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)