MMSRL

Our Multimodal Semantic Role Labeling model for CONSTRAINT 2022
git clone https://esimon.eu/repos/MMSRL.git
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ofa_seq2seq.sh (1540B)


      1 #!/bin/bash
      2 #SBATCH -A lco@gpu
      3 #SBATCH -C v100-32g
      4 #SBATCH --job-name=mmsrl             # job name
      5 #SBATCH --ntasks=1                   # number of MP tasks
      6 #SBATCH --ntasks-per-node=1          # number of MPI tasks per node
      7 #SBATCH --gres=gpu:1                 # number of GPUs per node
      8 #SBATCH --cpus-per-task=10           # number of cores per tasks
      9 #SBATCH --hint=nomultithread         # we get physical cores not logical
     10 #SBATCH --distribution=block:block   # we pin the tasks on contiguous cores
     11 #SBATCH --time=10:00:00               # maximum execution time (HH:MM:SS)
     12 #SBATCH --output=/gpfswork/rech/lco/url46ht/outputs/ofa_seq2seq_%j_%x_%A_%a.out  # output file name
     13 #SBATCH --error=/gpfswork/rech/lco/url46ht/outputs/ofa_seq2seq_%j_%x_%A_%a.err   # error file name
     14 #SBATCH --array=0-11
     15 
     16 set -x
     17 
     18 cd $WORK/mmsrl
     19 
     20 module purge
     21 source ~/.bashrc
     22 conda activate pytorch
     23 export DATA_PATH=$WORK/data
     24 
     25 base_config=(""
     26              "--ofa_path=OFA/checkpoints/ofa_base.pt"
     27              "--weight_decay=0.01"
     28              "--ofa_path=OFA/checkpoints/ofa_base.pt --weight_decay=0.01")
     29 base_name=("s2s_vqa_large"
     30            "s2s_base"
     31            "s2s_vqa_large_ddecay"
     32            "s2s_base_ddecay")
     33 iconfig=$(($SLURM_ARRAY_TASK_ID%4))
     34 config=${base_config[$iconfig]}
     35 name=${base_name[$iconfig]}
     36 python -m mmsrl.train configs/ofa_ours.py configs/ofa_vqa.py configs/ofa_seq2seq.py --patience=26 $config --output_val=\"$WORK/outputs/val_${name}_${SLURM_ARRAY_TASK_ID}.pkl\" --output_test=\"$WORK/outputs/test_${name}_${SLURM_ARRAY_TASK_ID}.pkl\"