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Runtime error
| #SBATCH --job-name=frozenseg_eval | |
| #SBATCH --output=output/slurm/%j.run.out | |
| #SBATCH --error=output/slurm/%j.run.err | |
| #SBATCH --partition=gpu-a100 | |
| #SBATCH --gres=gpu:1 | |
| #SBATCH --cpus-per-task=16 | |
| #SBATCH --comment=yhx_team | |
| export MODULEPATH="/opt/app/spack/share/spack/modules/linux-centos7-haswell:/opt/app/spack/share/spack/modules/linux-centos7-cascadelake:/usr/share/Modules/modulefiles:/etc/modulefiles:/opt/app/modulefiles" | |
| source /users/cx_xchen/.bashrc_12.1 | |
| export DETECTRON2_DATASETS=/users/cx_xchen/DATASETS/ | |
| export TORCH_DISTRIBUTED_DEBUG=DETAIL | |
| export OMP_NUM_THREADS=1 | |
| export USE_SIMPLE_THREADED_LEVEL3=1 | |
| conda activate frozenseg | |
| configs=( | |
| # "configs/coco/frozenseg/convnext_large_eval_a847.yaml" | |
| # "configs/coco/frozenseg/convnext_large_eval_ade20k.yaml" | |
| # "configs/coco/frozenseg/convnext_large_eval_lvis.yaml" | |
| # "configs/coco/frozenseg/convnext_large_eval_pas21.yaml" | |
| "configs/coco/frozenseg/convnext_large_eval_pc459.yaml" | |
| # "configs/coco/frozenseg/convnext_large_eval_cityscapes.yaml" | |
| # "configs/coco/frozenseg/convnext_large_eval_coco.yaml" | |
| # "configs/coco/frozenseg/convnext_large_eval_mapillary_vistas.yaml" | |
| # configs/coco/frozenseg/convnext_large_eval_bdd_panop.yaml | |
| # configs/coco/frozenseg/convnext_large_eval_bdd_sem.yaml | |
| ) | |
| port=$((10000 + RANDOM % 50000)) | |
| sam=vit_b | |
| path=output/ConvNext-L_${sam}_1x | |
| for config in "${configs[@]}"; do | |
| python train_net.py --eval-only --num-gpus 1 --dist-url tcp://127.0.0.1:$port \ | |
| --config-file $config \ | |
| OUTPUT_DIR $path/$(basename "$config" .yaml) \ | |
| MODEL.WEIGHTS modified_model.pth \ | |
| MODEL.SAM_NAME vit_b \ | |
| MODEL.FROZEN_SEG.CLIP_PRETRAINED_WEIGHTS pretrained_checkpoint/models--laion--CLIP-convnext_large_d_320.laion2B-s29B-b131K-ft-soup/open_clip_pytorch_model.bin \ | |
| TEST.USE_SAM_MASKS False \ | |
| MODEL.FROZEN_SEG.GEOMETRIC_ENSEMBLE_BETA 0.6 | |
| done | |
| ########## with mask ensemble ######## | |
| # for config in "${configs[@]}"; do | |
| # python train_net.py --eval-only --num-gpus 1 --dist-url tcp://127.0.0.1:$port \ | |
| # --config-file $config \ | |
| # OUTPUT_DIR $path/w_maskEnsemble/$(basename "$config" .yaml) \ | |
| # MODEL.WEIGHTS $path/model_final.pth \ | |
| # MODEL.MASK_FORMER.SAM_QUERY_FUSE_LAYER 2 \ | |
| # MODEL.MASK_FORMER.SAM_FEATURE_FUSE_LAYER 0 \ | |
| # MODEL.SAM_NAME vit_b \ | |
| # MODEL.FROZEN_SEG.CLIP_PRETRAINED_WEIGHTS pretrained_checkpoint/models--laion--CLIP-convnext_large_d_320.laion2B-s29B-b131K-ft-soup/open_clip_pytorch_model.bin \ | |
| # TEST.USE_SAM_MASKS True \ | |
| # TEST.PKL_SAM_MODEL_NAME vit_h | |
| # done | |
| ########### test recall ############ | |
| # path=output/Sam_query/ConvNext-L_vit_b_1x | |
| # for config in "${configs[@]}"; do | |
| # srun python train_net.py --eval-only --num-gpus 4 --dist-url tcp://127.0.0.1:$port \ | |
| # --config-file $config \ | |
| # OUTPUT_DIR "output/Ablation/recall_withEverything/$(basename "$config" .yaml)" \ | |
| # MODEL.WEIGHTS "$path/model_final.pth" \ | |
| # TEST.USE_SAM_MASKS True \ | |
| # MODEL.MASK_FORMER.TEST.RECALL_ON True \ | |
| # MODEL.MASK_FORMER.TEST.SEMANTIC_ON False \ | |
| # MODEL.MASK_FORMER.TEST.INSTANCE_ON False \ | |
| # MODEL.MASK_FORMER.TEST.PANOPTIC_ON False \ | |
| # done |