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create_data.py
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create_data.py
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# -*- coding: utf-8 -*-
import copy
import json
import os
import re
import shutil
import urllib.request
from collections import OrderedDict
from io import BytesIO
from zipfile import ZipFile
import difflib
import numpy as np
import argparse
from shutil import copyfile
np.set_printoptions(precision=3)
np.random.seed(2)
'''
Most of the codes are from https://github.com/budzianowski/multiwoz
'''
# GLOBAL VARIABLES
DICT_SIZE = 400
MAX_LENGTH = 50
IGNORE_KEYS_IN_GOAL = ['eod', 'topic', 'messageLen', 'message']
fin = open('utils/mapping.pair','r')
replacements = []
for line in fin.readlines():
tok_from, tok_to = line.replace('\n', '').split('\t')
replacements.append((' ' + tok_from + ' ', ' ' + tok_to + ' '))
def is_ascii(s):
return all(ord(c) < 128 for c in s)
def insertSpace(token, text):
sidx = 0
while True:
sidx = text.find(token, sidx)
if sidx == -1:
break
if sidx + 1 < len(text) and re.match('[0-9]', text[sidx - 1]) and \
re.match('[0-9]', text[sidx + 1]):
sidx += 1
continue
if text[sidx - 1] != ' ':
text = text[:sidx] + ' ' + text[sidx:]
sidx += 1
if sidx + len(token) < len(text) and text[sidx + len(token)] != ' ':
text = text[:sidx + 1] + ' ' + text[sidx + 1:]
sidx += 1
return text
def normalize(text, clean_value=True):
# lower case every word
text = text.lower()
# replace white spaces in front and end
text = re.sub(r'^\s*|\s*$', '', text)
# hotel domain pfb30
text = re.sub(r"b&b", "bed and breakfast", text)
text = re.sub(r"b and b", "bed and breakfast", text)
if clean_value:
# normalize phone number
ms = re.findall('\(?(\d{3})\)?[-.\s]?(\d{3})[-.\s]?(\d{4,5})', text)
if ms:
sidx = 0
for m in ms:
sidx = text.find(m[0], sidx)
if text[sidx - 1] == '(':
sidx -= 1
eidx = text.find(m[-1], sidx) + len(m[-1])
text = text.replace(text[sidx:eidx], ''.join(m))
# normalize postcode
ms = re.findall('([a-z]{1}[\. ]?[a-z]{1}[\. ]?\d{1,2}[, ]+\d{1}[\. ]?[a-z]{1}[\. ]?[a-z]{1}|[a-z]{2}\d{2}[a-z]{2})',
text)
if ms:
sidx = 0
for m in ms:
sidx = text.find(m, sidx)
eidx = sidx + len(m)
text = text[:sidx] + re.sub('[,\. ]', '', m) + text[eidx:]
# weird unicode bug
text = re.sub(u"(\u2018|\u2019)", "'", text)
if clean_value:
# replace time and and price
text = re.sub(timepat, ' [value_time] ', text)
text = re.sub(pricepat, ' [value_price] ', text)
#text = re.sub(pricepat2, '[value_price]', text)
# replace st.
text = text.replace(';', ',')
text = re.sub('$\/', '', text)
text = text.replace('/', ' and ')
# replace other special characters
text = text.replace('-', ' ')
text = re.sub('[\"\<>@\(\)]', '', text) # remove
# insert white space before and after tokens:
for token in ['?', '.', ',', '!']:
text = insertSpace(token, text)
# insert white space for 's
text = insertSpace('\'s', text)
# replace it's, does't, you'd ... etc
text = re.sub('^\'', '', text)
text = re.sub('\'$', '', text)
text = re.sub('\'\s', ' ', text)
text = re.sub('\s\'', ' ', text)
for fromx, tox in replacements:
text = ' ' + text + ' '
text = text.replace(fromx, tox)[1:-1]
# remove multiple spaces
text = re.sub(' +', ' ', text)
# concatenate numbers
tmp = text
tokens = text.split()
i = 1
while i < len(tokens):
if re.match(u'^\d+$', tokens[i]) and \
re.match(u'\d+$', tokens[i - 1]):
tokens[i - 1] += tokens[i]
del tokens[i]
else:
i += 1
text = ' '.join(tokens)
return text
def fixDelex(filename, data, data2, idx, idx_acts):
"""Given system dialogue acts fix automatic delexicalization."""
