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LaunchScan.sh
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LaunchScan.sh
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#!/bin/bash
#SBATCH --job-name=4p ### Job Name
#SBATCH --partition=gpu ### Quality of Service (like a queue in PBS)
#SBATCH --time=0-18:00:00 ### Wall clock time limit in Days-HH:MM:SS
#SBATCH --nodes=1 ### Node count required for the job
#SBATCH --ntasks-per-node=7 ### Nuber of tasks to be launched per Node
#SBATCH --gres=gpu:1 ### General REServation of gpu:number of gpus
#SBATCH --mem=32G ### Memory
#SBATCH --array=20,50,200,500 ### Arrays for lambda
#SBATCH --output=SlurmOuts/output_4p_%a.txt
#SBATCH --error=SlurmErrors/error_4p_%a.txt
#SBATCH [email protected] ### email for alerts
#SBATCH --mail-type=ALL
PRONG=4
module load cuda/9.0
module load python3
echo $SLURM_NTASKS
export OMP_NUM_THREADS=$SLURM_NTASKS
cd /projects/het/bostdiek/MassAgnostic-JetTaggers
python3 src/models/train_Adversarial.py --prong=$PRONG --lam=${SLURM_ARRAY_TASK_ID}