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sgd / preprocess.py
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from zipfile import ZipFile, ZIP_DEFLATED
import json
import os
from pprint import pprint
from copy import deepcopy
from collections import Counter
from tqdm import tqdm
from shutil import rmtree
import re
digit2word = {
'0': 'zero', '1': 'one', '2': 'two', '3': 'three', '4': 'four', '5': 'five',
'6': 'six', '7': 'seven', '8': 'eight', '9': 'nine', '10': 'ten'
}
match = {
'0': 0,
'1': 0,
'>1': 0,
}
def pharse_in_sen(phrase, sen):
'''
match value in the sentence
:param phrase: str
:param sen: str
:return: start, end if matched, else None, None
'''
assert isinstance(phrase, str)
pw = '(^|[\s,\.:\?!-])(?P<v>{})([\s,\.:\?!-]|$)'
pn = '(^|[\s\?!-]|\D[,\.:])(?P<v>{})($|[\s\?!-]|[,\.:]\D|[,\.:]$)'
if phrase.isdigit():
pattern = pn
else:
pattern = pw
p = re.compile(pattern.format(re.escape(phrase)), re.I)
m = re.search(p, sen)
if m:
num = len(re.findall(p, sen))
if num > 1:
match['>1'] += 1
else:
match['1'] += 1
return m.span('v'), num
if phrase.isdigit() and phrase in digit2word:
phrase = digit2word[phrase]
p = re.compile(pw.format(re.escape(phrase)), re.I)
m = re.search(p, sen)
if m:
num = len(re.findall(p, sen))
if num > 1:
match['>1'] += 1
else:
match['1'] += 1
return m.span('v'), num
match['0'] += 1
return (None, None), 0
def sys_intent():
"""from original data README.md"""
return {
"inform": {"description": "Inform the value for a slot to the user."},
"request": {"description": "Request the value of a slot from the user."},
"confirm": {"description": "Confirm the value of a slot before making a transactional service call."},
"offer": {"description": "Offer a certain value for a slot to the user."},
"notify_success": {"description": "Inform the user that their request was successful."},
"notify_failure": {"description": "Inform the user that their request failed."},
"inform_count": {"description": "Inform the number of items found that satisfy the user's request."},
"offer_intent": {"description": "Offer a new intent to the user."},
"req_more": {"description": "Asking the user if they need anything else."},
"goodbye": {"description": "End the dialogue."},
}
def usr_intent():
"""from original data README.md"""
return {
"inform_intent": {"description": "Express the desire to perform a certain task to the system."},
"negate_intent": {"description": "Negate the intent which has been offered by the system."},
"affirm_intent": {"description": "Agree to the intent which has been offered by the system."},
"inform": {"description": "Inform the value of a slot to the system."},
"request": {"description": "Request the value of a slot from the system."},
"affirm": {"description": "Agree to the system's proposition. "},
"negate": {"description": "Deny the system's proposal."},
"select": {"description": "Select a result being offered by the system."},
"request_alts": {"description": "Ask for more results besides the ones offered by the system."},
"thank_you": {"description": "Thank the system."},
"goodbye": {"description": "End the dialogue."},
}
def get_intent():
"""merge sys & usr intent"""
return {
"inform": {"description": "Inform the value for a slot."},
"request": {"description": "Request the value of a slot."},
"confirm": {"description": "Confirm the value of a slot before making a transactional service call."},
"offer": {"description": "Offer a certain value for a slot to the user."},
"notify_success": {"description": "Inform the user that their request was successful."},
"notify_failure": {"description": "Inform the user that their request failed."},
"inform_count": {"description": "Inform the number of items found that satisfy the user's request."},
"offer_intent": {"description": "Offer a new intent to the user."},
"req_more": {"description": "Asking the user if they need anything else."},
"goodbye": {"description": "End the dialogue."},
"inform_intent": {"description": "Express the desire to perform a certain task to the system."},
"negate_intent": {"description": "Negate the intent which has been offered by the system."},
