From cb7bb5b004fe1c733671a8db00585f9958f2c2d7 Mon Sep 17 00:00:00 2001
From: zhuqi <zqwerty@users.noreply.github.com>
Date: Sun, 27 Sep 2020 16:43:26 +0800
Subject: [PATCH] Maintenance (#132)
* add test set example for dstc9 (multiwoz_zh, crosswoz_en)
* update new_goal_model.pkl
* update crosswoz auto_sys_template_nlg
* add postcode as special case for NLU tokenization
* fix lower case for int value in nlg.py
* fix empty user utterance problem in multiwoz simulator, issue #130
* remove debug output
---
.../rule/multiwoz/policy_agenda_multiwoz.py | 213 ++++++++++--------
1 file changed, 123 insertions(+), 90 deletions(-)
diff --git a/convlab2/policy/rule/multiwoz/policy_agenda_multiwoz.py b/convlab2/policy/rule/multiwoz/policy_agenda_multiwoz.py
index 3e717ff..a13e5e8 100755
--- a/convlab2/policy/rule/multiwoz/policy_agenda_multiwoz.py
+++ b/convlab2/policy/rule/multiwoz/policy_agenda_multiwoz.py
@@ -106,16 +106,20 @@ class UserPolicyAgendaMultiWoz(Policy):
self.agenda.close_session()
else:
sys_action = self._transform_sysact_in(sys_action)
+ # print('sys action before update agenda', sys_action)
self.agenda.update(sys_action, self.goal)
if self.goal.task_complete():
self.agenda.close_session()
- # A -> A' + user_action
- # action = self.agenda.get_action(random.randint(2, self.max_initiative))
- action = self.agenda.get_action(self.max_initiative)
+ action = {}
+ while len(action) == 0:
+ # A -> A' + user_action
+ # action = self.agenda.get_action(random.randint(2, self.max_initiative))
+ action = self.agenda.get_action(self.max_initiative)
- # transform to DA
- action = self._transform_usract_out(action)
+ # transform to DA
+ action = self._transform_usract_out(action)
+ # print(action)
tuples = []
for domain_intent, svs in action.items():
@@ -169,6 +173,8 @@ class UserPolicyAgendaMultiWoz(Policy):
new_action[new_act].append(['NotBook', 'none'])
elif slot is not None:
new_action[new_act].append([slot, pairs[1]])
+ if len(new_action[new_act]) == 0:
+ new_action.pop(new_act)
# new_action[new_act] = [[REF_USR_DA_M[dom.capitalize()].get(pairs[0], pairs[0]), pairs[1]] for pairs in action[act]]
else:
new_action[act] = action[act]
@@ -848,7 +854,6 @@ class Agenda(object):
diaacts = []
slots = []
values = []
-
p_diaact, p_slot = self.__check_next_diaact_slot()
if p_diaact.split('-')[1] == 'inform' and p_slot in BOOK_SLOT:
for _ in range(10 if self.__cur_push_num == 0 else self.__cur_push_num):
@@ -914,23 +919,23 @@ if __name__ == '__main__':
from convlab2.dst.rule.multiwoz.dst import RuleDST
from convlab2.nlu.jointBERT.multiwoz.nlu import BERTNLU
- seed = 50
+ seed = 41
np.random.seed(seed)
random.seed(seed)
torch.manual_seed(seed)
+ #
+ # sys_nlu = BERTNLU()
+ # sys_dst = RuleDST()
+ # sys_policy = RulePolicy()
+ # sys_nlg = TemplateNLG(is_user=False)
+ # sys_agent = PipelineAgent(sys_nlu, sys_dst, sys_policy, sys_nlg, name='sys')
- sys_nlu = BERTNLU()
- sys_dst = RuleDST()
- sys_policy = RulePolicy()
- sys_nlg = TemplateNLG(is_user=False)
- sys_agent = PipelineAgent(sys_nlu, sys_dst, sys_policy, sys_nlg, name='sys')
-
- user_nlu = BERTNLU(mode='sys', config_file='multiwoz_sys_context.json',
- model_file='https://convlab.blob.core.windows.net/convlab-2/bert_multiwoz_sys_context.zip')
- user_dst = None
- user_policy = RulePolicy(character='usr')
- user_nlg = TemplateNLG(is_user=True)
- user_agent = PipelineAgent(user_nlu, user_dst, user_policy, user_nlg, name='user')
+ # user_nlu = BERTNLU(mode='sys', config_file='multiwoz_sys_context.json',
+ # model_file='https://convlab.blob.core.windows.net/convlab-2/bert_multiwoz_sys_context.zip')
+ # user_dst = None
+ # user_policy = RulePolicy(character='usr')
+ # user_nlg = TemplateNLG(is_user=True)
+ # user_agent = PipelineAgent(user_nlu, user_dst, user_policy, user_nlg, name='user')
