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 !!!')