def __init__(self, args):
super(MoDLRecon, self).__init__(args)
self.l2lam = torch.nn.Parameter(torch.tensor(args.l2lam_init))
if args.network == 'ResNet5Block':
self.denoiser = ResNet5Block(num_filters=args.latent_channels,
filter_size=7,
batch_norm=args.batch_norm)
elif args.network == 'ResNet':
self.denoiser = ResNet(latent_channels=args.latent_channels,
num_blocks=args.num_blocks,
kernel_size=7,
batch_norm=args.batch_norm)
modl_recon_one_unroll = MoDLReconOneUnroll(denoiser=self.denoiser,
l2lam=self.l2lam,
args=args)
self.unroll_model = UnrollNet(module_list=[modl_recon_one_unroll],
data_list=[None],
num_unrolls=self.num_unrolls)