# evaluator = MultiWozEvaluator()
# sess = BiSession(sys_agent=sys_agent, user_agent=user_agent, kb_query=None, evaluator=evaluator)
@@ -938,14 +943,14 @@ if __name__ == '__main__':
- # user_policy = UserPolicyAgendaMultiWoz()
+ user_policy = UserPolicyAgendaMultiWoz()
#
- # sys_policy = RuleBasedMultiwozBot()
+ sys_policy = RulePolicy(character='sys')
#
- # user_nlg = TemplateNLG(is_user=True, mode='manual')
- # sys_nlg = TemplateNLG(is_user=False, mode='manual')
+ user_nlg = TemplateNLG(is_user=True, mode='manual')
+ sys_nlg = TemplateNLG(is_user=False, mode='manual')
#
- # dst = RuleDST()
+ dst = RuleDST()
#
# user_nlu = BERTNLU(mode='sys', config_file='multiwoz_sys_context.json',
# model_file='https://convlab.blob.core.windows.net/convlab-2/bert_multiwoz_sys_context.zip')
@@ -956,12 +961,24 @@ if __name__ == '__main__':
# if 'restaurant' in goal['domain_ordering'] and 'hotel' in goal['domain_ordering']:
# break
# # pprint(goal)
- user_goal = {'domain_ordering': ('restaurant', 'hotel', 'taxi'),
- 'hotel': {'book': {'day': 'sunday', 'people': '6', 'stay': '4'},
- 'info': {'internet': 'no',
- 'parking': 'no',
- 'pricerange': 'moderate',
- 'area': 'centre'}},
+ user_goal = {'domain_ordering': ('hotel', 'attraction'),
+ 'train': {
+ 'info': {'arriveBy': '16:00',
+ 'day': 'monday',
+ 'departure': 'cambridge',
+ 'destination': 'stansted airport'},
+ 'book': {'people': 2}, 'booked': '?'
+ },
+ 'attraction': {
+ 'info': {'type': 'museum'},
+ 'reqt': ['phone']
+ },
+ 'hotel': {
+ 'info': {'internet': 'yes',
+ 'parking': 'yes',
+ 'stars': '4',
+ 'type': 'hotel'},
+ 'reqt': ['postcode']},
'restaurant': {'info': {'area': 'centre',
'food': 'portuguese',
'pricerange': 'cheap'},
@@ -986,7 +1003,7 @@ if __name__ == '__main__':
user_policy.init_session(ini_goal=goal)
print('init goal:')
# pprint(user_policy.get_goal())
- pprint(user_agent.policy.get_goal())
+ # pprint(user_agent.policy.get_goal())
# pprint(sess.evaluator.goal)
# print('-' * 50)
# for i in range(20):
@@ -1005,60 +1022,66 @@ if __name__ == '__main__':
# print('=' * 100)
history = []
- user_utt = user_agent.response('')
- print(user_utt)
- user_utt = 'I need a restaurant . It just needs to be expensive . I am also in the market for a new restaurant . Is there something in the centre of town ? Do you have portuguese food ?'
- # history.append(['user', user_utt])
- sys_agent.dst.state['belief_state']['restaurant']['semi']['food'] = 'portuguese'
- sys_utt = sys_agent.response(user_utt)
- pprint(sys_agent.dst.state)
- print(sys_utt)
- sys_utt = "I have n't found any in the centre. I am unable to find any portuguese restaurants in town ."
- # history.append(['user', user_utt])
-
- user_utt = user_agent.response(sys_utt)
- print(user_utt)
- user_utt = "It just needs to be cheap ."
- sys_utt = sys_agent.response(user_utt)
- print(sys_utt)
- sys_utt = "It is in the centre area . They serve portuguese . Would you like to try nandos city centre ? They are in the cheap price range . I will book it for you and get a reference number ?"
-
- user_utt = user_agent.response(sys_utt)
- print(user_utt)
- sys_utt = sys_agent.response(user_utt)
- print(sys_utt)
-
- user_utt = user_agent.response(sys_utt)
- print(user_utt)
- sys_utt = sys_agent.response(user_utt)
- print(sys_utt)
-
- user_utt = user_agent.response(sys_utt)
- print(user_utt)
- sys_utt = sys_agent.response(user_utt)
- print(sys_utt)
-
+ # user_utt = user_agent.response('')
+ # print(user_utt)
+ # user_utt = 'I need a restaurant . It just needs to be expensive . I am also in the market for a new restaurant . Is there something in the centre of town ? Do you have portuguese food ?'
+ # # history.append(['user', user_utt])
+ # sys_agent.dst.state['belief_state']['restaurant']['semi']['food'] = 'portuguese'
+ # sys_utt = sys_agent.response(user_utt)
+ # pprint(sys_agent.dst.state)
+ # print(sys_utt)
+ # sys_utt = "I have n't found any in the centre. I am unable to find any portuguese restaurants in town ."
