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1 Examples
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View Complete Implementation : generator.py
Copyright Apache License 2.0
Author : snakeztc
Copyright Apache License 2.0
Author : snakeztc
def gen(self, domain, complexity, num_sess=1):
"""
Generate synthetic dialogs in the given domain.
:param domain: a domain specification dictionary
:param complexity: an implmenetaiton of Complexity
:param num_sess: how dialogs to generate
:return: a list of dialogs. Each dialog is a list of turns.
"""
dialogs = []
action_channel = ActionChannel(domain, complexity)
word_channel = WordChannel(domain, complexity)
# natural language generators
sys_nlg = SysNlg(domain, complexity)
usr_nlg = UserNlg(domain, complexity)
bar = progressbar.ProgressBar(max_value=num_sess)
for i in range(num_sess):
bar.update(i)
usr = User(domain, complexity)
sys = System(domain, complexity)
# begin conversation
noisy_usr_as = []
dialog = []
conf = 1.0
while True:
# make a decision
sys_r, sys_t, sys_as, sys_s = sys.step(noisy_usr_as, conf)
sys_utt, sys_str_as = sys_nlg.generate_sent(sys_as, domain=domain)
dialog.append(self.pack_msg("SYS", sys_utt, actions=sys_str_as, domain=domain.name, state=sys_s))
if sys_t:
break
usr_r, usr_t, usr_as = usr.step(sys_as)
# pasting through noise, nlg and noise!
noisy_usr_as, conf = action_channel.transmit2sys(usr_as)
usr_utt = usr_nlg.generate_sent(noisy_usr_as)
noisy_usr_utt = word_channel.transmit2sys(usr_utt)
dialog.append(self.pack_msg("USR", noisy_usr_utt, actions=noisy_usr_as, conf=conf, domain=domain.name))
dialogs.append(dialog)
return dialogs