playing with zizgpu slurm

command.sh

sbatch --gres=gpu:1 --partition=ziz-gpu-small slurm.sh

slurm.sh

#!/bin/bash
#SBATCH -A bigbayes                       # Account to be used, e.g. academic, acadrel, aims, bigbayes, opig, oxcsml, oxwasp, rstudent, statgen, statml, visitors
#SBATCH -J job01                          # Job name, can be useful but optional
#SBATCH --time=00:00:30                   # Walltime - run time of just 30 seconds
#SBATCH [email protected]     # set email address to use, change to your own email address instead of "me"
#SBATCH --mail-type=ALL                   # Caution: fine for debug, but not if handling hundreds of jobs!
#SBATCH --output="/data/ziz/agolinsk/slurm_stdout" # To avoid slurm job failing if it can not write to a file in the current directory, specify an output file for standard output
#SBATCH --error="/data/ziz/agolinsk/slurm_stderr" # Same for standard error

echo Starting on `hostname`
source /data/localhost/not-backed-up/agolinsk/utils/miniconda3/bin/activate amci
python /data/ziz/agolinsk/slurm_python.py
nvidia-smi > /data/ziz/agolinsk/slurm_output.txt
echo Finishing

slurm_python.py

# in /data/ziz/agolinsk
import torch
print(torch.cuda.is_available())