resample real inputs for music_diffusion_fid

pull/9/head
James Betker 2022-06-18 10:40:48 +07:00
parent c000e489fa
commit cb7569ee5e
1 changed files with 10 additions and 6 deletions

@ -52,7 +52,7 @@ class MusicDiffusionFid(evaluator.Evaluator):
model_var_type='learned_range', loss_type='mse', betas=get_named_beta_schedule('linear', 4000),
conditioning_free=False, conditioning_free_k=1)
self.dev = self.env['device']
mode = opt_get(opt_eval, ['diffusion_type'], 'tts')
mode = opt_get(opt_eval, ['diffusion_type'], 'spec_decode')
self.spec_decoder = get_mel2wav_model()
self.projector = ContrastiveAudio(model_dim=512, transformer_heads=8, dropout=0, encoder_depth=8, mel_channels=256)
@ -141,7 +141,11 @@ class MusicDiffusionFid(evaluator.Evaluator):
model_kwargs={'aligned_conditioning': gen_mel_denorm})
gen_wav = pixel_shuffle_1d(gen_wav, 16)
return gen_wav, real_resampled, gen_mel, mel_norm, sample_rate
real_wav = self.spectral_diffuser.p_sample_loop(self.spec_decoder, output_shape,
model_kwargs={'aligned_conditioning': mel})
real_wav = pixel_shuffle_1d(real_wav, 16)
return gen_wav, real_wav.squeeze(0), gen_mel, mel_norm, sample_rate
def perform_partial_diffusion_from_codes_quant(self, audio, sample_rate=22050, partial_low=0, partial_high=256):
if sample_rate != sample_rate:
@ -271,15 +275,15 @@ class MusicDiffusionFid(evaluator.Evaluator):
if __name__ == '__main__':
diffusion = load_model_from_config('X:\\dlas\\experiments\\train_music_diffusion_tfd_quant.yml', 'generator',
also_load_savepoint=False,
load_path='X:\\dlas\\experiments\\train_music_diffusion_tfd11\\models\\24000_generator_ema.pth'
load_path='X:\\dlas\\experiments\\train_music_diffusion_tfd12\\models\\41500_generator_ema.pth'
).cuda()
opt_eval = {'path': 'Y:\\split\\yt-music-eval', # eval music, mostly electronica. :)
#'path': 'E:\\music_eval', # this is music from the training dataset, including a lot more variety.
'diffusion_steps': 200,
'conditioning_free': False, 'conditioning_free_k': 1,
'diffusion_schedule': 'cosine', 'diffusion_type': 'from_codes_quant',
'conditioning_free': True, 'conditioning_free_k': 2,
'diffusion_schedule': 'linear', 'diffusion_type': 'from_codes_quant',
#'partial_low': 128, 'partial_high': 192
}
env = {'rank': 0, 'base_path': 'D:\\tmp\\test_eval_music', 'step': 600, 'device': 'cuda', 'opt': {}}
env = {'rank': 0, 'base_path': 'D:\\tmp\\test_eval_music', 'step': 605, 'device': 'cuda', 'opt': {}}
eval = MusicDiffusionFid(diffusion, opt_eval, env)
print(eval.perform_eval())