try:
turn = data2[filename.strip('.json')][str(idx_acts)]
except:
return data
if not isinstance(turn, str):# and not isinstance(turn, unicode):
for k, act in turn.items():
if 'Attraction' in k:
if 'restaurant_' in data['log'][idx]['text']:
data['log'][idx]['text'] = data['log'][idx]['text'].replace("restaurant", "attraction")
if 'hotel_' in data['log'][idx]['text']:
data['log'][idx]['text'] = data['log'][idx]['text'].replace("hotel", "attraction")
if 'Hotel' in k:
if 'attraction_' in data['log'][idx]['text']:
data['log'][idx]['text'] = data['log'][idx]['text'].replace("attraction", "hotel")
if 'restaurant_' in data['log'][idx]['text']:
data['log'][idx]['text'] = data['log'][idx]['text'].replace("restaurant", "hotel")
if 'Restaurant' in k:
if 'attraction_' in data['log'][idx]['text']:
data['log'][idx]['text'] = data['log'][idx]['text'].replace("attraction", "restaurant")
if 'hotel_' in data['log'][idx]['text']:
data['log'][idx]['text'] = data['log'][idx]['text'].replace("hotel", "restaurant")
return data
def getDialogueAct(filename, data, data2, idx, idx_acts):
"""Given system dialogue acts fix automatic delexicalization."""
acts = []
try:
turn = data2[filename.strip('.json')][str(idx_acts)]
except:
return acts
if not isinstance(turn, str): # and not isinstance(turn, unicode):
for k in turn.keys():
# temp = [k.split('-')[0].lower(), k.split('-')[1].lower()]
# for a in turn[k]:
# acts.append(temp + [a[0].lower()])
if k.split('-')[1].lower() == 'request':
for a in turn[k]:
acts.append(a[0].lower())
elif k.split('-')[1].lower() == 'inform':
for a in turn[k]:
acts.append([a[0].lower(), normalize(a[1].lower(), False)])
return acts
def get_summary_bstate(bstate, get_domain=False):
"""Based on the mturk annotations we form multi-domain belief state"""
domains = [u'taxi',u'restaurant', u'hospital', u'hotel',u'attraction', u'train', u'police']
summary_bstate = []
summary_bvalue = []
active_domain = []
for domain in domains:
domain_active = False
booking = []
#print(domain,len(bstate[domain]['book'].keys()))
for slot in sorted(bstate[domain]['book'].keys()):
if slot == 'booked':
if len(bstate[domain]['book']['booked'])!=0:
booking.append(1)
# summary_bvalue.append("book {} {}:{}".format(domain, slot, "Yes"))
else:
booking.append(0)
else:
if bstate[domain]['book'][slot] != "":
booking.append(1)
summary_bvalue.append(["{}-book {}".format(domain, slot.strip().lower()), normalize(bstate[domain]['book'][slot].strip().lower(), False)]) #(["book", domain, slot, bstate[domain]['book'][slot]])
else:
booking.append(0)
if domain == 'train':
if 'people' not in bstate[domain]['book'].keys():
booking.append(0)
if 'ticket' not in bstate[domain]['book'].keys():
booking.append(0)
summary_bstate += booking
for slot in bstate[domain]['semi']:
slot_enc = [0, 0, 0] # not mentioned, dontcare, filled
if bstate[domain]['semi'][slot] == 'not mentioned':
slot_enc[0] = 1
elif bstate[domain]['semi'][slot] in ['dont care', 'dontcare', "don't care", "do not care"]:
slot_enc[1] = 1
summary_bvalue.append(["{}-{}".format(domain, slot.strip().lower()), "dontcare"]) #(["semi", domain, slot, "dontcare"])
elif bstate[domain]['semi'][slot]:
summary_bvalue.append(["{}-{}".format(domain, slot.strip().lower()), normalize(bstate[domain]['semi'][slot].strip().lower(), False)]) #(["semi", domain, slot, bstate[domain]['semi'][slot]])
if slot_enc != [0, 0, 0]:
domain_active = True
summary_bstate += slot_enc
# quasi domain-tracker
if domain_active:
summary_bstate += [1]
active_domain.append(domain)
else:
summary_bstate += [0]
#print(len(summary_bstate))
assert len(summary_bstate) == 94
if get_domain:
return active_domain
else:
return summary_bstate, summary_bvalue
def analyze_dialogue(dialogue, maxlen):
"""Cleaning procedure for all kinds of errors in text and annotation."""
