| # Grid 2 — the method vs its ablations vs the baseline, on all three probes. | |
| # | |
| # Objectives | |
| # mdlm ELBO only (standard masked diffusion) | |
| # selfcorrupt ELBO + self-conditioning (component 1) | |
| # coord ELBO + coordination (component 2, the core) | |
| # cmd ELBO + both (full method) | |
| # | |
| # The probes make the claim falsifiable: `copy` has independent answer | |
| # positions, so the method must NOT hurt there; `agree` and `parity` have | |
| # jointly-dependent positions, which is where it must win. | |
| #SBATCH -J g2 | |
| #SBATCH -p gpu-h100 | |
| #SBATCH --gpus=h100:1 | |
| #SBATCH -c 8 | |
| #SBATCH --mem=64g | |
| #SBATCH -t 08:00:00 | |
| #SBATCH -o logs/g2-%A_%a.out | |
| #SBATCH --array=0-23%12 | |
| source /etc/profile | |
| SCR=/scratch/zt1/project/msml612/user/$USER | |
| module load python/3.10.10 | |
| export PYTHONPATH= | |
| PY=$SCR/hf_env/bin/python | |
| cd $SCR/pcmd/src | |
| I=$SLURM_ARRAY_TASK_ID | |
| TASKS=(copy agree parity); OBJ=(mdlm selfcorrupt coord cmd); SEEDS=(0 1) | |
| T=${TASKS[$((I / 8))]} | |
| O=${OBJ[$(((I % 8) / 2))]} | |
| S=${SEEDS[$((I % 2))]} | |
| NAME="g2-$T-$O-s$S" | |
| echo "=== $NAME ===" | |
| $PY train.py --task $T --objective $O --coupling 4 --seed $S \ | |
| --seq_len 128 --n_train 200000 --n_eval 500 --eval_bs 100 \ | |
| --d 384 --layers 6 --heads 6 --bs 64 --steps 20000 --lr 3e-4 \ | |
| --alpha 0.5 --beta 1.0 --group 4 --coord_every 4 --ramp_frac 0.3 \ | |
| --out $SCR/pcmd/runs/$NAME | |