| # Phase 1 - the bound, measured rather than asserted. | |
| # | |
| # Four graph families spanning total correlation from 0.11 to 8.44 bits, where | |
| # the one-pass ceiling V* is known in closed form (V* >= 2^-TC, with equality | |
| # for fixed-edge-count families). The question each run answers: does a trained | |
| # masked diffusion model REACH that ceiling at one pass? | |
| # | |
| # reaches it -> the residual gap is mode (ii), provably not trainable | |
| # falls short -> the shortfall is mode (i), and budget conditioning should | |
| # close it, which the anybudget arm tests directly | |
| # | |
| # Runs on a 5GB MIG slice: these are 15-token sequences and sub-3M-parameter | |
| # models, and that partition bills at 9/min against the H100's 144 - a 16x | |
| # saving that makes the whole phase cost well under one H100-hour. | |
| #SBATCH -J gr1 | |
| #SBATCH -p gpu-a100_1g.5gb | |
| #SBATCH --gres=gpu:a100_1g.5gb:1 | |
| #SBATCH -c 4 | |
| #SBATCH --mem=16g | |
| #SBATCH -t 4:00:00 | |
| #SBATCH -o logs/gr1-%A_%a.out | |
| #SBATCH --array=0-15%8 | |
| source /etc/profile | |
| SCR=/scratch/zt1/project/msml612/user/$USER | |
| module load python/3.10.10 | |
| export PYTHONPATH= | |
| cd $SCR/pcmd/src | |
| FAMS=(matching 2regular tree bipartite); MODES=(mdlm anybudget); SEEDS=(0 1) | |
| I=$SLURM_ARRAY_TASK_ID | |
| F=${FAMS[$((I / 4))]}; M=${MODES[$(((I % 4) / 2))]}; S=${SEEDS[$((I % 2))]} | |
| NAME="gr1-$F-$M-s$S" | |
| echo "=== $NAME ===" | |
| $SCR/hf_env/bin/python -u train_graph.py --family $F --n 6 --mode $M --seed $S \ | |
| --d 256 --layers 6 --heads 8 --bs 256 --steps 30000 --lr 1e-4 --warmup 1000 \ | |
| --n_gen 4096 --gen_bs 512 --out $SCR/pcmd/runs/$NAME | |