def prepare_data(self, type=None):
# get dialogs from file
if type == 'Train':
dialogs, dialog_indices = util.read_dialogs(
with_indices=True,
file_name=
'/root/jude/data/dialog-bAbI-tasks/dialog-babi-task6-dstc2-trn.txt',
babi_num=6)
elif type == 'Test':
dialogs, dialog_indices = util.read_dialogs(
with_indices=True,
file_name=
'/root/jude/data/dialog-bAbI-tasks/dialog-babi-task6-dstc2-tst.txt',
babi_num=6)
# get utterances
utterances = util.get_utterances(dialogs)
# get responses
responses = util.get_responses(dialogs)
responses = [self.get_template_id(response) for response in responses]
trainset = []
for u, r in zip(utterances, responses):
trainset.append((u, r))
return trainset, dialog_indices
def get_action_templates(self):
ut_responses = util.get_responses()
ent = []
for response in ut_responses:
ent.append(self.et.extract_entities(response, update=False))
responses = list(set(ent))
#responses = list(set([ self.et.extract_entities(response, update=False)
# for response in util.get_responses() ]))
def extract_(response):
template = []
for word in response.split(' '):
if 'resto_' in word:
if 'phone' in word:
template.append('<info_phone>')
elif 'address' in word:
template.append('<info_address>')
else:
template.append('<restaurant>')
else:
template.append(word)
return ' '.join(template)
# extract restaurant entities
extracted_responses = sorted(
set([extract_(response) for response in responses]))
return extracted_responses
def get_action_templates(self):
no_set_responses = []
for i, response in enumerate(util.get_responses()):
res = self.filter_response(response)
no_set_responses.append(res)
responses = list(set(no_set_responses))
responses.remove('<UNK>')
return sorted(responses)
def prepare_data(self):
# get dialogs from file
dialogs, dialog_indices = util.read_dialogs(with_indices=True)
# get utterances
utterances = util.get_utterances(dialogs)
# get responses
responses_id = util.get_responses()
trainset = []
for u, r in zip(utterances, responses_id):
trainset.append((u, int(r)-1))
return trainset, dialog_indices # [(utterance_1, action_template_id_1),..] [{'start':0, 'end':20},...]
def prepare_data(self):
# get dialogs from file
dialogs, dialog_indices = util.read_dialogs(with_indices=True)
# get utterances
utterances = util.get_utterances(dialogs)
# get responses
responses = util.get_responses(dialogs)
responses = [self.get_template_id(response) for response in responses]
trainset = []
for u, r in zip(utterances, responses):
trainset.append((u, r))
return trainset, dialog_indices
def get_action_templates(self):
responses = list(set([ self.et.extract_entities(response, update=False)
for response in util.get_responses()]))
def extract_(response):
template = []
for word in response.split(' '):
if 'resto_' in word:
if 'phone' in word:
template.append('<info_phone>')
elif 'address' in word:
template.append('<info_address>')
else:
template.append('<restaurant>')
else:
template.append(word)
return ' '.join(template)
for each in responses:
each_response = extract_(each)
if each_response == '<info_phone> 입니다':
print(each)
# extract restaurant entities
return sorted(set([ extract_(response) for response in responses ]))
