jleuschn
commented
3 years ago Hi, thanks a lot for the compliment!
You can try upgrading ODL to the latest master version.
pip install https://github.com/odlgroup/odl/archive/master.zip --upgrade
Just let me know if it does not help. In that case, with which version of odl and pytorch does this error occur?
Best, Johannes
gmzang
Hi First of all, thanks a lot for this excellent library! When I tried the DIPTV demo in the example folder, it returns an error shown below, which seems related to the new version of autograd with ODL. Do you have any hint on how to solve this issue? For example, installing an older version of pytorch (or ODL ) can help?? Thanks in advance.
(base) zan@pc-kw-60:~/projects/dival/dival/examples$ python3 ct_diptv.py DIP: 0%| | 0/17000 [00:00<?, ?it/s] Traceback (most recent call last): File "ct_diptv.py", line 36, in
reco = reconstructor.reconstruct(obs)
File "/home/zan/anaconda3/lib/python3.7/site-packages/dival/reconstructors/reconstructor.py", line 529, in reconstruct
reconstruction = super().reconstruct(observation, out=out)
File "/home/zan/anaconda3/lib/python3.7/site-packages/dival/reconstructors/reconstructor.py", line 198, in reconstruct
reco = self._reconstruct(observation)
File "/home/zan/anaconda3/lib/python3.7/site-packages/dival/reconstructors/dip_ct_reconstructor.py", line 154, in _reconstruct
loss = criterion(self.ray_trafo_module(output),
File "/home/zan/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/zan/anaconda3/lib/python3.7/site-packages/odl/contrib/torch/operator.py", line 397, in forward
results.append(self.op_func(x_flat_xtra[i]))
File "/home/zan/anaconda3/lib/python3.7/site-packages/torch/autograd/function.py", line 149, in call
"Legacy autograd function with non-static forward method is deprecated. "
RuntimeError: Legacy autograd function with non-static forward method is deprecated. Please use new-style autograd function with static forward method. (Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function)