def add_model_specific_args()

in fastmri/pl_modules/varnet_module.py [0:0]


    def add_model_specific_args(parent_parser):  # pragma: no-cover
        """
        Define parameters that only apply to this model
        """
        parser = ArgumentParser(parents=[parent_parser], add_help=False)
        parser = MriModule.add_model_specific_args(parser)

        # param overwrites

        # network params
        parser.add_argument(
            "--num_cascades",
            default=12,
            type=int,
            help="Number of VarNet cascades",
        )
        parser.add_argument(
            "--pools",
            default=4,
            type=int,
            help="Number of U-Net pooling layers in VarNet blocks",
        )
        parser.add_argument(
            "--chans",
            default=18,
            type=int,
            help="Number of channels for U-Net in VarNet blocks",
        )
        parser.add_argument(
            "--sens_pools",
            default=4,
            type=int,
            help="Number of pooling layers for sense map estimation U-Net in VarNet",
        )
        parser.add_argument(
            "--sens_chans",
            default=8,
            type=float,
            help="Number of channels for sense map estimation U-Net in VarNet",
        )

        # training params (opt)
        parser.add_argument(
            "--lr", default=0.0003, type=float, help="Adam learning rate"
        )
        parser.add_argument(
            "--lr_step_size",
            default=40,
            type=int,
            help="Epoch at which to decrease step size",
        )
        parser.add_argument(
            "--lr_gamma",
            default=0.1,
            type=float,
            help="Extent to which step size should be decreased",
        )
        parser.add_argument(
            "--weight_decay",
            default=0.0,
            type=float,
            help="Strength of weight decay regularization",
        )

        return parser