deepmr.optim.CGStep#
- class deepmr.optim.CGStep(*args: Any, **kwargs: Any)[source]#
Conjugate Gradient method step.
This represents propagation through a single iteration of a CG algorithm; can be used to build unrolled architectures.
- AHA#
Normal operator AHA = AH * A.
- Type:
Callable | torch.Tensor
- Ahy#
Adjoint AH of measurement operator A applied to the measured data y.
- Type:
- ndim#
Number of spatial dimensions of the problem. It is used to infer the batch axes. If
AHA
is adeepmr.linop.Linop
operator, this is inferred fromAHA.ndim
andndim
is ignored.- Type:
Methods
__init__
(AHA, AHy[, ndim, tol])check_convergence
()dot
(s1, s2)forward
(input)