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