| from zipfile import ZipFile, ZIP_DEFLATED |
| from shutil import rmtree |
| import json |
| import os |
| from tqdm import tqdm |
| from collections import Counter |
| from pprint import pprint |
| from nltk.tokenize import sent_tokenize, word_tokenize |
| from nltk.tokenize.treebank import TreebankWordDetokenizer |
| import re |
|
|
| topic_map = { |
| 1: "Ordinary Life", |
| 2: "School Life", |
| 3: "Culture & Education", |
| 4: "Attitude & Emotion", |
| 5: "Relationship", |
| 6: "Tourism", |
| 7: "Health", |
| 8: "Work", |
| 9: "Politics", |
| 10: "Finance" |
| } |
|
|
| act_map = { |
| 1: "inform", |
| 2: "question", |
| 3: "directive", |
| 4: "commissive" |
| } |
|
|
| emotion_map = { |
| 0: "no emotion", |
| 1: "anger", |
| 2: "disgust", |
| 3: "fear", |
| 4: "happiness", |
| 5: "sadness", |
| 6: "surprise" |
| } |
|
|
| def preprocess(): |
| original_data_dir = 'ijcnlp_dailydialog' |
| new_data_dir = 'data' |
|
|
| if not os.path.exists(original_data_dir): |
| original_data_zip = 'ijcnlp_dailydialog.zip' |
| if not os.path.exists(original_data_zip): |
| raise FileNotFoundError(f'cannot find original data {original_data_zip} in dailydialog/, should manually download ijcnlp_dailydialog.zip from http://yanran.li/files/ijcnlp_dailydialog.zip') |
| else: |
| archive = ZipFile(original_data_zip) |
| archive.extractall() |
|
|
| os.makedirs(new_data_dir, exist_ok=True) |
|
|
| dataset = 'dailydialog' |
| splits = ['train', 'validation', 'test'] |
| dialogues_by_split = {split:[] for split in splits} |
| dial2topics = {} |
| with open(os.path.join(original_data_dir, 'dialogues_text.txt')) as dialog_file, \ |
| open(os.path.join(original_data_dir, 'dialogues_topic.txt')) as topic_file: |
| for dialog, topic in zip(dialog_file, topic_file): |
| topic = int(topic.strip()) |
| dialog = dialog.replace(' __eou__ ', ' ') |
| if dialog in dial2topics: |
| dial2topics[dialog].append(topic) |
| else: |
| dial2topics[dialog] = [topic] |
|
|
| global topic_map, act_map, emotion_map |
|
|
| ontology = {'domains': {x:{'description': '', 'slots': {}} for x in topic_map.values()}, |
| 'intents': {x:{'description': ''} for x in act_map.values()}, |
| 'state': {}, |
| 'dialogue_acts': { |
| "categorical": [], |
| "non-categorical": [], |
| "binary": {} |
| }} |
|
|
| detokenizer = TreebankWordDetokenizer() |
|
|
| for data_split in splits: |
| archive = ZipFile(os.path.join(original_data_dir, f'{data_split}.zip')) |
| with archive.open(f'{data_split}/dialogues_{data_split}.txt') as dialog_file, \ |
| archive.open(f'{data_split}/dialogues_act_{data_split}.txt') as act_file, \ |
| archive.open(f'{data_split}/dialogues_emotion_{data_split}.txt') as emotion_file: |
| for dialog_line, act_line, emotion_line in tqdm(zip(dialog_file, act_file, emotion_file)): |
| if not dialog_line.strip(): |
| break |
| utts = dialog_line.decode().split("__eou__")[:-1] |
| acts = act_line.decode().split(" ")[:-1] |
| emotions = emotion_line.decode().split(" ")[:-1] |
| assert (len(utts) == len(acts) == len(emotions)), "Different turns btw dialogue & emotion & action" |
|
|
| topics = dial2topics[dialog_line.decode().replace(' __eou__ ', ' ')] |
| topic = Counter(topics).most_common(1)[0][0] |
| domain = topic_map[topic] |
| |
| dialogue_id = f'{dataset}-{data_split}-{len(dialogues_by_split[data_split])}' |
| dialogue = { |
| 'dataset': dataset, |
| 'data_split': data_split, |
| 'dialogue_id': dialogue_id, |
| 'original_id': f'{data_split}-{len(dialogues_by_split[data_split])}', |
| 'domains': [domain], |
| 'turns': [] |
| } |
|
|
| for utt, act, emotion in zip(utts, acts, emotions): |
| speaker = 'user' if len(dialogue['turns']) % 2 == 0 else 'system' |
| intent = act_map[int(act)] |
| emotion = emotion_map[int(emotion)] |
| |
| utt = ' '.join([detokenizer.detokenize(word_tokenize(s)) for s in sent_tokenize(utt)]) |
| |
| utt = utt.replace(' ’ ', "'") |
| |
| utt = re.sub('\.(?!com)(\w)', lambda x: '. '+x.group(1), utt) |
|
|
| dialogue['turns'].append({ |
| 'speaker': speaker, |
| 'utterance': utt.strip(), |
| 'utt_idx': len(dialogue['turns']), |
| 'dialogue_acts': { |
| 'binary': [{ |
| 'intent': intent, |
| 'domain': '', |
| 'slot': '' |
| }], |
| 'categorical': [], |
| 'non-categorical': [], |
| }, |
| 'emotion': emotion, |
| }) |
|
|
| ontology["dialogue_acts"]['binary'].setdefault((intent, '', ''), {}) |
| ontology["dialogue_acts"]['binary'][(intent, '', '')][speaker] = True |
|
|
| dialogues_by_split[data_split].append(dialogue) |
|
|
| ontology["dialogue_acts"]['binary'] = 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"]['binary'].items()]) |
| dialogues = dialogues_by_split['train']+dialogues_by_split['validation']+dialogues_by_split['test'] |
| 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() |
|
|
