#!/bin/bash 
#SBATCH -J name_of_the_job 
#SBATCH -p cpu-high
#SBATCH -N 1                 # one node
#SBATCH -n 1                 # one cpu or gpu
#SBATCH -t 5:00              # maximum time
#SBATCH -o job.out           # will print on the terminal if omitted
#SBATCH -e job.err          

XDG_RUNTIME_DIR=""
port=$(shuf -i8000-9999 -n1)
node=$(hostname -s)
user=$(whoami)
cluster=$(hostname -f | awk -F"." '{print $2}')
clusterurl="10.212.70.128"

export PATH=$PATH:~/.local/bin

# print tunneling instructions jupyter-log
echo -e "
MacOS or linux terminal command to create your ssh tunnel:
ssh -N -L ${port}:${node}:${port} ${user}@${clusterurl}
 
 Here is the MobaXterm info:

 Forwarded port:same as remote port
 Remote server: ${node}
 Remote port: ${port}
 SSH server: ${cluster}.${clusterurl}
 SSH login: $user
 SSH port: 22

 Use a Browser on your local machine to go to:
 localhost:${port} (prefix w/ https:// if using password)

 or copy the URL from below and put there localhost after http:// so it would be something like:
 http://localhost:9499/?token=86c93ba16aaead7529a5da0e5e5a46be7ad8cfea35b2d49f
 "

 # load modules or conda environments here
 # e.g. farnam:
 # module load Python/2.7.13-foss-2016b 
 # conda env activate mx
 # DON'T USE ADDRESS BELOW. 
 # DO USE TOKEN BELOWa
 # module load anaconda3
 # source activate blpenv

#srun -p gpu-high --gres=gpu:2 jupyter lab --no-browser --port=${port} --ip=${node}
jupyter lab --no-browser --port=${port} --ip=${node}