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so-vits-svc
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This commit is contained in:
ylzz1997 2023-05-18 01:15:26 +08:00
parent 63066d3caa
commit 98db34e82d
2 changed files with 27 additions and 15 deletions
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40
inference/infer_tool.py
View File

@ -124,31 +124,41 @@ class Svc(object):
only_diffusion = False,
):
self.net_g_path = net_g_path
self.only_diffusion = only_diffusion
self.shallow_diffusion = shallow_diffusion
if device is None:
self.dev = torch.device("cuda" if torch.cuda.is_available() else "cpu")
else:
self.dev = torch.device(device)
self.net_g_ms = None
self.hps_ms = utils.get_hparams_from_file(config_path)
self.target_sample = self.hps_ms.data.sampling_rate
self.hop_size = self.hps_ms.data.hop_length
self.spk2id = self.hps_ms.spk
self.nsf_hifigan_enhance = nsf_hifigan_enhance
self.only_diffusion = only_diffusion
self.shallow_diffusion = shallow_diffusion
try:
self.speech_encoder = self.hps_ms.model.speech_encoder
except Exception as e:
self.speech_encoder = 'vec768l12'
if not self.only_diffusion:
self.hps_ms = utils.get_hparams_from_file(config_path)
self.target_sample = self.hps_ms.data.sampling_rate
self.hop_size = self.hps_ms.data.hop_length
self.spk2id = self.hps_ms.spk
try:
self.speech_encoder = self.hps_ms.model.speech_encoder
except Exception as e:
self.speech_encoder = 'vec768l12'
self.nsf_hifigan_enhance = nsf_hifigan_enhance
if self.shallow_diffusion or self.only_diffusion:
self.diffusion_model,self.vocoder,self.diffusion_args = load_model_vocoder(diffusion_model_path,self.dev,config_path=diffusion_config_path)
if os.path.exists(diffusion_model_path) and os.path.exists(diffusion_model_path):
self.diffusion_model,self.vocoder,self.diffusion_args = load_model_vocoder(diffusion_model_path,self.dev,config_path=diffusion_config_path)
if self.only_diffusion:
self.target_sample = self.diffusion_args.data.sampling_rate
self.hop_size = self.diffusion_args.data.block_size
self.spk2id = self.diffusion_args.spk
self.speech_encoder = self.diffusion_args.data.encoder
else:
print("No diffusion model or config found. Shallow diffusion mode will False")
self.shallow_diffusion = self.only_diffusion = False
# load hubert and model
if not self.only_diffusion:
self.load_model()
self.hubert_model = utils.get_speech_encoder(self.speech_encoder,device=self.dev)
self.volume_extractor = utils.Volume_Extractor(self.hps_ms.data.hop_length)
assert self.diffusion_args.data.encoder == self.hps_ms.model.speech_encoder
self.volume_extractor = utils.Volume_Extractor(self.hop_size)
else:
self.hubert_model = utils.get_speech_encoder(self.diffusion_args.data.encoder,device=self.dev)
self.volume_extractor = utils.Volume_Extractor(self.diffusion_args.data.block_size)
@ -212,7 +222,7 @@ class Svc(object):
k_step = 100
):
speaker_id = self.spk2id.__dict__.get(speaker)
speaker_id = self.spk2id.get(speaker)
if not speaker_id and type(speaker) is int:
if len(self.spk2id.__dict__) >= speaker:
speaker_id = speaker

2
utils.py
View File

@ -410,6 +410,8 @@ class HParams():
def __repr__(self):
return self.__dict__.__repr__()
def get(self,index):
return self.__dict__.get(index)
class Volume_Extractor:
def __init__(self, hop_size = 512):