d = dialogue
# do all the necessary postprocessing
if len(d['log']) % 2 != 0:
#print path
print('odd # of turns')
return None # odd number of turns, wrong dialogue
d_pp = {}
d_pp['goal'] = d['goal'] # for now we just copy the goal
usr_turns = []
sys_turns = []
# last_bvs = []
for i in range(len(d['log'])):
if len(d['log'][i]['text'].split()) > maxlen:
# print('too long')
return None # too long sentence, wrong dialogue
if i % 2 == 0: # usr turn
text = d['log'][i]['text']
if not is_ascii(text):
# print('not ascii')
return None
usr_turns.append(d['log'][i])
else: # sys turn
text = d['log'][i]['text']
if not is_ascii(text):
# print('not ascii')
return None
belief_summary, belief_value_summary = get_summary_bstate(d['log'][i]['metadata'])
d['log'][i]['belief_summary'] = str(belief_summary)
d['log'][i]['belief_value_summary'] = belief_value_summary
sys_turns.append(d['log'][i])
d_pp['usr_log'] = usr_turns
d_pp['sys_log'] = sys_turns
return d_pp
def get_dial(dialogue):
"""Extract a dialogue from the file"""
dial = []
d_orig = analyze_dialogue(dialogue, MAX_LENGTH) # max turn len is 50 words
if d_orig is None:
return None
usr = [t['text'] for t in d_orig['usr_log']]
sys = [t['text'] for t in d_orig['sys_log']]
sys_a = [t['dialogue_acts'] for t in d_orig['sys_log']]
bvs = [t['belief_value_summary'] for t in d_orig['sys_log']]
domain = [t['domain'] for t in d_orig['usr_log']]
for item in zip(usr, sys, sys_a, domain, bvs):
dial.append({'usr':item[0],'sys':item[1], 'sys_a':item[2], 'domain':item[3], 'bvs':item[4]})
return dial
def loadData(args):
data_url = os.path.join(args.main_dir, "data.json")
if args.mwz_ver == '2.1':
dataset_url = "https://www.repository.cam.ac.uk/bitstream/handle/1810/294507/MULTIWOZ2.1.zip?sequence=1&isAllowed=y"
else:
dataset_url = "https://www.repository.cam.ac.uk/bitstream/handle/1810/280608/MULTIWOZ2.zip?sequence=3&isAllowed=y"
if not os.path.exists(args.main_dir):
os.makedirs(args.main_dir)
if not os.path.exists(data_url):
print("Downloading and unzipping the MultiWOZ %s dataset" % args.mwz_ver)
resp = urllib.request.urlopen(dataset_url)
zip_ref = ZipFile(BytesIO(resp.read()))
zip_ref.extractall(args.main_dir)
zip_ref.close()
dir_name = 'MULTIWOZ2.1' if args.mwz_ver == '2.1' else 'MULTIWOZ2 2'
shutil.copy(os.path.join(args.main_dir, dir_name, 'data.json'), args.main_dir)
shutil.copy(os.path.join(args.main_dir, dir_name, 'ontology.json'), args.main_dir)
shutil.copy(os.path.join(args.main_dir, dir_name, 'valListFile.json'), args.main_dir)
shutil.copy(os.path.join(args.main_dir, dir_name, 'testListFile.json'), args.main_dir)
shutil.copy(os.path.join(args.main_dir, dir_name, 'dialogue_acts.json'), args.main_dir)
def getDomain(idx, log, domains, last_domain):
if idx == 1:
active_domains = get_summary_bstate(log[idx]["metadata"], True)
crnt_doms = active_domains[0] if len(active_domains)!=0 else domains[0]
return crnt_doms
else:
ds_diff = get_ds_diff(log[idx-2]["metadata"], log[idx]["metadata"])
if len(ds_diff.keys()) == 0: # no clues from dialog states
crnt_doms = last_domain
else:
crnt_doms = list(ds_diff.keys())
# print(crnt_doms)
return crnt_doms[0] # How about multiple domains in one sentence senario ?
def get_ds_diff(prev_d, crnt_d):
diff = {}
# Sometimes, metadata is an empty dictionary, bug?
if not prev_d or not crnt_d:
return diff
for ((k1, v1), (k2, v2)) in zip(prev_d.items(), crnt_d.items()):
assert k1 == k2
if v1 != v2: # updated
diff[k2] = v2
return diff
def createData(args):
# download the data
loadData(args)
