Comments (5)
taoranyi
commented on May 5, 2024
1
"pip install jax==0.2.20" may solve your problem
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nahyup
commented on May 5, 2024
1
I think that jaxlib version may cause the segfault.
I suffered same issue.
"pip install jaxlib==0.1.71+cuda111 -f https://storage.googleapis.com/jax-releases/jax_releases.html" may solve your problem
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SuwoongHeo
commented on May 5, 2024
This error seems related to a version mismatch between jax and flax.
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ChikaYan
commented on May 5, 2024
"pip install jax==0.2.20" may solve your problem
Thx! Installing jax==0.2.20 successfully resolves the flax.errors.InvalidRngError.
Sadly, it now causes segmentation fault raised by line 330 of train.py. I'm running on a single GPU with 47GB memory and I've tried setting batch_size = 64, NerfModel.num_coarse_samples = 16, NerfModel.num_fine_samples = 16 in configs/test_local.gin and the segfault still happens, so I suppose it shouldn't be an issue with insufficient memory?
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ChikaYan
commented on May 5, 2024
I think that jaxlib version may cause the segfault. I suffered same issue.
"pip install jaxlib==0.1.71+cuda111 -f https://storage.googleapis.com/jax-releases/jax_releases.html" may solve your problem
Thx a lot! The issue has been resolved.
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Related Issues (20)
- LPIPS metric computation HOT 1
- Hyper-Space Template
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- Some tips on collecting selfie video for hypernerf? HOT 5
- TypeError: broadcast_to requires ndarray or scalar arguments, got <class 'list'> at position 0. HOT 1
- ValueError: Non-hashable static arguments are not supported HOT 1
- Problem with Geman-McClure loss implementation HOT 2
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- using gpu memory but not computation
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