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arguments.py
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arguments.py
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import argparse
def get_args_parser():
parser = argparse.ArgumentParser('Holistic edge attention transformer', add_help=False)
parser.add_argument('--exp_dataset', default='outdoor',
help='the dataset for experiments, outdoor/s3d_floorplan')
parser.add_argument('--lr', default=2e-4, type=float)
parser.add_argument('--batch_size', default=16, type=int)
parser.add_argument('--weight_decay', default=1e-5, type=float)
parser.add_argument('--epochs', default=800, type=int)
parser.add_argument('--lr_drop', default=600, type=int)
parser.add_argument('--clip_max_norm', default=0.1, type=float,
help='gradient clipping max norm')
parser.add_argument('--print_freq', default=40, type=int)
parser.add_argument('--output_dir', default='./checkpoints/ckpts_heat_outdoor_256',
help='path where to save, empty for no saving')
parser.add_argument('--resume', default='',
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('--image_size', default=256, type=int)
parser.add_argument('--max_corner_num', default=150, type=int,
help='the max number of corners allowed in the experiments')
parser.add_argument('--corner_to_edge_multiplier', default=3, type=int,
help='the max number of edges based on the number of corner candidates (assuming the '
'average degree never greater than 6)')
parser.add_argument('--lambda_corner', default=0.05, type=float,
help='the max number of corners allowed in the experiments')
parser.add_argument('--run_validation', action='store_true',
help='Whether run validation or not, default: False')
return parser