+ # # history.append(['user', user_utt])
#
- # print(user_policy.agenda)
- # user_act = user_policy.predict([])
- # print(user_act)
- # user_utt = user_nlg.generate(user_act)
+ # user_utt = user_agent.response(sys_utt)
# print(user_utt)
- # state = dst.state
- # state['user_action'] = user_act
- # dst.update(user_act)
- # # pprint(state)
- # sys_act = sys_policy.predict(state)
- # sys_utt = sys_nlg.generate(sys_act)
- # # sys_act.append(["Request", "Restaurant", "Price", "?"])
- # # sys_act = [['Request', 'Hotel', 'Area', '?'], ['Request', 'Hotel', 'Stars', '?']]
- # print(sys_act)
+ # user_utt = "It just needs to be cheap ."
+ # sys_utt = sys_agent.response(user_utt)
# print(sys_utt)
+ # sys_utt = "It is in the centre area . They serve portuguese . Would you like to try nandos city centre ? They are in the cheap price range . I will book it for you and get a reference number ?"
#
- # user_act = user_policy.predict(sys_act)
- # print(user_act)
- # user_utt = user_nlg.generate(user_act)
+ # user_utt = user_agent.response(sys_utt)
+ # print(user_utt)
+ # sys_utt = sys_agent.response(user_utt)
+ # print(sys_utt)
+ #
+ # user_utt = user_agent.response(sys_utt)
+ # print(user_utt)
+ # sys_utt = sys_agent.response(user_utt)
+ # print(sys_utt)
+ #
+ # user_utt = user_agent.response(sys_utt)
# print(user_utt)
+ # sys_utt = sys_agent.response(user_utt)
+ # print(sys_utt)
+
+ #
+ print(user_policy.agenda)
+ user_act = user_policy.predict([])
+ print(user_act)
+ user_utt = user_nlg.generate(user_act)
+ print(user_utt)
+ history.append(['user', user_utt])
+ state = dst.state
+ state['user_action'] = user_act
+ dst.update(user_act)
+ # pprint(state)
+ sys_act = sys_policy.predict(state)
+ sys_utt = sys_nlg.generate(sys_act)
+ # sys_act.append(["Request", "Restaurant", "Price", "?"])
+ # sys_act = [['Request', 'Hotel', 'Area', '?'], ['Request', 'Hotel', 'Stars', '?']]
+ sys_act = [['Inform', 'Hotel', 'Post', 'pe296fl']]
+ print(sys_act)
+ history.append(['sys', user_utt])
+
+ # sys_utt = sys_agent.response(user_utt)
+ # print(sys_utt)
+ #
+ user_act = user_policy.predict(sys_act)
+ print(user_act)
+ user_utt = user_nlg.generate(user_act)
+ print(user_utt)
+ history.append(['user', user_utt])
# state = dst.state
# state['user_action'] = user_act
# dst.update(user_act)
@@ -1066,24 +1089,34 @@ if __name__ == '__main__':
# sys_act = sys_policy.predict(state)
# # sys_act = [['Inform', 'Hotel', 'Choice', '3']]
# print(sys_act)
+ sys_act = [
+ ['Inform', 'Hotel', 'Post', 'pe296fl']
+ ]
+ print(sys_act)
+ # sys_utt = sys_agent.response(user_utt)
+ # print(sys_utt)
+ # sys_utt = 'The arrive time is 15:08 . The train will be departing from cambridge . The booking is for arriving in stansted airport . TR6936 will be your perfect fit . How about 14:40 will that work for you ?'
+ # history.append(['sys', user_utt])
#
#
- # user_act = user_policy.predict(sys_act)
- # print(user_act)
- # user_utt = user_nlg.generate(user_act)
- # print(user_utt)
+ # sys_act = user_nlu.predict(sys_utt, history)
+ # print(sys_act)
+ user_act = user_policy.predict(sys_act)
+ print(user_act)
+ user_utt = user_nlg.generate(user_act)
+ print(user_utt)
# state = dst.state
# state['user_action'] = user_act
# dst.update(user_act)
# # pprint(state)
# sys_act = sys_policy.predict(state)
- # # sys_act = [["Book", "Booking", "Ref", "7GAWK763"]]
- # print(sys_act)
+ sys_act = [['Request', 'Hotel', 'Price', '?'], ['Request', 'Attraction', 'Price', '?']]
+ print(sys_act)
# #
- # user_act = user_policy.predict(sys_act)
- # print(user_act)
- # user_utt = user_nlg.generate(user_act)
- # print(user_utt)
+ user_act = user_policy.predict(sys_act)
+ print(user_act)
+ user_utt = user_nlg.generate(user_act)
+ print(user_utt)
# state = dst.state
# state['user_action'] = user_act
# dst.update(user_act)
--
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