# create dictionary of delexicalied values that then we will search against, order matters here!
# dic = delexicalize.prepareSlotValuesIndependent()
delex_data = {}
fin1 = open(os.path.join(args.main_dir, 'data.json'), 'r')
data = json.load(fin1)
fin2 = open(os.path.join(args.main_dir, 'dialogue_acts.json'), 'r')
data2 = json.load(fin2)
for didx, dialogue_name in enumerate(data):
dialogue = data[dialogue_name]
domains = []
for dom_k, dom_v in dialogue['goal'].items():
if dom_v and dom_k not in IGNORE_KEYS_IN_GOAL: # check whether contains some goal entities
domains.append(dom_k)
idx_acts = 1
last_domain, last_slot_fill = "", []
for idx, turn in enumerate(dialogue['log']):
# normalization, split and delexicalization of the sentence
origin_text = normalize(turn['text'], False)
# origin_text = delexicalize.markEntity(origin_text, dic)
dialogue['log'][idx]['text'] = origin_text
if idx % 2 == 1: # if it's a system turn
cur_domain = getDomain(idx, dialogue['log'], domains, last_domain)
last_domain = [cur_domain]
dialogue['log'][idx - 1]['domain'] = cur_domain
dialogue['log'][idx]['dialogue_acts'] = getDialogueAct(dialogue_name, dialogue, data2, idx, idx_acts)
idx_acts += 1
# FIXING delexicalization:
dialogue = fixDelex(dialogue_name, dialogue, data2, idx, idx_acts)
delex_data[dialogue_name] = dialogue
# if didx > 10:
# break
# with open('data/multi-woz/woz2like_data.json', 'w') as outfile:
# json.dump(delex_data, outfile)
return delex_data
def buildDelexDict(origin_sent, delex_sent):
dictionary = {}
s = difflib.SequenceMatcher(None, delex_sent.split(), origin_sent.split())
bs = s.get_matching_blocks()
for i, b in enumerate(bs):
if i < len(bs)-2:
a_start = b.a + b.size
b_start = b.b + b.size
b_end = bs[i+1].b
dictionary[a_start] = " ".join(origin_sent.split()[b_start:b_end])
return dictionary
def divideData(data,args):
"""Given test and validation sets, divide
the data for three different sets"""
os.makedirs(args.target_path,exist_ok=True)
copyfile(os.path.join(args.main_dir,'ontology.json'), os.path.join(args.target_path,'ontology.json'))
testListFile = []
fin = open(os.path.join(args.main_dir,'testListFile.json'), 'r')
for line in fin:
testListFile.append(line[:-1])
fin.close()
valListFile = []
fin = open(os.path.join(args.main_dir,'valListFile.json'), 'r')
for line in fin:
valListFile.append(line[:-1])
fin.close()
trainListFile = open(os.path.join(args.target_path,'trainListFile'), 'w')
test_dials = []
val_dials = []
train_dials = []
# dictionaries
word_freqs_usr = OrderedDict()
word_freqs_sys = OrderedDict()
count_train, count_val, count_test = 0, 0, 0
for dialogue_name in data:
# print dialogue_name
dial_item = data[dialogue_name]
domains = []
for dom_k, dom_v in dial_item['goal'].items():
if dom_v and dom_k not in IGNORE_KEYS_IN_GOAL: # check whether contains some goal entities
domains.append(dom_k)
dial = get_dial(data[dialogue_name])
if dial:
dialogue = {}
dialogue['dialogue_idx'] = dialogue_name
dialogue['domains'] = list(set(domains)) #list(set([d['domain'] for d in dial]))
last_bs = []
dialogue['dialogue'] = []
for turn_i, turn in enumerate(dial):
# usr, usr_o, sys, sys_o, sys_a, domain
turn_dialog = {}
turn_dialog['system_transcript'] = dial[turn_i-1]['sys'] if turn_i > 0 else ""
turn_dialog['turn_idx'] = turn_i
turn_dialog['belief_state'] = [{"slots": [s], "act": "inform"} for s in turn['bvs']]
turn_dialog['turn_label'] = [bs["slots"][0] for bs in turn_dialog['belief_state'] if bs not in last_bs]
turn_dialog['transcript'] = turn['usr']
turn_dialog['system_acts'] = dial[turn_i-1]['sys_a'] if turn_i > 0 else []
turn_dialog['domain'] = turn['domain']
last_bs = turn_dialog['belief_state']
dialogue['dialogue'].append(turn_dialog)
if dialogue_name in testListFile:
test_dials.append(dialogue)
count_test += 1
elif dialogue_name in valListFile:
val_dials.append(dialogue)
count_val += 1
else:
trainListFile.write(dialogue_name + '\n')
train_dials.append(dialogue)
count_train += 1
print("# of dialogues: Train {}, Val {}, Test {}".format(count_train, count_val, count_test))
# save all dialogues
with open(os.path.join(args.target_path, 'dev_dials.json'), 'w') as f:
json.dump(val_dials, f, indent=4)
with open(os.path.join(args.target_path, 'test_dials.json'), 'w') as f:
json.dump(test_dials, f, indent=4)
with open(os.path.join(args.target_path, 'train_dials.json'), 'w') as f:
json.dump(train_dials, f, indent=4)
# return word_freqs_usr, word_freqs_sys
def main(args):
print('Create WOZ-like dialogues. Get yourself a coffee, this might take a while.')
delex_data = createData(args)
print('Divide dialogues...')
divideData(delex_data,args)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--main_dir", type=str, default='data')
parser.add_argument("--mwz_ver", type=str, default='2.1')
parser.add_argument("--target_path", type=str, default='data/mwz2.1')
args = parser.parse_args()
main(args)