train_vqa_old.sh (1530B)
1 #!/bin/bash 2 # 3 # 4 # Comments starting with #OAR are used by the resource manager if using "oarsub -S" 5 # 6 # Note : quoting style of parameters matters, follow the example 7 # 8 # The job is submitted to the default queue 9 #OAR -q default 10 # Path to the binary to run 11 12 module purge 13 module load conda 14 source activate pytorch 15 module load cuda/10.2 16 module load gcc/7.3.0 17 module load cudnn/7.6-cuda-10.2 18 19 echo python -m mmsrl.train configs/ofa_old_best.py --output_val=outputs/ofa_vqa_old_max35_lr5_val.pkl \ 20 --output_test=outputs/ofa_vqa_old_max35_lr5_test.pkl \ 21 --save_model=models/ofa_vqa_old.bin 22 23 python -m mmsrl.train configs/ofa_old_best.py --output_val=outputs/ofa_vqa_old_max35_lr5_val.pkl \ 24 --output_test=outputs/ofa_vqa_old_max35_lr5_test.pkl \ 25 --save_model=models/ofa_vqa_old.bin 26 27 # oarsub -p "gpu='YES'" -l /gpunum=1,walltime=20:00:00 -t besteffort ./oarscripts/train_vqa_old.sh 28 # oarsub -p "gpu='YES' and mem>80000 and host='nefgpu39.inria.fr'" -l /gpunum=1,walltime=20:00:00 -t besteffort ./oarscripts/train_vqa_old.sh 29 #OAR_JOB_ID=12236582 30 # --unfreeze=\"classifier\" \ 31 32 #ipython --pdb -c "%run -m mmsrl.train configs/ofa_vqa.py \"--ofa_path=ofa_path.replace('vqa_large_best','ofa_large')\" --ofa_unfreeze="all" --learning_rate=1e-4 --output_val=outputs/ofa_vqa_large_val_lr4.pkl --output_test=outputs/ofa_vqa_large_test_lr4.pkl --save_model=models/ofa_vqa_large_lr4.bin"