MRM-pytorch
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Can't use distributed processing
Thank you for sharing the code! This is my script run.sh:
CUDA_VISIBLE_DEVICES=0,1,2,3 OMP_NUM_THREADS=1 python -m torch.distributed.launch --nproc_per_node=4 --master_port 12345 main_pretrain.py \
--num_workers 10 \
--accum_iter 2 \
--batch_size 128 \
--model mrm \
--norm_pix_loss \
--mask_ratio 0.75 \
--epochs 200 \
--warmup_epochs 40 \
--blr 1.5e-4 --weight_decay 0.05 \
--resume ./MRM/mae_pretrain_vit_base.pth \
--data_path ./MRM \
--output_dir ./MRM \
When I use distributed computing, the program always gets stuck in this position
and never continue. But if I set the graphics card to one, it can train at a very slow speed.
I'm wondering how to deal with it.