MMSRL

Our Multimodal Semantic Role Labeling model for CONSTRAINT 2022
git clone https://esimon.eu/repos/MMSRL.git
Log | Files | Refs | Submodules | README

generic_features.sh (2787B)

      1 #!/bin/bash
      2 #SBATCH -A lco@gpu
      3 #SBATCH --job-name=mmsrl             # job name
      4 #SBATCH --ntasks=1                   # number of MP tasks
      5 #SBATCH --ntasks-per-node=1          # number of MPI tasks per node
      6 #SBATCH --gres=gpu:1                 # number of GPUs per node
      7 #SBATCH --cpus-per-task=10           # number of cores per tasks
      8 #SBATCH --hint=nomultithread         # we get physical cores not logical
      9 #SBATCH --distribution=block:block   # we pin the tasks on contiguous cores
     10 #SBATCH --time=10:00:00               # maximum execution time (HH:MM:SS)
     11 #SBATCH --output=/gpfswork/rech/lco/url46ht/outputs/generic_features/generic_feature_%j_%x_%A_%a.out  # output file name
     12 #SBATCH --error=/gpfswork/rech/lco/url46ht/outputs/generic_features/generic_feature_%j_%x_%A_%a.err   # error file name
     13 #SBATCH --array=0-17
     14 
     15 
     16 cd $WORK/mmsrl
     17 
     18 module purge
     19 source ~/.bashrc
     20 conda activate pytorch
     21 export DATA_PATH=$WORK/data
     22 export HF_DATASETS_OFFLINE=1 
     23 export TRANSFORMERS_OFFLINE=1
     24 
     25 
     26 base_config=("--features_path='all' --use_sbert=True --use_caption=True --use_entities=True --use_visualbert=True --use_clip=True"
     27              "--features_path=features_frcnn --use_sbert=True --use_caption=True --use_entities=True --use_visualbert=True --use_clip=True"
     28              "--features_path=features_b7 --use_sbert=True --use_caption=True --use_entities=True --use_visualbert=True --use_clip=True"
     29              "--features_path=features_vgg --use_sbert=True --use_caption=True --use_entities=True --use_visualbert=True --use_clip=True"
     30              "--features_path=features_frcnn --use_sbert=True  --use_entities=True --use_visualbert=True --use_clip=True"
     31              "--features_path=features_frcnn --use_sbert=True --use_caption=True --use_visualbert=True --use_clip=True"
     32              "--features_path=features_frcnn --use_sbert=True --use_caption=True --use_entities=True --use_clip=True"
     33              "--features_path=features_frcnn --use_sbert=True --use_caption=True --use_entities=True --use_visualbert=True"
     34              "--features_path=features_frcnn --use_caption=True --use_entities=True --use_visualbert=True --use_clip=True")
     35 
     36 base_name=("all"
     37            "frcnn"
     38            "b7"
     39            "vgg"
     40            "nocaption"
     41            "noentities"
     42            "novisualbert"
     43            "noclip"
     44            "nosbert")
     45 base_pooling=(attention mlp)
     46 
     47 iconfig=$(($SLURM_ARRAY_TASK_ID%9))
     48 ipooling=$(($SLURM_ARRAY_TASK_ID/9%2))
     49 config=${base_config[$iconfig]}
     50 pooling=${base_pooling[$ipooling]}
     51 name=${base_name[$iconfig]}_${pooling}
     52 python -m mmsrl.train configs/generic.py --pooling=$pooling $config --patience=26 --output_val=\"$WORK/outputs/generic_features/val_${name}_${SLURM_ARRAY_TASK_ID}.pkl\" --output_test=\"$WORK/outputs/generic_features/test_${name}_${SLURM_ARRAY_TASK_ID}.pkl\"