"MakeCoffee": {
"unit_name": "test_slot_filler"
},
"MakeTea": {
"unit_name": "test_slot_filler"
}
},
"config": config.to_dict(),
}
# When
parser = ProbabilisticIntentParser.from_dict(parser_dict)
# Then
self.assertDictEqual(parser.config.to_dict(), config.to_dict())
self.assertIsNotNone(parser.intent_classifier)
self.assertListEqual(sorted(parser.slot_fillers),
["MakeCoffee", "MakeTea"])