"affirm_intent": {"description": "Agree to the intent which has been offered by the system."},
"affirm": {"description": "Agree to the system's proposition. "},
"negate": {"description": "Deny the system's proposal."},
"select": {"description": "Select a result being offered by the system."},
"request_alts": {"description": "Ask for more results besides the ones offered by the system."},
"thank_you": {"description": "Thank the system."},
}
def preprocess():
original_data_dir = 'dstc8-schema-guided-dialogue-master'
new_data_dir = 'data'
if not os.path.exists(original_data_dir):
original_data_zip = 'dstc8-schema-guided-dialogue-master.zip'
if not os.path.exists(original_data_zip):
raise FileNotFoundError(f'cannot find original data {original_data_zip} in sgd/, should manually download dstc8-schema-guided-dialogue-master.zip from https://github.com/google-research-datasets/dstc8-schema-guided-dialogue')
else:
archive = ZipFile(original_data_zip)
archive.extractall()
os.makedirs(new_data_dir, exist_ok=True)
dialogues = []
ontology = {'domains': {},
'intents': get_intent(),
'state': {},
'dialogue_acts': {
"categorical": {},
"non-categorical": {},
"binary": {}
}}
splits = ['train', 'validation', 'test']
dataset_name = 'sgd'
for data_split in splits:
data_dir = os.path.join(original_data_dir, data_split if data_split != 'validation' else 'dev')
# schema => ontology
with open(os.path.join(data_dir, 'schema.json')) as f:
data = json.load(f)
for schema in data:
domain = schema['service_name']
ontology['domains'].setdefault(domain, {})
ontology['domains'][domain]['description'] = schema['description']
ontology['domains'][domain].setdefault('slots', {})
ontology['domains'][domain]['active_intents'] = schema['intents']
ontology['state'].setdefault(domain, {})
for slot in schema['slots']:
ontology['domains'][domain]['slots'][slot['name']] = {
"description": slot['description'],
"is_categorical": slot['is_categorical'],
"possible_values": slot['possible_values']
}
ontology['state'][domain][slot['name']] = ''
# add 'count' slot
ontology['domains'][domain]['slots']['count'] = {
"description": "the number of items found that satisfy the user's request.",
"is_categorical": False,
"possible_values": []
}
# dialog
cnt = 0
for root, dirs, files in os.walk(data_dir):
fs = sorted([x for x in files if 'dialogues' in x])
for f in tqdm(fs, desc='processing schema-guided-{}'.format(data_split)):
data = json.load(open(os.path.join(data_dir, f)))
for d in data:
dialogue = {
"dataset": dataset_name,
"data_split": data_split,
"dialogue_id": f'{dataset_name}-{data_split}-{cnt}',
"original_id": d['dialogue_id'],
"domains": d['services'],
"goal": { # no goal
'description': '',
'inform': {},
'request': {}
},
"turns": []
}
cnt += 1
prev_state = {}
for domain in dialogue['domains']:
prev_state.setdefault(domain, deepcopy(ontology['state'][domain]))
for utt_idx, t in enumerate(d['turns']):
speaker = t['speaker'].lower()
turn = {
'speaker': speaker,
'utterance': t['utterance'],
'utt_idx': utt_idx,
'dialogue_acts': {
'binary': [],
'categorical': [],
'non-categorical': [],
},
}
for frame in t['frames']:
domain = frame['service']
for action in frame['actions']:
intent = action['act'].lower() # lowercase intent
assert intent in ontology['intents'], [intent]
slot = action['slot']
value_list = action['values']
if action['act'] in ['REQ_MORE', 'AFFIRM', 'NEGATE', 'THANK_YOU', 'GOODBYE']:
# Slot and values are always empty
assert slot == "" and len(value_list) == 0
turn['dialogue_acts']['binary'].append({
"intent": intent,
"domain": '',
"slot": ''
})
elif action['act'] in ['NOTIFY_SUCCESS', 'NOTIFY_FAILURE', 'REQUEST_ALTS', 'AFFIRM_INTENT', 'NEGATE_INTENT']:
# Slot and values are always empty
assert slot == "" and len(value_list) == 0
turn['dialogue_acts']['binary'].append({
"intent": intent,
"domain": domain,
"slot": ''
})
elif action['act'] in ['OFFER_INTENT', 'INFORM_INTENT']:
# slot containing the intent being offered.
assert slot == 'intent' and len(value_list) == 1
turn['dialogue_acts']['binary'].append({
"intent": intent,
"domain": domain,
"slot": value_list[0]
})
elif action['act'] in ['REQUEST'] and len(value_list) == 0:
