Comments (3)
The arguments in lines are batch size, num_workers for the dataloader. Maybe you can try reducing the num_workers from 8 and see if it works.
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Hi @WurmD
It is possible that you might be running out of memory around the 1200th epoch. How much GPU memory do you have available?
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8GB
Usually when that's the case I see an actual RuntimeError: CUDA error: out of memory
I'll go monitor the GPU RAM usage now
EDIT: Hmm, lack of GPU RAM doesn't seem to be the issue,
It's not breaking now due to the same RuntimeError, and GPU RAM seems to remain steady at 795MiB / 8119MiB during the whole cycle (up to epoch 1700), and on the 2nd cycle it ups to 817MiB / 8119MiB
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Related Issues (14)
- Rename num_epoch_per_cycle to num_cycle_per_epoch HOT 1
- Confused about some folders HOT 7
- some questions about visual feature extractor HOT 5
- Is there any Inference to test on an Image or a video? HOT 2
- NTU split
- What is val*.npy, where does it come from, and how do you determined the sample size of it?
- Extra spaces in examples HOT 1
- [Question] Why did ShiftGCN perform so much better than MS-G3D? HOT 1
- How to replicate ablation test with MS-G3D? HOT 3
- [Questions] Only calling Dataloader once per epoch? Training classifier from scratch at each cycle? HOT 1
- What is gtest_out.npy? HOT 7
- In synse_resources rs10.npy == rs100.npy HOT 2
- What is synse_10_r_unseen_zs.npy and synse_10_r_seen_zs.npy HOT 5
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