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update inference mode for unified

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This commit is contained in:
James Betker 2021-12-26 15:33:21 -07:00
parent a698d3f525
commit 4a32949b0e
1 changed files with 8 additions and 3 deletions
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codes/scripts/audio/gen/use_gpt_tts.py
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@ -7,6 +7,7 @@ import torchaudio
import yaml
from tokenizers import Tokenizer
from data.audio.paired_voice_audio_dataset import CharacterTokenizer
from data.audio.unsupervised_audio_dataset import load_audio
from data.util import is_audio_file, find_files_of_type
from models.tacotron2.text import text_to_sequence
@ -87,12 +88,11 @@ if __name__ == '__main__':
parser.add_argument('-dvae_model_name', type=str, help='Name of the DVAE model in opt.', default='dvae')
parser.add_argument('-opt_gpt_tts', type=str, help='Path to options YAML file used to train the GPT-TTS model', default='X:\\dlas\\experiments\\train_gpt_unified_voice.yml')
parser.add_argument('-gpt_tts_model_name', type=str, help='Name of the GPT TTS model in opt.', default='gpt')
parser.add_argument('-gpt_tts_model_path', type=str, help='GPT TTS model checkpoint to load.', default='X:\\dlas\\experiments\\train_gpt_unified_voice\\models\\15000_gpt.pth')
parser.add_argument('-gpt_tts_model_path', type=str, help='GPT TTS model checkpoint to load.', default='X:\\dlas\\experiments\\train_gpt_unified_voice\\models\\13750_gpt_ema.pth')
parser.add_argument('-text', type=str, help='Text to speak.', default="I am a language model that has learned to speak.")
parser.add_argument('-cond_path', type=str, help='Path to condioning sample.', default='')
parser.add_argument('-cond_preset', type=str, help='Use a preset conditioning voice (defined above). Overrides cond_path.', default='libri_test')
parser.add_argument('-num_samples', type=int, help='How many outputs to produce.', default=1)
parser.add_argument('-tokenizer_vocab_file', type=str, help='Tokenizer vocabulary file used to train.', default='../experiments/custom_lowercase_gptvoice_tokenizer_r2.json')
args = parser.parse_args()
print("Loading GPT TTS..")
@ -102,8 +102,13 @@ if __name__ == '__main__':
gpt = load_model_from_config(preloaded_options=gpt_opt, model_name=args.gpt_tts_model_name, also_load_savepoint=False, load_path=args.gpt_tts_model_path)
print("Loading data..")
tokenizer = Tokenizer.from_file(args.tokenizer_vocab_file)
tokenizer = CharacterTokenizer()
text = torch.IntTensor(tokenizer.encode(args.text.strip().lower()).ids).unsqueeze(0).cuda()
paired_text_length = gpt_opt['datasets']['train']['max_paired_text_length']
padding_needed = paired_text_length - text.shape[1]
assert padding_needed > 0
text = F.pad(text, (0,padding_needed))
cond_path = args.cond_path if args.cond_preset is None else preselected_cond_voices[args.cond_preset]
conds, cond_wav = load_conditioning(cond_path)