train_snli.sh (1326B)
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 20 echo python -m mmsrl.train configs/ofa_vqa.py --ofa_path=OFA/checkpoints/snli_ve_large_best.pt \ 21 --output_val=outputs/ofa_snli_val.pkl \ 22 --output_test=outputs/ofa_snli_test.pkl \ 23 --save_model=models/ofa_snli.bin 24 25 python -m mmsrl.train configs/ofa_vqa.py --ofa_path=OFA/checkpoints/snli_ve_large_best.pt \ 26 --output_val=outputs/ofa_snli_val.pkl \ 27 --output_test=outputs/ofa_snli_test.pkl \ 28 --save_model=models/ofa_snli.bin 29 30 # oarsub -p "gpu='YES'" -l /gpunum=1,walltime=20:00:00 -t besteffort ./oarscripts/train_vqa.sh 31 # oarsub -p "gpu='YES' and host='nefgpu47.inria.fr'" -l /gpunum=1,walltime=20:00:00 -t besteffort ./oarscripts/train_snli.sh 32 33 #OAR_JOB_ID=12239573 34 # "--ofa_input='ocr question'" \