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)