import hashlib import logging from pathlib import Path import requests from tqdm import tqdm log = logging.getLogger() links = [ { 'name': 'mmaudio_small_16k.pth', 'url': 'https://databank.illinois.edu/datafiles/k6jve/download', 'md5': 'af93cde404179f58e3919ac085b8033b', }, { 'name': 'mmaudio_small_44k.pth', 'url': 'https://databank.illinois.edu/datafiles/864ya/download', 'md5': 'babd74c884783d13701ea2820a5f5b6d', }, { 'name': 'mmaudio_medium_44k.pth', 'url': 'https://databank.illinois.edu/datafiles/pa94t/download', 'md5': '5a56b6665e45a1e65ada534defa903d0', }, { 'name': 'mmaudio_large_44k.pth', 'url': 'https://databank.illinois.edu/datafiles/4jx76/download', 'md5': 'fed96c325a6785b85ce75ae1aafd2673' }, { 'name': 'mmaudio_large_44k_v2.pth', # 'url': 'https://huggingface.co/hkchengrex/MMAudio/resolve/main/weights/mmaudio_large_44k_v2.pth', 'url': 'https://databank.illinois.edu/datafiles/i1pd9/download', 'md5': '01ad4464f049b2d7efdaa4c1a59b8dfe' }, { 'name': 'v1-16.pth', 'url': 'https://github.com/hkchengrex/MMAudio/releases/download/v0.1/v1-16.pth', 'md5': '69f56803f59a549a1a507c93859fd4d7' }, { 'name': 'best_netG.pt', 'url': 'https://github.com/hkchengrex/MMAudio/releases/download/v0.1/best_netG.pt', 'md5': 'eeaf372a38a9c31c362120aba2dde292' }, { 'name': 'v1-44.pth', 'url': 'https://github.com/hkchengrex/MMAudio/releases/download/v0.1/v1-44.pth', 'md5': 'fab020275fa44c6589820ce025191600' }, { 'name': 'synchformer_state_dict.pth', 'url': 'https://github.com/hkchengrex/MMAudio/releases/download/v0.1/synchformer_state_dict.pth', 'md5': '5b2f5594b0730f70e41e549b7c94390c' }, ] def download_model_if_needed(model_path: Path): base_name = model_path.name for link in links: if link['name'] == base_name: target_link = link break else: raise ValueError(f'No link found for {base_name}') model_path.parent.mkdir(parents=True, exist_ok=True) if not model_path.exists() or hashlib.md5(open(model_path, 'rb').read()).hexdigest() != target_link['md5']: log.info(f'Downloading {base_name} to {model_path}...') r = requests.get(target_link['url'], stream=True) total_size = int(r.headers.get('content-length', 0)) block_size = 1024 t = tqdm(total=total_size, unit='iB', unit_scale=True) with open(model_path, 'wb') as f: for data in r.iter_content(block_size): t.update(len(data)) f.write(data) t.close() if total_size != 0 and t.n != total_size: raise RuntimeError('Error while downloading %s' % base_name)