def test_memorise_with_nlu(self, trained_policy, default_domain):
filename = "data/test_dialogues/nlu_dialogue.json"
dialogue = read_dialogue_file(filename)
tracker = DialogueStateTracker(dialogue.name, default_domain.slots)
tracker.recreate_from_dialogue(dialogue)
states = trained_policy.featurizer.prediction_states([tracker],
default_domain)[0]
recalled = trained_policy.recall(states, tracker, default_domain)
assert recalled is not None
def test_memorise_with_nlu(self, trained_policy, default_domain):
filename = "data/test_dialogues/nlu_dialogue.json"
dialogue = read_dialogue_file(filename)
tracker = DialogueStateTracker(dialogue.name, default_domain.slots)
tracker.recreate_from_dialogue(dialogue)
states = trained_policy.featurizer.prediction_states([tracker],
default_domain)[0]
recalled = trained_policy.recall(states, tracker, default_domain)
assert recalled is not None
def test_tracker_duplicate():
filename = "data/test_dialogues/inform_no_change.json"
dialogue = read_dialogue_file(filename)
tracker = DialogueStateTracker(dialogue.name, domain.slots)
tracker.recreate_from_dialogue(dialogue)
num_actions = len([event
for event in dialogue.events
if isinstance(event, ActionExecuted)])
# There is always one duplicated tracker more than we have actions,
# as the tracker also gets duplicated for the
# action that would be next (but isn't part of the operations)
assert len(list(tracker.generate_all_prior_trackers())) == num_actions + 1
def test_tracker_duplicate():
filename = "data/test_dialogues/inform_no_change.json"
dialogue = read_dialogue_file(filename)
tracker = DialogueStateTracker(dialogue.name, domain.slots)
tracker.recreate_from_dialogue(dialogue)
num_actions = len([event
for event in dialogue.events
if isinstance(event, ActionExecuted)])
# There is always one duplicated tracker more than we have actions,
# as the tracker also gets duplicated for the
# action that would be next (but isn't part of the operations)
assert len(list(tracker.generate_all_prior_trackers())) == num_actions + 1
