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train_hico_rf_uc.sh
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train_hico_rf_uc.sh
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ulimit -n 4096
set -x
EXP_DIR=exps/hico/hoiclip
for i in 1 2 3 4 5 6 7 8 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9
do
swapon --show
free -h
export NCCL_P2P_LEVEL=NVL
export OMP_NUM_THREADS=8
python -m torch.distributed.launch \
--nproc_per_node=2 \
--master_port $[29403 + i] \
--use_env \
main.py \
--output_dir ${EXP_DIR} \
--dataset_file hico \
--hoi_path data/hico_20160224_det \
--num_obj_classes 80 \
--num_verb_classes 117 \
--backbone resnet50 \
--num_queries 64 \
--dec_layers 3 \
--epochs 90 \
--lr_drop 60 \
--use_nms_filter \
--fix_clip \
--batch_size 8 \
--pretrained params/detr-r50-pre-2branch-hico.pth \
--with_clip_label \
--with_obj_clip_label \
--gradient_accumulation_steps 1 \
--num_workers 8 \
--opt_sched "multiStep" \
--dataset_root GEN \
--model_name HOICLIP \
--del_unseen \
--zero_shot_type rare_first \
--resume ${EXP_DIR}/checkpoint_last.pth \
--verb_pth ./tmp/verb.pth \
--training_free_enhancement_path \
./training_free_ehnahcement/
sleep 120
done