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ar4 avatar ar4 commented on August 29, 2024

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ar4 avatar ar4 commented on August 29, 2024

Dear Arnab,

I have modified the code to change __restrict__ to __restrict. The latter is apparently supported by more compilers, so it might resolve your problem. This change is incorporated in release v0.0.7. To update to this version, run pip install -U deepwave.

-Alan

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wslhhh1994 avatar wslhhh1994 commented on August 29, 2024

Thanks for your code sir.
I also got this error on my machine, which has the environmen of pytorch1.0 ,cuda9.0, and gcc 4.9.2 , and I changed the restrict part, but it still didn't work and have the same error of "Segmentation fault (core dumped) " .
In addition, l had read your essay"Seismic Full_waveform iversion using deep learning tools and techniques",the idea in this essay is very advanced. In this essay, you said your implementation is on Tensorflow. Can you upload the code of Tensorflow version? Thanks very much!!!

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ar4 avatar ar4 commented on August 29, 2024

That is sad news, and I am sorry that you have encountered a problem. I am unfortunately still unable to reproduce this problem - the package works well for me. It seems to work on the free Google Colaboratory, if you would like to use it there.

The TensorFlow implementation is in the ancillary files associated with the paper. It is several years old now, however, and so may not run with a recent version of TensorFlow.

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wslhhh1994 avatar wslhhh1994 commented on August 29, 2024

Dear Alan,
I'm appreciated that you can reply so fast. I'll try it on Google Colaboratory.
By the way ,I found it works when I change the device = torch.device('cuda:0') to device = torch.device('cpu') .Maybe there are something wrong with my GPU (I guess ,hah)
Thanks again!

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ar4 avatar ar4 commented on August 29, 2024

I'm glad that you got it to work locally on your CPU, but it would be nice to get it working on your GPU as well. Does PyTorch normally work on your GPU? Did the Deepwave package seem to install without error? As you may know, you can also use a GPU for free on Google Colaboratory, so hopefully that will work for you if you cannot get it to work on your own computer.

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wslhhh1994 avatar wslhhh1994 commented on August 29, 2024

I think pytorch does work on my GPU. When I run simple examples such as a = torch.ones(1,1) print(a.cuda()) and torch.cuda.is_available(), there is no error.
And I will continue to check my environment and code. If I find which makes this problem, I would comment here.
Thanks for your generous help again.

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