| #!/bin/bash | |
| #SBATCH --job-name=se3clf-train | |
| #SBATCH --output=logs/%x-%j.out | |
| #SBATCH --error=logs/%x-%j.err | |
| #SBATCH --nodes=1 | |
| #SBATCH --ntasks=1 | |
| #SBATCH --gres=gpu:4 | |
| #SBATCH --cpus-per-task=16 | |
| #SBATCH --time=24:00:00 | |
| #SBATCH --qos=gp_debug | |
| set -euo pipefail | |
| # --- Adjust these to your MN5 environment --- | |
| # module purge | |
| # module load <python-module> | |
| # module load <cuda-module> | |
| # source /path/to/venv/bin/activate | |
| cd "${SLURM_SUBMIT_DIR}" | |
| mkdir -p logs wandb | |
| export WANDB_MODE=offline | |
| export WANDB_DIR="${SLURM_SUBMIT_DIR}/wandb" | |
| srun python train_classifier.py \ | |
| experiment.num_devices=4 \ | |
| experiment.trainer.strategy=ddp \ | |
| experiment.wandb.offline=true \ | |
| experiment.wandb.dir="${WANDB_DIR}" | |