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parser.add_argument('--load_path',
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help = 'load a saved experiment')
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parser.add_argument('--load_iter',
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help = 'iteration of saved model to load')
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parser.add_argument('--save_path',
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help = 'path for saving the experiment')
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# loading previous stages in later stages
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parser.add_argument('--enc_path',
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help = 'path to saved encoder')
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parser.add_argument('--enc_iter', type = int,
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help = 'iteration of saved encoder to load')
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parser.add_argument('--cla_path',
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help = 'path to saved classifier')
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parser.add_argument('--cla_iter', type = int,
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help = 'iteration of saved classifier to load')
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parser.add_argument('--reset_gen', action = 'store_true',
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help = 'do not inherit stage 1 generator')
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parser.add_argument('--reset_sty', action = 'store_true',
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help = 'do not inherit of stage 1 style codes')
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parser.add_argument('--reset_dis', action = 'store_true',
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help = 'do not initialize discriminator with pre-trained c2')
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parser.add_argument('--reset_cla', action = 'store_true',
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help = 'do not inherit pre-trained c2')
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# dataset
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parser.add_argument('--data_root',
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help = 'path to dataset')
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parser.add_argument('--weight_root',
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help = 'path to reconstruction weight maps')
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parser.add_argument('--image_size', type = int,
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help = 'size of image')
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parser.add_argument('--crop_size', type = int,
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help = 'center crop size before resizing')
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# base network structures
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parser.add_argument('--features', type = int, nargs = '+',
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help = 'number of features')
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parser.add_argument('--blocks', nargs = '+',
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help = 'sequence of blocks')
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parser.add_argument('--adain_features', type = int,
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help = 'number of AdaIn features')
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parser.add_argument('--adain_blocks', type = int,
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help = 'number of AdaIn blocks')
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parser.add_argument('--content_size', type = int,
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help = 'length of content code')
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parser.add_argument('--style_size', type = int,
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help = 'length of style code')
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# network structure for each network, overrides the base
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parser.add_argument('--enc_features', type = int, nargs = '+',
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help = 'number of features in encoder')
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parser.add_argument('--enc_blocks', nargs = '+',
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help = 'sequence of blocks in encoder')
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parser.add_argument('--enc_adain_features', type = int,
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help = 'number of AdaIn features in encoder')
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parser.add_argument('--enc_adain_blocks', type = int,
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help = 'number of AdaIn blocks in encoder')
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parser.add_argument('--gen_features', type = int, nargs = '+',
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help = 'number of features in generator')
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parser.add_argument('--gen_blocks', nargs = '+',
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help = 'sequence of blocks in generator')
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parser.add_argument('--gen_adain_features', type = int,
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help = 'number of AdaIn features in generator')
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parser.add_argument('--gen_adain_blocks', type = int,
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help = 'number of AdaIn blocks in generator')
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parser.add_argument('--cla_features', type = int, nargs = '+',
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help = 'number of features in classifier')
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parser.add_argument('--cla_blocks', nargs = '+',
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help = 'sequence of blocks in classifier')
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parser.add_argument('--cla_adain_features', type = int,
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help = 'number of AdaIn features in classifier')
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parser.add_argument('--cla_adain_blocks', type = int,
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help = 'number of AdaIn blocks in classifier')
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parser.add_argument('--dis_features', type = int, nargs = '+',
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help = 'number of features in discriminator')
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parser.add_argument('--dis_blocks', nargs = '+',
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help = 'sequence of blocks in discriminator')
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parser.add_argument('--dis_adain_features', type = int,
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help = 'number of AdaIn features in discriminator')
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parser.add_argument('--dis_adain_blocks', type = int,
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help = 'number of AdaIn blocks in discriminator')
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parser.add_argument('--mlp', action = 'store_true',
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help = 'use MLP in stage 1')
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parser.add_argument('--mlp_features', type = int,
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help = 'number of features in MLP classifier')
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parser.add_argument('--mlp_layers', type = int,
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help = 'number of layers in MLP classifier')
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# weighting
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parser.add_argument('--con_weight', type = float,
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help = 'weight of content loss')
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parser.add_argument('--sty_weight', type = float,
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help = 'weight of style loss')
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