snca.pytorch
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what would be the best way to do multi-gpu training for snca?
Shall I do nn.parallel.DistributedDataParallel for for both "model" and "lemniscate" and mannually sync each lemniscate memory per epoch?
I think a better solution might be use a single GPU for "lemniscate" memory and calculation, while other GPUs for data parallel "model" part?
I am doing a comics image retrieval task, and find this project very useful. Thank you for you help.
Hi, I am also thinking about the memory issue, how did you deal with it?
I put the memory forward and backward on CPU, when the memory became large. it was a little bit slower but worked well.
model_forward_gpu -> memory_forward_cpu -> loss_cpu -> memory_backward_cpu -> model_backward_gpu
Thanks for sharing!