| import torch | |
| from typing import Optional | |
| from nitrous_ema import PostHocEMA | |
| from mmaudio.model.networks_new import get_my_mmaudio | |
| def synthesize_ema(sigma: float, step: Optional[int]): | |
| vae = get_my_mmaudio('small_44k') | |
| emas = PostHocEMA(vae, | |
| sigma_rels=[0.05, 0.1], | |
| update_every=1, | |
| checkpoint_every_num_steps=5000, | |
| checkpoint_folder='/inspire/hdd/ws-f4d69b29-e0a5-44e6-bd92-acf4de9990f0/gaopeng/zhoutao-240108120126/kwang/MMAudio/output/vgg_only_small_44k_new_model_feb1/ema_ckpts') | |
| synthesized_ema = emas.synthesize_ema_model(sigma_rel=sigma, step=step, device='cpu') | |
| state_dict = synthesized_ema.ema_model.state_dict() | |
| return state_dict | |
| # Synthesize EMA | |
| ema_sigma = 0.05 | |
| print('Start !!!') | |
| state_dict = synthesize_ema(ema_sigma, step=None) | |
| save_dir = '/inspire/hdd/ws-f4d69b29-e0a5-44e6-bd92-acf4de9990f0/gaopeng/zhoutao-240108120126/kwang/MMAudio/output/vgg_only_small_44k_new_model_feb1/vgg_only_small_44k_new_model_feb1_ema_final.pth' | |
| torch.save(state_dict, save_dir) | |
| print('Finished !!!') | |