| import json | |
| import os | |
| import tarfile | |
| import zipfile | |
| import gzip | |
| import requests | |
| import gdown | |
| from glob import glob | |
| def wget(url, cache_dir: str = './cache', gdrive_filename: str = None): | |
| """ wget and uncompress data_iterator """ | |
| path = _wget(url, cache_dir, gdrive_filename=gdrive_filename) | |
| if path.endswith('.tar.gz') or path.endswith('.tgz') or path.endswith('.tar'): | |
| if path.endswith('.tar'): | |
| tar = tarfile.open(path) | |
| else: | |
| tar = tarfile.open(path, "r:gz") | |
| tar.extractall(cache_dir) | |
| tar.close() | |
| os.remove(path) | |
| elif path.endswith('.zip'): | |
| with zipfile.ZipFile(path, 'r') as zip_ref: | |
| zip_ref.extractall(cache_dir) | |
| os.remove(path) | |
| elif path.endswith('.gz'): | |
| with gzip.open(path, 'rb') as f: | |
| with open(path.replace('.gz', ''), 'wb') as f_write: | |
| f_write.write(f.read()) | |
| os.remove(path) | |
| def _wget(url: str, cache_dir, gdrive_filename: str = None): | |
| """ get data from web """ | |
| os.makedirs(cache_dir, exist_ok=True) | |
| if url.startswith('https://drive.google.com'): | |
| assert gdrive_filename is not None, 'please provide fileaname for gdrive download' | |
| return gdown.download(url, f'{cache_dir}/{gdrive_filename}', quiet=False) | |
| filename = os.path.basename(url) | |
| with open(f'{cache_dir}/{filename}', "wb") as f: | |
| r = requests.get(url) | |
| f.write(r.content) | |
| return f'{cache_dir}/{filename}' | |
| def get_data(n_sample: int = 10, v_rate: float = 0.2, n_sample_max: int = 10): | |
| assert n_sample <= n_sample_max | |
| cache_dir = 'cache' | |
| os.makedirs(cache_dir, exist_ok=True) | |
| path_answer = f'{cache_dir}/Phase2Answers' | |
| path_scale = f'{cache_dir}/Phase2AnswersScaled' | |
| url = 'https://drive.google.com/u/0/uc?id=0BzcZKTSeYL8VYWtHVmxUR3FyUmc&export=download' | |
| filename = 'SemEval-2012-Platinum-Ratings.tar.gz' | |
| if not (os.path.exists(path_scale) and os.path.exists(path_answer)): | |
| wget(url, gdrive_filename=filename, cache_dir=cache_dir) | |
| files_answer = [os.path.basename(i) for i in glob(f'{path_answer}/*.txt')] | |
| files_scale = [os.path.basename(i) for i in glob(f'{path_scale}/*.txt')] | |
| assert files_answer == files_scale, f'files are not matched: {files_scale} vs {files_answer}' | |
| all_positive_v = {} | |
| all_negative_v = {} | |
| all_positive_t = {} | |
| all_negative_t = {} | |
| for i in files_scale: | |
| relation_id = i.split('-')[-1].replace('.txt', '') | |
| relation_id = f"{relation_id[:-1]}/{relation_id[-1]}" | |
| with open(f'{path_answer}/{i}', 'r') as f: | |
| lines_answer = [l.replace('"', '').split('\t') for l in f.read().split('\n') if not l.startswith('#') and len(l)] | |
| relation_type = list(set(list(zip(*lines_answer))[-1])) | |
| assert len(relation_type) == 1, relation_type | |
| with open(f'{path_scale}/{i}', 'r') as f: | |
| lines_scale = [[float(l[:5]), l[6:].replace('"', '')] for l in f.read().split('\n') | |
| if not l.startswith('#') and len(l)] | |
| lines_scale = sorted(lines_scale, key=lambda x: x[0]) | |
| _negative = [tuple(i.split(':')) for i in list(zip(*list(filter(lambda x: x[0] < 0, lines_scale[:n_sample_max]))))[1]] | |
| _positive = [tuple(i.split(':')) for i in list(zip(*list(filter(lambda x: x[0] > 0, lines_scale[-n_sample_max:]))))[1]] | |
| v_negative = _negative[::int(len(_negative) * (1 - v_rate))] | |
| v_positive = _positive[::int(len(_positive) * (1 - v_rate))] | |
| t_negative = [i for i in _negative if i not in v_negative] | |
| t_positive = [i for i in _positive if i not in v_positive] | |
| all_negative_v[relation_id] = v_negative | |
| all_positive_v[relation_id] = v_positive | |
| all_negative_t[relation_id] = t_negative[:n_sample] | |
| all_positive_t[relation_id] = t_positive[-n_sample:] | |
| return (all_positive_t, all_negative_t), (all_positive_v, all_negative_v) | |
| if __name__ == '__main__': | |
| (all_positive_t, all_negative_t), (all_positive_v, all_negative_v) = get_data(n_sample=10, v_rate=0.2, n_sample_max=10) | |
| os.makedirs('data', exist_ok=True) | |
| keys = all_positive_t.keys() | |
| with open("data/train.jsonl", "w") as f: | |
| for k in sorted(keys): | |
| f.write(json.dumps({"relation_type": k, "positives": all_positive_t[k], "negatives": all_negative_t[k]})) | |
| f.write("\n") | |
| keys = all_positive_v.keys() | |
| with open("data/valid.jsonl", "w") as f: | |
| for k in sorted(keys): | |
| f.write(json.dumps({"relation_type": k, "positives": all_positive_v[k], "negatives": all_negative_v[k]})) | |
| f.write("\n") | |