File size: 3,252 Bytes
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def get_args_pretrain():
parser = argparse.ArgumentParser('MAE pre-training', add_help=False)
parser.add_argument('--batch_size', default=32, type=int,
help='Batch size per GPU (effective batch size is batch_size * accum_iter * # gpus')
parser.add_argument('--epochs', default=100, type=int)
parser.add_argument('--warmup_epochs', type=int, default=5, metavar='N',
help='epochs to warmup LR')
parser.add_argument('--accum_iter', default=1, type=int,
help='Accumulate gradient iterations (for increasing the effective batch size under memory constraints)')
parser.add_argument('--finetune',
default='.', )
# Model parameters
parser.add_argument('--model', default='mae_vit_base_patch16', type=str, metavar='MODEL',
help='Name of model to train')
parser.add_argument('--input_size', default=448, type=int,
help='images input size')
parser.add_argument('--mask_ratio', default=0.75, type=float,
help='Masking ratio (percentage of removed patches).')
parser.add_argument('--norm_pix_loss', action='store_true',
help='Use (per-patch) normalized pixels as targets for computing loss')
parser.set_defaults(norm_pix_loss=False)
# Optimizer parameters
parser.add_argument('--weight_decay', type=float, default=0.05,
help='weight decay (default: 0.05)')
parser.add_argument('--lr', type=float, default=None, metavar='LR',
help='learning rate (absolute lr)')
parser.add_argument('--blr', type=float, default=1e-4, metavar='LR',
help='base learning rate: absolute_lr = base_lr * total_batch_size / 256')
parser.add_argument('--min_lr', type=float, default=5e-8, metavar='LR',
help='lower lr bound for cyclic schedulers that hit 0')
# Dataset parameters
parser.add_argument('--data_path', default=f'/home/SARDatasets/SARfolder/', type=str,
help='dataset pathpwp')
parser.add_argument('--output_dir', default='./output',
help='path where to save, empty for no saving')
parser.add_argument('--log_dir', default='./output',
help='path where to tensorboard log')
parser.add_argument('--device', default='cuda',
help='device to use for training / testing')
parser.add_argument('--seed', default=0, type=int)
parser.add_argument('--resume', default=False,
help='resume from checkpoint')
parser.add_argument('--start_epoch', default=0, type=int, metavar='N',
help='start epoch')
parser.add_argument('--num_workers', default=4, type=int)
parser.add_argument('--pin_mem', action='store_true',
help='Pin CPU memory in DataLoader for more efficient (sometimes) transfer to GPU.')
parser.add_argument('--no_pin_mem', action='store_false', dest='pin_mem')
parser.set_defaults(pin_mem=True)
return parser
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