pytorch autograd depreciated about odl HOT 4 OPEN

I meet the same problem!

from odl.

Just lower your pytorch version to below 1.3, but I am also solving this problem that occurs above version 1.3, and I am researching...

from odl.

Hi,

I am using almost the latest pytorch (1.12.1.post201) and I have no such problem with the binding.
I imagine that part3_learned_reconstruction_pytorch.ipynb can have some outdated code, however
the following code runs as expected:

import matplotlib.pyplot as plt
import numpy as np
import odl
import torch
from odl.contrib.torch import OperatorModule

print(torch.version)

X = odl.uniform_discr([-10, -10], [10, 10], (100,100))
x = odl.phantom.shepp_logan(X)

apart = odl.uniform_partition(0, 2*np.pi, 100)
dpart = odl.uniform_partition(-30, 30, 100)
geometry = odl.tomo.FanBeamGeometry(apart=apart, dpart=dpart, src_radius=15, det_radius=15)
operator = odl.tomo.RayTransform(X, geometry)
pt_op = OperatorModule(operator)
pt_x = torch.from_numpy(x.asarray().reshape(1,1,*x.shape)).cuda()

plt.imshow(pt_op(pt_x).detach().cpu().numpy().squeeze())

from odl.

Hi,

I am using almost the latest pytorch (1.12.1.post201) and I have no such problem with the binding. I imagine that part3_learned_reconstruction_pytorch.ipynb can have some outdated code, however the following code runs as expected:

import matplotlib.pyplot as plt import numpy as np import odl import torch from odl.contrib.torch import OperatorModule

print(torch.version)

X = odl.uniform_discr([-10, -10], [10, 10], (100,100)) x = odl.phantom.shepp_logan(X)

apart = odl.uniform_partition(0, 2*np.pi, 100) dpart = odl.uniform_partition(-30, 30, 100) geometry = odl.tomo.FanBeamGeometry(apart=apart, dpart=dpart, src_radius=15, det_radius=15) operator = odl.tomo.RayTransform(X, geometry) pt_op = OperatorModule(operator) pt_x = torch.from_numpy(x.asarray().reshape(1,1,*x.shape)).cuda()

plt.imshow(pt_op(pt_x).detach().cpu().numpy().squeeze())

I still meet error when use your example.(pytorch==1.10.0,1.8.0)

from odl.