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What does Segmentation fault mean?
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- It fails on specific file, what does it mean?
- If some file fails, the whole procedure stop when it's applied on a directory. I think it should run anyway through other files whether if failed on specific file or not
Segmentation fault generally comes from libraries and function calls closer to the system. I am afraid that from the Python level we won't have much to do. That said I experienced that yesterday in a brand new Ubuntu 20.04 machine with GPU with python 3.8 and Pytorch 1.6+cpu version. I started to look into the same issue. Can you tell me a bit about your configuration please?
Hope that we will find a solution easily.
(to give a better perspective, in this colab - https://colab.research.google.com/drive/19O7uvH2bZ-K0DGxnSW3_C7B4tzzvWUsT?usp=sharing the segmentation fault does not occur on same file for which I saw it happening in the machine I mentioned earlier.)
Thank you for your answer. I was working in docker image (rayproject/ray-ml:1.0.0), but not exactly same image from the docker hub as I installed more packages.
I also thought about just showing pip list, but it seems not a good way. If there's any formal way to share configuration, please tell me and I'll show you my configuation.
Furthermore, I think some non-english characters in the code may cause the error. As I'm reading the code from the other person for the first time for refactoring, I cannot say the code itself is perfect and may not cause any syntax, or any unknown error. I'll also tell you If I find something while refactoring that.
Ok great. Thanks. I hope that docly will be helpful for you. If you need to go ahead then clone the colab I linked in my last message and then you can upload some code files and run docly in the colab environment. That is not the optimal solution but until I find a fix that is a good way to go.
Anyway, it is nice to see that you consider docly in a real use case. Always happy to help
Thanks for your support. I'll share any information as it comes out. Hope your app become new standard like black, isort :)