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model output is NAN for toy dataset #9
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Hi, Thank you for your interest in our work. |
It seems that the nan is caused by softpool, if I disable it things run fine.
|
Hi @jonbakerfish, if you are sure that it is a softpool problem, you can refer to alexandrosstergiou/SoftPool#12 and alexandrosstergiou/adaPool#2. I tried to reproduce this nan issue on 3090, 2080Ti, v100, 2070 Super GPU servers, but failed. 😅 |
Hi @jonbakerfish , I finally found the cause of this problem! When I use the new version The specific reason may need to carefully check the softpool code and discuss with the author, but rolling back the softpool version is a quick solution to this problem. git clone https://github.com/alexandrosstergiou/SoftPool.git
cd SoftPool
git checkout 2d2ec6d # rollback to 2d2ec6dca10b7683ffd41061a27910d67816bfa5
cd pytorch
make install
--- (optional) ---
make test I hope you can help to check it, if you have any questions, please contact me again. |
Just for reference: |
Hi @L-Reichardt, thank you for your feedback. The temporary plan of rolling back to 2d2ec6d has been verified by several developers, and there should be no problem with the data set used in this project. Disabling Softpool may cause a slight decrease in performance, as demonstrated by the ablation experiments in the paper I hope you can confirm two questions. First, whether the installation was successfully replaced with the new version after rolling back the version. Second, your own data is clean and does not contain nan. |
@MaxChanger my bad, you are correct. Recently I updated to a newer SoftPool version in order to use PyTorch 1.13.1, but forgot about it. |
@L-Reichardt Great to hear that 🙃 |
Hi, I run the
infer.py
script with the toy dataset. For some frames, theself.model
's outputs (proj_output
,last_feature
) are NaN arrays. Why?The text was updated successfully, but these errors were encountered: