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32 lines
1.4 KiB
32 lines
1.4 KiB
import argparse
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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# NN
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parser.add_argument('--in_channels', type=int, default=3)
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parser.add_argument('--n_classes', type=int, default=10)
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parser.add_argument('--trained', type=str, default='')
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parser.add_argument('--slope', type=float, default=0.2)
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parser.add_argument('--model', type=str, default='default')
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# train
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parser.add_argument('--lr', type=float, default=1e-5)
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parser.add_argument('--d_lr', type=float, default=1e-3)
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parser.add_argument('--weight_decay', type=float, default=2.5e-5)
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parser.add_argument('--epochs', type=int, default=500)
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parser.add_argument('--batch_size', type=int, default=32)
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parser.add_argument('--betas', type=float, nargs='+', default=(.5, .999))
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# misc
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parser.add_argument('--device', type=str, default='cuda:0')
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parser.add_argument('--n_workers', type=int, default=0)
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parser.add_argument('--logdir', type=str, default='outputs/garbage')
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# office dataset categories
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parser.add_argument('--src_cat', type=str, default='amazon')
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parser.add_argument('--tgt_cat', type=str, default='webcam')
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parser.add_argument('--message', '-m', type=str, default='')
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args, unknown = parser.parse_known_args()
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if args.model == 'default':
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from core.experiment import run
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elif args.model == 'resnet50':
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from core.experiment_rn50 import run
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run(args)
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