spyrit.core.recon.LearnedPGD.forward

LearnedPGD.forward(x)

Full pipeline of reconstruction network

Args:

x: ground-truth images

Shape:

x: ground-truth images with shape \((B,C,H,W)\)

output: reconstructed images with shape \((B,C,H,W)\)

Example:

>>> from spyrit.core.meas import HadamSplit2d
>>> from spyrit.core.prep import UnsplitRescale
>>> from spyrit.core.recon import LearnedPGD
>>> import torch

>>> acqu = HadamSplit2d(32, M=400)
>>> prep = UnsplitRescale()
>>> recnet = LearnedPGD(acqu, prep)
>>> x = torch.FloatTensor(10,1,32,32).uniform_(-1, 1)
>>> z = recnet(x)
>>> print(z.shape)
torch.Size([10, 1, 32, 32])