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remove weigth norm when synthesizing to make inference fatser

This commit is contained in:
chenfeiyu 2020-07-17 17:56:23 +08:00
parent 45f6e55911
commit de6e15339f
1 changed files with 7 additions and 1 deletions
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8
examples/deepvoice3/synthesize.py
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@ -17,7 +17,7 @@ import soundfile as sf
from parakeet.data import SliceDataset, DataCargo, PartialyRandomizedSimilarTimeLengthSampler, SequentialSampler from parakeet.data import SliceDataset, DataCargo, PartialyRandomizedSimilarTimeLengthSampler, SequentialSampler
from parakeet.utils.io import save_parameters, load_parameters, add_yaml_config_to_args from parakeet.utils.io import save_parameters, load_parameters, add_yaml_config_to_args
from parakeet.g2p import en from parakeet.g2p import en
from parakeet.models.deepvoice3.weight_norm_hook import remove_weight_norm
from vocoder import WaveflowVocoder, GriffinLimVocoder from vocoder import WaveflowVocoder, GriffinLimVocoder
from train import create_model from train import create_model
@ -25,6 +25,12 @@ from train import create_model
def main(args, config): def main(args, config):
model = create_model(config) model = create_model(config)
loaded_step = load_parameters(model, checkpoint_path=args.checkpoint) loaded_step = load_parameters(model, checkpoint_path=args.checkpoint)
for name, layer in model.named_sublayers():
try:
remove_weight_norm(layer)
except ValueError:
# this layer has not weight norm hook
pass
model.eval() model.eval()
if args.vocoder == "waveflow": if args.vocoder == "waveflow":
vocoder = WaveflowVocoder() vocoder = WaveflowVocoder()