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KumapowerLIU avatar KumapowerLIU commented on June 3, 2024

Due to the limitation of the experimental environment, I set this parameter to 1 so that multiple sets of comparative experiments can be run. If you want to set it larger, you can change the code details。

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XiaoYangon avatar XiaoYangon commented on June 3, 2024

@wode-czw ,Do you change the batchsize?, How do you change other code details?

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camellia120 avatar camellia120 commented on June 3, 2024

@KumapowerLIU In my experiments, when setting the batch size to 16, the GPU memory increases to 84% (9203MiB) in RTX 2080, but it seems that the GPU utilization is still very low (less than 30%, as same as the batch size setting in 1). Is it possible that the searching and generating process in 32x32 feature maps cause that?
@wode-czw how do u solve the problem u descript?

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Ikhwansong avatar Ikhwansong commented on June 3, 2024

I think so like that. If when we use a 1080ti GPU for training, the GPU can allocates memories of 11GBytes. So that it is sufficient to train with batch size of 4 over.
Why didn't you try?

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