def hello():
waveglow.load_waveglow_torch('../models/waveglow/waveglow_v5_model.pt')
# melgan.load_melgan_model(r'E:\githup\zhrtvc\models\vocoder\saved_models\melgan\melgan_multi_speaker.pt',
# args_path=r'E:\githup\zhrtvc\models\vocoder\saved_models\melgan\args.yml')
melgan.load_melgan_torch('../models/melgan/melgan_multi_speaker_model.pt')
# mellotron.load_mellotron_model(r'E:\githup\zhrtvc\models\mellotron\samples\checkpoint\checkpoint-000000.pt',
# hparams_path=r'E:\githup\zhrtvc\models\mellotron\samples\metadata\hparams.yml')
#
# torch.save(mellotron._model, '../models/mellotron/mellotron_samples_model.pt')
mellotron.load_mellotron_torch(
'../models/mellotron/mellotron_samples_model.pt')
# text, mel, speaker, f0
text = torch.randint(0, 100, [4, 50]).cuda()
style = 0 # torch.rand(4, 80, 400).cuda()
speaker = torch.randint(0, 10, [4]).cuda()
f0 = None # torch.rand(4, 400)
mels = mellotron.generate_mel(text=text,
style=style,
speaker=speaker,
f0=f0)
for mel in mels:
print(mel.shape)
mel = torch.rand(4, 80, 400).cuda()
wav = waveglow.generate_wave(mel)
print(wav.shape)
def load_models(args):
if args.waveglow_path:
waveglow.load_waveglow_torch(args.waveglow_path)
if args.melgan_path:
melgan.load_melgan_torch(args.melgan_path)
if args.mellotron_path:
mellotron.load_mellotron_torch(args.mellotron_path)
def load_models(mellotron_path=_mellotron_path,
waveglow_path=_waveglow_path,
ge2e_path=_ge2e_path,
mellotron_hparams_path=_mellotron_hparams_path,
**kwargs):
global _use_waveglow
global _dataloader
if (mellotron_path == _mellotron_path and waveglow_path == _waveglow_path
and ge2e_path == _ge2e_path
and mellotron_hparams_path == _mellotron_hparams_path):
download_resource()
if _dataloader is not None:
return
if waveglow_path and waveglow_path not in {'_', 'gf', 'griffinlim'}:
waveglow.load_waveglow_torch(waveglow_path)
_use_waveglow = 1
if mellotron_path:
mellotron.load_mellotron_torch(mellotron_path)
mellotron_hparams = mellotron.create_hparams(
open(mellotron_hparams_path, encoding='utf8').read())
mellotron_hparams.encoder_model_fpath = ge2e_path
_dataloader = mellotron.TextMelLoader(audiopaths_and_text='',
hparams=mellotron_hparams,
speaker_ids=None,
mode='test')
return _dataloader
def load_models(args):
global _use_waveglow
if args.waveglow_path and args.waveglow_path not in {
'_', 'gf', 'griffinlim'
}:
waveglow.load_waveglow_torch(args.waveglow_path)
_use_waveglow = 1
if args.mellotron_path:
mellotron.load_mellotron_torch(args.mellotron_path)
