from ImgModels.Ops import _Trainer
from ImgModels.SC_FEGAN import SC_FEGAN_Trainer
import argparse, os
from Toolkit.DavisData import mp_preprocessing



parser = argparse.ArgumentParser(description="")
parser.add_argument('--dataset', type=str, default='davis',
                    choices=['voxceleb1', 'davis'],
                    help=' ')
parser.add_argument('--Optim', type=str, default='adam',
                    help=' ')
parser.add_argument('--checkname', type=str, default='SC-FEGAN',
                    help=' ')
parser.add_argument('--num_workers', type=int, default=1,
                    metavar='N', help='dataloader threads')
parser.add_argument('--batch-size', type=int, default=1,
                    help=' ')
parser.add_argument('--pin_memory', type=bool, default=True,
                    help=' ')
parser.add_argument('--shuffle', type=bool, default=True,
                    help=' ')
args = parser.parse_args()
args.abs_path = os.path.dirname(os.path.abspath(__file__))

args.lrD = 1e-4
args.lrG = 5e-4
# args.batch_size = 24
args.cuda = True
args.visualize = True
#
args.checkname = "useless"
args.lambda_per = 0.05
args.lambda_gt = 0.001
args.lambda_sn = 0.001
args.lambda_sty = 120
args.lambda_tv = 0.1
args.steps_dis = 1
args.max_epoches = 50
args.resume = "/data1/yingruliu/Documents/Project-Video-Free-Form-Completion/run/davis/useless/experiment_1/CheckPoint.pth-0013.tar"
args.train = True
#
if __name__ == "__main__":
    trainer = SC_FEGAN_Trainer(args)
    trainer.train()
    #mp_preprocessing()

b860b9ba208e2b197d17dd14df29c26f8fdfb23d
<mask token>

<mask token>
parser.add_argument('--dataset', type=str, default='davis', choices=[
    'voxceleb1', 'davis'], help=' ')
parser.add_argument('--Optim', type=str, default='adam', help=' ')
parser.add_argument('--checkname', type=str, default='SC-FEGAN', help=' ')
parser.add_argument('--num_workers', type=int, default=1, metavar='N', help
    ='dataloader threads')
parser.add_argument('--batch-size', type=int, default=1, help=' ')
parser.add_argument('--pin_memory', type=bool, default=True, help=' ')
parser.add_argument('--shuffle', type=bool, default=True, help=' ')
<mask token>
if __name__ == '__main__':
    trainer = SC_FEGAN_Trainer(args)
    trainer.train()

<mask token>
parser = argparse.ArgumentParser(description='')
parser.add_argument('--dataset', type=str, default='davis', choices=[
    'voxceleb1', 'davis'], help=' ')
parser.add_argument('--Optim', type=str, default='adam', help=' ')
parser.add_argument('--checkname', type=str, default='SC-FEGAN', help=' ')
parser.add_argument('--num_workers', type=int, default=1, metavar='N', help
    ='dataloader threads')
parser.add_argument('--batch-size', type=int, default=1, help=' ')
parser.add_argument('--pin_memory', type=bool, default=True, help=' ')
parser.add_argument('--shuffle', type=bool, default=True, help=' ')
args = parser.parse_args()
args.abs_path = os.path.dirname(os.path.abspath(__file__))
args.lrD = 0.0001
args.lrG = 0.0005
args.cuda = True
args.visualize = True
args.checkname = 'useless'
args.lambda_per = 0.05
args.lambda_gt = 0.001
args.lambda_sn = 0.001
args.lambda_sty = 120
args.lambda_tv = 0.1
args.steps_dis = 1
args.max_epoches = 50
args.resume = (
    '/data1/yingruliu/Documents/Project-Video-Free-Form-Completion/run/davis/useless/experiment_1/CheckPoint.pth-0013.tar'
    )
args.train = True
if __name__ == '__main__':
    trainer = SC_FEGAN_Trainer(args)
    trainer.train()

from ImgModels.Ops import _Trainer
from ImgModels.SC_FEGAN import SC_FEGAN_Trainer
import argparse, os
from Toolkit.DavisData import mp_preprocessing
parser = argparse.ArgumentParser(description='')
parser.add_argument('--dataset', type=str, default='davis', choices=[
    'voxceleb1', 'davis'], help=' ')
parser.add_argument('--Optim', type=str, default='adam', help=' ')
parser.add_argument('--checkname', type=str, default='SC-FEGAN', help=' ')
parser.add_argument('--num_workers', type=int, default=1, metavar='N', help
    ='dataloader threads')
parser.add_argument('--batch-size', type=int, default=1, help=' ')
parser.add_argument('--pin_memory', type=bool, default=True, help=' ')
parser.add_argument('--shuffle', type=bool, default=True, help=' ')
args = parser.parse_args()
args.abs_path = os.path.dirname(os.path.abspath(__file__))
args.lrD = 0.0001
args.lrG = 0.0005
args.cuda = True
args.visualize = True
args.checkname = 'useless'
args.lambda_per = 0.05
args.lambda_gt = 0.001
args.lambda_sn = 0.001
args.lambda_sty = 120
args.lambda_tv = 0.1
args.steps_dis = 1
args.max_epoches = 50
args.resume = (
    '/data1/yingruliu/Documents/Project-Video-Free-Form-Completion/run/davis/useless/experiment_1/CheckPoint.pth-0013.tar'
    )
args.train = True
if __name__ == '__main__':
    trainer = SC_FEGAN_Trainer(args)
    trainer.train()

from ImgModels.Ops import _Trainer
from ImgModels.SC_FEGAN import SC_FEGAN_Trainer
import argparse, os
from Toolkit.DavisData import mp_preprocessing



parser = argparse.ArgumentParser(description="")
parser.add_argument('--dataset', type=str, default='davis',
                    choices=['voxceleb1', 'davis'],
                    help=' ')
parser.add_argument('--Optim', type=str, default='adam',
                    help=' ')
parser.add_argument('--checkname', type=str, default='SC-FEGAN',
                    help=' ')
parser.add_argument('--num_workers', type=int, default=1,
                    metavar='N', help='dataloader threads')
parser.add_argument('--batch-size', type=int, default=1,
                    help=' ')
parser.add_argument('--pin_memory', type=bool, default=True,
                    help=' ')
parser.add_argument('--shuffle', type=bool, default=True,
                    help=' ')
args = parser.parse_args()
args.abs_path = os.path.dirname(os.path.abspath(__file__))

args.lrD = 1e-4
args.lrG = 5e-4
# args.batch_size = 24
args.cuda = True
args.visualize = True
#
args.checkname = "useless"
args.lambda_per = 0.05
args.lambda_gt = 0.001
args.lambda_sn = 0.001
args.lambda_sty = 120
args.lambda_tv = 0.1
args.steps_dis = 1
args.max_epoches = 50
args.resume = "/data1/yingruliu/Documents/Project-Video-Free-Form-Completion/run/davis/useless/experiment_1/CheckPoint.pth-0013.tar"
args.train = True
#
if __name__ == "__main__":
    trainer = SC_FEGAN_Trainer(args)
    trainer.train()
    #mp_preprocessing()