# always contains a slot, but values are optional.
assert slot in ontology['domains'][domain]['slots'], f'{domain}-{slot}'
turn['dialogue_acts']['binary'].append({
"intent": intent,
"domain": domain,
"slot": slot
})
elif action['act'] in ['SELECT'] and len(value_list) == 0:
# (slot=='' and len(value_list) == 0) or (slot!='' and len(value_list) > 0)
assert slot == '', f'{domain}-{slot}-{action}'
turn['dialogue_acts']['binary'].append({
"intent": intent,
"domain": domain,
"slot": slot
})
elif action['act'] in ['INFORM_COUNT']:
# always has "count" as the slot, and a single element in values for the number of results obtained by the system.
assert slot == 'count' and len(value_list) == 1
value = value_list[0]
turn['dialogue_acts']['non-categorical'].append({
"intent": intent,
"domain": domain,
"slot": slot,
"value": value,
})
# find char span
(start, end), num = pharse_in_sen(value, t['utterance'])
assert num > 0, f'{value}-{t["utterance"]}' # {1:20086, 2:341, 3:19}
assert value.lower() == t['utterance'][start:end].lower() \
or digit2word[value].lower() == t['utterance'][start:end].lower()
# first match is always the choice
turn['dialogue_acts']['non-categorical'][-1].update({
"value": t['utterance'][start:end], "start": start, "end": end
})
else:
# have slot & value
if ontology['domains'][domain]['slots'][slot]['is_categorical']:
possible_values = [value.lower() for value in ontology['domains'][domain]['slots'][slot]['possible_values']]
for value in value_list:
if value.lower() not in possible_values and value != 'dontcare':
ontology['domains'][domain]['slots'][slot]['possible_values'].append(value)
print(f'add value to ontology\t{domain}-{slot}-{value}', possible_values)
turn['dialogue_acts']['categorical'].append({
"intent": intent,
"domain": domain,
"slot": slot,
"value": value,
})
else:
# span info in frame['slots']
for value in value_list:
for slot_info in frame['slots']:
start = slot_info['start']
end = slot_info['exclusive_end']
if slot_info['slot'] == slot and t['utterance'][start:end].lower() == value.lower():
assert t['utterance'][start:end] == value, f'{action}-{slot_info}-{t["utterance"][start:end]}'
turn['dialogue_acts']['non-categorical'].append({
"intent": intent,
"domain": domain,
"slot": slot,
"value": value,
"start": start,
"end": end
})
break
else:
assert value == 'dontcare', f'{action}-{slot_info}'
if speaker == 'user':
state = deepcopy(prev_state)
active_intent = {}
requested_slots = {}
for frame in t['frames']:
domain = frame['service']
active_intent[domain] = frame['state']['active_intent']
requested_slots[domain] = frame['state']['requested_slots']
for slot in state[domain]:
if slot in frame['state']['slot_values']:
value_list = frame['state']['slot_values'][slot]
state[domain][slot] = value_list[0]
for value in value_list[1:]:
state[domain][slot] += '|' + value
else:
state[domain][slot] = ''
prev_state = state
turn['state'] = state
turn['active_intent'] = active_intent
turn['requested_slots'] = requested_slots
else:
# service_call and service_results
turn['service_call'] = {}
turn['db_results'] = {}
for frame in t['frames']:
if 'service_call' not in frame:
continue
domain = frame['service']
turn['service_call'][domain] = frame['service_call']
turn['db_results'][domain] = frame['service_results']
# add to dialogue_acts dictionary in the ontology
for da_type in turn['dialogue_acts']:
das = turn['dialogue_acts'][da_type]
for da in das:
ontology["dialogue_acts"][da_type].setdefault((da['intent'], da['domain'], da['slot']), {})
ontology["dialogue_acts"][da_type][(da['intent'], da['domain'], da['slot'])][speaker] = True
dialogue['turns'].append(turn)
dialogues.append(dialogue)
for da_type in ontology['dialogue_acts']:
ontology["dialogue_acts"][da_type] = sorted([str({'user': speakers.get('user', False), 'system': speakers.get('system', False), 'intent':da[0],'domain':da[1], 'slot':da[2]}) for da, speakers in ontology["dialogue_acts"][da_type].items()])
json.dump(dialogues[:10], open(f'dummy_data.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False)
json.dump(ontology, open(f'{new_data_dir}/ontology.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False)
json.dump(dialogues, open(f'{new_data_dir}/dialogues.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False)
with ZipFile('data.zip', 'w', ZIP_DEFLATED) as zf:
for filename in os.listdir(new_data_dir):
zf.write(f'{new_data_dir}/{filename}')
rmtree(original_data_dir)
rmtree(new_data_dir)
return dialogues, ontology
if __name__ == '__main__':
preprocess()