raycond2-cars.sh

#!/bin/bash

#SBATCH -J Cars2                           # Job name
#SBATCH -o Cars2.o                              # Name of stdout output file (%j expands to jobId)
#SBATCH -e Cars2.o                              # Name of stderr output file (%j expands to jobId)
#SBATCH -N 1                                            # Total number of nodes (physical machine) requested 
#SBATCH -n 8                                            # Number of cores requested
#SBATCH --mem=100000                                     # Memory pool (MB)
#SBATCH -t 96:00:00                                     # Run time (hh:mm:ss) 
#SBATCH --partition=cuvl,davis,snavely,gpu
#SBATCH --gres=gpu:2080ti:8                         # gpu:gpu_type:how_many_gpu

# below is the script that specifies all the commands to run
# or you could just add a single command
# e.g. echo "hello world!"
# better to use absolute path

python /share/phoenix/nfs04/S7/emc348/ray-conditioning/train.py --outdir=/share/phoenix/nfs04/S7/emc348/stylegan3/training-runs --data=/share/phoenix/nfs04/S7/emc348/nerf/eg3d/cars_full_params.zip --cfg=raycond2 --gpus=8 --batch=32 --gamma=0.3 --snap=20 --cond=1 --aug=noaug