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lmxyy avatar lmxyy commented on July 17, 2024

Sorry, could you please tell me which model are you compressing?

Since search_multi.py sometimes may cause a deadlock, I didn't update it for some time. So I do not recommend you use it.
If you need parallel multi-GPU searching, you could manually split the search space with search.py. All you need to do is add additional arguments --split and --remainder. For example, if you need to search the sub-networks for cycleGAN with 2 GPUs, you could use the following commands:

python search.py --dataroot database/horse2zebra/valA \
  --dataset_mode single \
  --restore_G_path logs/cycle_gan/horse2zebra/supernet/checkpoints/latest_net_G.pth \
  --output_path logs/cycle_gan/horse2zebra/supernet/pkls/result0.pkl \
  --ngf 32 --batch_size 32 \
  --config_set channels-32 \
  --real_stat_path real_stat/horse2zebra_B.npz \
  --split 2 --remainder 0

And on the second GPU

python search.py --dataroot database/horse2zebra/valA \
  --dataset_mode single \
  --restore_G_path logs/cycle_gan/horse2zebra/supernet/checkpoints/latest_net_G.pth \
  --output_path logs/cycle_gan/horse2zebra/supernet/pkls/result1.pkl \
  --ngf 32 --batch_size 32 \
  --config_set channels-32 \
  --real_stat_path real_stat/horse2zebra_B.npz \
  --split 2 --remainder 1 --gpu_ids 1

And then you could merge the search results with merge.py:

python merge.py --in_dir logs/cycle_gan/horse2zebra/supernet/pkls --output_path logs/cycle_gan/horse2zebra/supernet

I will try to fix the search_multi.py.

from gan-compression.

techmonsterwang avatar techmonsterwang commented on July 17, 2024

Good solving method, I'll try it! Thanks for the answer!

from gan-compression.

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