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I am using one GPU to train the model, but it is still using around 10-16G CPU memory. Would you please tell what operations are using so much memory on the CPU.
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Hmm interesting, I have never noticed this before. My guess would be the input preprocessing stuff is using too many threads/memory. This part is handled by the CPU because GPU training is not really the bottleneck (data preprocessing is).
My suggestion would be to take a look at the input preprocessing stuff and see if you can come up with a better way for your specific application.
I am using one GPU to train the model, but it is still using around 10-16G CPU memory. Would you please tell what operations are using so much memory on the CPU.
The text was updated successfully, but these errors were encountered: