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def set_template(args): |
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if args.template.find('jpeg') >= 0: |
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args.data_train = 'DIV2K_jpeg' |
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args.data_test = 'DIV2K_jpeg' |
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args.epochs = 200 |
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args.decay = '100' |
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if args.template.find('EDSR_paper') >= 0: |
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args.model = 'EDSR' |
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args.n_resblocks = 32 |
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args.n_feats = 256 |
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args.res_scale = 0.1 |
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if args.template.find('MDSR') >= 0: |
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args.model = 'MDSR' |
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args.patch_size = 48 |
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args.epochs = 650 |
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if args.template.find('DDBPN') >= 0: |
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args.model = 'DDBPN' |
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args.patch_size = 128 |
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args.scale = '4' |
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args.data_test = 'Set5' |
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args.batch_size = 20 |
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args.epochs = 1000 |
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args.decay = '500' |
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args.gamma = 0.1 |
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args.weight_decay = 1e-4 |
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args.loss = '1*MSE' |
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if args.template.find('GAN') >= 0: |
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args.epochs = 200 |
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args.lr = 5e-5 |
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args.decay = '150' |
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if args.template.find('RCAN') >= 0: |
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args.model = 'RCAN' |
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args.n_resgroups = 10 |
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args.n_resblocks = 20 |
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args.n_feats = 64 |
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args.chop = True |
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if args.template.find('VDSR') >= 0: |
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args.model = 'VDSR' |
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args.n_resblocks = 20 |
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args.n_feats = 64 |
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args.patch_size = 41 |
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args.lr = 1e-1 |
