def main():
parser = argparse.ArgumentParser()
# parser.add_argument('--base_dir', default=os.path.expanduser('/past_projects/DB'))
# parser.add_argument('--output', default='sitec')
parser.add_argument('--dataset',
required=True,
choices=[
'blizzard', 'ljspeech', 'sitec', 'sitec_short',
'selvas_multi', 'libri_tts',
'selvas_multispeaker_pron', 'integrate_dataset',
'public_korean_pron', 'check_file_integrity'
])
parser.add_argument(
'--hparams',
default='',
help=
'Hyperparameter overrides as a comma-separated list of name=value pairs'
)
parser.add_argument('--num_workers', type=int, default=12)
args = parser.parse_args()
hparams = create_hparams(args.hparams)
if args.dataset == 'libri_tts':
assert (True)
print("Not implemented")
# preprocess_libri_tts(args)
elif args.dataset == 'selvas_multi':
assert (True)
print("Not implemented")
# preprocess_selvas_multi(args)
elif args.dataset == 'integrate_dataset':
integrate_dataset(args)
elif args.dataset == 'selvas_multispeaker_pron':
preprocess_selvas_multispeaker_pron(args)
elif args.dataset == 'public_korean_pron':
preprocess_public_korean_pron(args)
elif args.dataset == 'check_file_integrity':
check_for_file_integrity(args)
'''
Defines the set of symbols used in text input to the model.
The default is a set of ASCII characters that works well for English or text that has been run
through Unidecode. For other data, you can modify _characters. See TRAINING_DATA.md for details.
'''
from configs.hparams import create_hparams # hparams, hparams_debug_string
from .korean import ALL_SYMBOLS
hparams=create_hparams()
if hparams.text_cleaners != 'korean_cleaners':
# symbols = '_~ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!\'(),-.:;? '
print('english cleaner')
symbols = '_~ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!\'(),-.:;?<>《》 '
else:
print('korean cleaner')
symbols = ALL_SYMBOLS
type=int,
default=0,
required=False,
help='rank of current gpu')
parser.add_argument('--group_name',
type=str,
default='group_name',
required=False,
help='Distributed group name')
parser.add_argument('--hparams',
type=str,
required=False,
help='comma separated name=value pairs')
args = parser.parse_args()
hparams = create_hparams(args.hparams)
if hparams.text_cleaners != 'korean_cleaners':
# symbols = '_~ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!\'(),-.:;? '
symbols = '_~ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!\'(),-.:;?<>《》 '
else:
symbols = ALL_SYMBOLS
torch.backends.cudnn.enabled = hparams.cudnn_enabled
torch.backends.cudnn.benchmark = hparams.cudnn_benchmark
print("FP16 Run:", hparams.fp16_run)
print("Dynamic Loss Scaling:", hparams.dynamic_loss_scaling)
print("Distributed Run:", hparams.distributed_run)
print("cuDNN Enabled:", hparams.cudnn_enabled)
print("cuDNN Benchmark:", hparams.cudnn_benchmark)
train(args.output_directory, args.log_directory, args.checkpoint_path,