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svc_export.py
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svc_export.py
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import sys,os
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import torch
import argparse
from omegaconf import OmegaConf
from model.generator import Generator
from model.discriminator import Discriminator
def main(args):
hp = OmegaConf.load(args.config)
model_g = Generator(hp)
model_d = Discriminator(hp)
checkpoint = torch.load(args.checkpoint_path, map_location='cpu')
model_g.load_state_dict(checkpoint['model_g'])
model_d.load_state_dict(checkpoint['model_d'])
torch.save({
'model_g': model_g.state_dict(),
}, "maxgan_g.pth")
torch.save({
'model_g': model_g.state_dict(),
'model_d': model_d.state_dict(),
}, "maxgan_pretrain_32K.pth")
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-c', '--config', type=str, required=True,
help="yaml file for config. will use hp_str from checkpoint if not given.")
parser.add_argument('-p', '--checkpoint_path', type=str, required=True,
help="path of checkpoint pt file for evaluation")
args = parser.parse_args()
main(args)