Comments (4)
Our model was trained on 32GB V100 GPUs.
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Hi, please refer to this. If the problem still present, please let me know and provide with more details. Thanks!
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Thanks for you reply. In fact, I mean how much memory is enough to train Str2Str? This would help to to choose what GPU or how many GPUs for retraijning the model.
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Well I found the problem is that some multi-chain proteins are included in training, which could lead to an enormous memory cost. If I remove pkl files larger than 1M, it in fact would could consult 6.7 GB memory when batch_size=1.
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Related Issues (7)
- Errors in using pretrained models HOT 1
- src install error HOT 4
- tica plot is not same as Figure S4 HOT 1
- torch.cuda.OutOfMemoryError to infer for a large protein HOT 1
- ValueError: zero-size array to reduction operation minimum which has no identity HOT 5
- Change default hparam for sampling s2011 HOT 1
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