mirror of
https://github.com/AntoineHX/smart_augmentation.git
synced 2025-05-04 12:10:45 +02:00
73 lines
4.1 KiB
Python
73 lines
4.1 KiB
Python
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import argparse
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#Argparse
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parser = argparse.ArgumentParser(description='Run smart augmentation')
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parser.add_argument('-dv','--device', default='cuda', dest='device',
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help='Device : cpu / cuda')
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parser.add_argument('-dt','--dtype', default='FP32', dest='dtype',
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help='Data type (Default: Float32)')
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parser.add_argument('-m','--model', default='resnet18', dest='model',
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help='Network')
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parser.add_argument('-pt','--pretrained', default='', dest='pretrained',
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help='Use pretrained weight if possible')
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parser.add_argument('-ep','--epochs', type=int, default=10, dest='epochs',
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help='epoch')
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# parser.add_argument('-ot', '--optimizer', default='SGD', dest='opt_type',
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# help='Model optimizer')
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parser.add_argument('-lr', type=float, default=1e-1, dest='lr',
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help='Model learning rate')
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parser.add_argument('-mo', '--momentum', type=float, default=0.9, dest='momentum',
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help='Momentum')
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parser.add_argument('-dc', '--decay', type=float, default=0.0005, dest='decay',
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help='Weight decay')
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parser.add_argument('-ns','--nesterov', type=bool, default=False, dest='nesterov',
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help='Nesterov momentum ?')
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parser.add_argument('-sc', '--scheduler', default='cosine', dest='scheduler',
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help='Model learning rate scheduler')
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parser.add_argument('-wu', '--warmup', type=float, default=0, dest='warmup',
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help='Warmup multiplier')
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parser.add_argument('-a','--augment', type=bool, default=False, dest='augment',
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help='Data augmentation ?')
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parser.add_argument('-N', type=int, default=1,
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help='Combination of TF')
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parser.add_argument('-K', type=int, default=0,
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help='Number inner iteration')
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parser.add_argument('-al','--augment_loss', type=int, default=1, dest='augment_loss',
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help='Number of augmented example for each sample in loss computation.')
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parser.add_argument('-t', '--temp', type=float, default=0.5, dest='temp',
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help='Probability distribution temperature')
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parser.add_argument('-tfc','--tf_config', default='../config/invScale_wide_tf_config.json', dest='tf_config',
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help='TF config')
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parser.add_argument('-ls', '--learn_seq', type=bool, default=False, dest='learn_seq',
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help='Learn order of application of TF (DataugV7-8) ?')
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parser.add_argument('-fm', '--fixed_mag', type=bool, default=False, dest='fixed_mag',
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help='Fixed magnitude when learning data augmentation ?')
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parser.add_argument('-sm', '--shared_mag', type=bool, default=False, dest='shared_mag',
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help='Shared magnitude when learning data augmentation ?')
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# parser.add_argument('-mot', '--metaoptimizer', default='Adam', dest='meta_opt_type',
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# help='Meta optimizer (Augmentations)')
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parser.add_argument('-mlr', type=float, default=1e-2, dest='mlr',
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help='Meta learning rate (Augmentations)')
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parser.add_argument('-ms', type=int, default=0, dest='meta_epoch_start',
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help='Epoch at which start meta learning')
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parser.add_argument('-mr', type=float, default=0.001, dest='mag_reg',
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help='Augmentation magnitudes regulation factor')
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parser.add_argument('-rf','--res_folder', default='../res/', dest='res_folder',
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help='Results folder')
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parser.add_argument('-pf','--postfix', default='', dest='postfix',
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help='Res postfix')
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parser.add_argument('-dr','--dataroot', default='~/scratch/data', dest='dataroot',
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help='Datasets folder')
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parser.add_argument('-ds','--dataset', default='CIFAR10', dest='dataset',
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help='Dataset')
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parser.add_argument('-bs','--batch_size', type=int, default=256, dest='batch_size',
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help='Batch size') #256 (WRN) / 512
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parser.add_argument('-w','--workers', type=int, default=6, dest='workers',
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help='Numer of workers (Nb CPU cores).')
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