def test_parse(self):
# Given / When
train(BEVERAGE_DATASET_PATH, str(self.tmp_file_path), config_path=None)
# When
with self.fail_if_exception("Failed to parse using CLI script"):
parse(str(self.tmp_file_path), "Make me two cups of coffee")
def test_train(self):
# Given / When
train(BEVERAGE_DATASET_PATH, str(self.tmp_file_path), config_path=None)
# Then
if not self.tmp_file_path.exists():
self.fail("No trained engine generated")
msg = "Failed to create an engine from engine dict."
with self.fail_if_exception(msg):
SnipsNLUEngine.from_path(self.tmp_file_path)
def test_train(self):
# Given / When
train(BEVERAGE_DATASET_PATH, str(self.tmp_file_path), config_path=None)
# Then
if not self.tmp_file_path.exists():
self.fail("No trained engine generated")
msg = "Failed to create an engine from engine dict."
with self.fail_if_exception(msg):
with self.tmp_file_path.open(mode="r", encoding="utf8") as f:
trained_engine_dict = json.load(f)
SnipsNLUEngine.from_dict(trained_engine_dict)
def test_train(self):
# Given / When
train(self.beverage_dataset_path,
str(self.tmp_file_path),
config_path=None,
verbose=False)
# Then
if not self.tmp_file_path.exists():
self.fail("No trained engine generated")
msg = "Failed to create an engine from engine dict."
with self.fail_if_exception(msg):
SnipsNLUEngine.from_path(self.tmp_file_path)