fastmri_examples/unet/unet_reproduce_20201111.py/unet_brain_leaderboard.py [94:128]:
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    parser.add_argument(
        "--mode",
        default="train",
        choices=("train", "test"),
        type=str,
        help="Operation mode",
    )

    # data transform params
    parser.add_argument(
        "--mask_type",
        choices=("random", "equispaced"),
        default="equispaced",
        type=str,
        help="Type of k-space mask",
    )
    parser.add_argument(
        "--center_fractions",
        nargs="+",
        default=[0.08, 0.04],
        type=float,
        help="Number of center lines to use in mask",
    )
    parser.add_argument(
        "--accelerations",
        nargs="+",
        default=[4, 8],
        type=int,
        help="Acceleration rates to use for masks",
    )

    # data config with path to fastMRI data and batch size
    parser = FastMriDataModule.add_data_specific_args(parser)
    parser.set_defaults(
        data_path=data_path,  # path to fastMRI data
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fastmri_examples/varnet/varnet_reproduce_20201111/varnet_knee_leaderboard.py [96:130]:
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    parser.add_argument(
        "--mode",
        default="train",
        choices=("train", "test"),
        type=str,
        help="Operation mode",
    )

    # data transform params
    parser.add_argument(
        "--mask_type",
        choices=("random", "equispaced"),
        default="equispaced",
        type=str,
        help="Type of k-space mask",
    )
    parser.add_argument(
        "--center_fractions",
        nargs="+",
        default=[0.08, 0.04],
        type=float,
        help="Number of center lines to use in mask",
    )
    parser.add_argument(
        "--accelerations",
        nargs="+",
        default=[4, 8],
        type=int,
        help="Acceleration rates to use for masks",
    )

    # data config
    parser = FastMriDataModule.add_data_specific_args(parser)
    parser.set_defaults(
        data_path=data_path,  # path to fastMRI data
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