From c54ddb88b532be28ca3096e21de405d90163ecfa Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Mon, 29 Jun 2026 12:04:47 -0500 Subject: Package full RRoG GNN project --- .gitignore | 13 +- README.md | 150 ++ .../ogbg-molhiv_fixed-rrog_T3_ns3_diagnostics.csv | 18 + .../ogbg-molhiv_fixed-rrog_T3_ns3_diagnostics.md | 47 + diag/aggregate.py | 5 +- diag/cin_color.py | 3 +- diag/esan_color.py | 3 +- diag/eval_rec_ttc.py | 113 ++ diag/lyap.py | 24 +- diag/ptrm_color.py | 33 +- diag/run_archA.sh | 5 +- diag/run_archB.sh | 8 +- diag/run_color.sh | 13 +- diag/run_le.sh | 6 +- diag/run_pe.sh | 11 +- diag/run_pe2.sh | 6 +- diag/run_pe3.sh | 8 +- diag/run_pna.sh | 3 +- diag/run_rec.sh | 13 +- diag/run_seeds.sh | 7 +- diag/train_color.py | 142 +- diag/train_cycle.py | 11 +- diag/train_rec.py | 423 +++- logs/local_gpu3_act_ablation_20260624_102042.log | 39 + ...cal_gpu3_act_ablation_retry_20260624_102233.log | 2105 ++++++++++++++++++++ logs/ogbg-molbace_0.log | 683 +++++++ 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runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0_ns8_test.json create mode 100644 runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0_ns8_test_adaptive.json create mode 100644 runs/zinc_gine_after_ogb.log create mode 100644 scripts/analyze_ogb_hiv_log.py create mode 100755 scripts/collect_results.sh create mode 100755 scripts/run_ogb_act_task.sh create mode 100755 scripts/run_ogb_act_two_gpu.sh create mode 100755 scripts/run_ogb_mol_all_tasks.sh create mode 100755 scripts/run_ogb_mol_task_full.sh create mode 100755 scripts/run_smoke.sh create mode 100755 scripts/run_two_a6000.sh create mode 100755 scripts/run_zinc_cycle56_full.sh create mode 100755 scripts/setup_and_run_two_a6000.sh create mode 100755 scripts/setup_env.sh create mode 100644 summaries/ogb_graphprop.md create mode 100644 summaries/zinc_cycle56.md diff --git a/.gitignore b/.gitignore index 1a9b622..64601e1 100644 --- a/.gitignore +++ b/.gitignore @@ -1,10 +1,13 @@ __pycache__/ *.py[cod] - .venv/ -venv/ - data/ -runs/ - +*.pt +*.pth +ckpt_*.pt +runs/ckpt_*.pt +runs/*.pt +runs/*.pth +logs/*.tmp +summaries/*.tmp .DS_Store diff --git a/README.md b/README.md new file mode 100644 index 0000000..2bbf938 --- /dev/null +++ b/README.md @@ -0,0 +1,150 @@ +# RRoG-GNN + +This is the working repo for RRoG/TRM-on-GNN experiments. It contains the +current experiment runner, diagnostic prototypes, paper references, scripts, and +tracked JSON/log/summary outputs. + +Core rule: + +```text +view/graph aggregation happens once; recursive compute is edge-free hidden-state refinement. +``` + +The main reported table is: + +```text +Task x Backbone -> classic baseline +Task x Backbone x fixed-RRoG -> delta against the matching classic row +``` + +`classic` is the non-RRoG baseline for every backbone: `T=0`, `n_sup=1`. + +## One-command Run On 2x A6000 + +On a clean machine with two visible GPUs: + +```bash +git clone git@github.com:YurenHao0426/rrog.git +cd rrog +./scripts/setup_and_run_two_a6000.sh +``` + +Defaults: + +- GPU0: `zinc-cycle56` over 17 backbones, `classic + fixed-rrog` +- GPU1: `ogbg-molhiv` over 17 backbones, `classic + fixed-rrog` +- Results: `runs/*.json` +- Logs: `logs/*.log` +- Summaries: `summaries/*.md` + +If the environment already has compatible `torch`, `torch_geometric`, and `ogb`: + +```bash +SKIP_SETUP=1 ./scripts/setup_and_run_two_a6000.sh +``` + +To override CUDA wheel index during setup: + +```bash +TORCH_INDEX_URL=https://download.pytorch.org/whl/cu121 ./scripts/setup_env.sh +``` + +## Common Commands + +Smoke test: + +```bash +./scripts/setup_env.sh +DEVICE=cuda:0 ./scripts/run_smoke.sh +``` + +Run the paired ZINC matrix only: + +```bash +DEVICE=cuda:0 EPOCHS=200 ./scripts/run_zinc_cycle56_full.sh +``` + +Run one OGB molecular task: + +```bash +TASK=ogbg-molhiv DEVICE=cuda:1 EPOCHS=100 ./scripts/run_ogb_mol_task_full.sh +``` + +Run the same OGB task with the lighter fixed recursion used by the ZINC sweep: + +```bash +TASK=ogbg-molhiv DEVICE=cuda:1 EPOCHS=100 FIXED_T=1 FIXED_NS=3 ./scripts/run_ogb_mol_task_full.sh +``` + +Run all selected OGB molecular tasks serially on one GPU: + +```bash +DEVICE=cuda:1 ./scripts/run_ogb_mol_all_tasks.sh +``` + +Run the corrected stream-ACT sweep on two GPUs: + +```bash +EPOCHS=100 SEEDS=0 ./scripts/run_ogb_act_two_gpu.sh +``` + +Defaults: + +- GPU0: `ogbg-molhiv ogbg-molbbbp ogbg-molsider ogbg-molbace` +- GPU1: `ogbg-molesol ogbg-mollipo ogbg-moltox21 ogbg-molclintox` +- Every task runs all 17 backbones. +- ACT config: `T=1`, `n_sup=3`, `halt_max=8`, `halt_min=2`, `halt_target=loss`, `loss_threshold=0.2`, `halt_exploration=0.1`, `lam_q=0.1`, `q_warmup=0`, `act_train_mode=stream`. + +Optional ACT variants: + +```bash +# Add FreeSolv as a separate regression stress test. +TASKS_GPU0="ogbg-molfreesolv" TASKS_GPU1="" ./scripts/run_ogb_act_two_gpu.sh + +# Classification-only exact-halt target. +TASKS_GPU0="ogbg-molhiv ogbg-molbbbp ogbg-molsider" \ +TASKS_GPU1="ogbg-molbace ogbg-moltox21 ogbg-molclintox" \ +HALT_TARGET=exact ./scripts/run_ogb_act_two_gpu.sh + +# More robust but longer seed sweep. +SEEDS="0 1 2" ./scripts/run_ogb_act_two_gpu.sh +``` + +Collect summaries: + +```bash +./scripts/collect_results.sh +``` + +## Backbones + +The implemented 2D view/backbone list is shared across ZINC and OGB: + +```text +gin, gine, gcn, graphsage, gatv2, graphconv, transformer, pna, +gen, film, resgated, tag, sgc, cheb, arma, mf, appnp +``` + +For ZINC `gine`, there are no bond features, so GINE uses a learned constant edge token. +For OGB molecular tasks, GINE and edge-aware backbones use OGB bond encodings. + +## Notes + +- Runs are resumable at the cell level: scripts skip existing expected JSON files. +- ZINC cycle-count cache is generated under `data/cycle_cache`. +- OGB datasets are downloaded under `data/ogb`. +- Override data/runs locations with `RROG_DATA_DIR` and `RROG_RUNS_DIR`. +- Large artifacts are intentionally not versioned in Git: `data/`, checkpoints, + `*.pt`, and `*.pth` are ignored. Use external storage or Git LFS if those need + to be shared. + +## Upload Results + +After a remote machine finishes: + +```bash +git pull +git add -f runs/*.json logs/*.log summaries/*.md +git commit -m "Add stream ACT OGB results" +git push +``` diff --git a/analysis/ogbg-molhiv_fixed-rrog_T3_ns3_diagnostics.csv b/analysis/ogbg-molhiv_fixed-rrog_T3_ns3_diagnostics.csv new file mode 100644 index 0000000..8d8ff16 --- /dev/null +++ b/analysis/ogbg-molhiv_fixed-rrog_T3_ns3_diagnostics.csv @@ -0,0 +1,18 @@ +view,metric,base_ep,base_val,base_test,cand_ep,cand_val,cand_test,val_delta,test_delta,base_curve_best_ep,base_final_gap,cand_curve_best_ep,cand_curve_final_ep,cand_final_gap,cand_late_slope,cand_range,labels +appnp,rocauc,30,0.7674851190476192,0.7000000000000001,30,0.7203422006662747,0.682502558952471,-0.047142918381344434,-0.01749744104752904,30,0.04686000000000001,30,100,0.047719999999999985,0.0032600000000000406,0.07535000000000003,"val_and_test_down,fixed_val_lags_classic,late_collapse" +arma,rocauc,70,0.7872115667254557,0.7296336352575368,90,0.7926495443856555,0.7317541860599857,0.005437977660199822,0.002120550802448884,70,0.0020499999999999963,90,100,0.0011499999999999844,-0.0011499999999999844,0.13578999999999997,"positive_or_tie,maybe_undertrained" +cheb,rocauc,60,0.783120835782873,0.7281735838853589,40,0.7734757740544776,0.7425713126943356,-0.009645061728395299,0.014397728808976717,60,0.021220000000000017,40,100,0.03462999999999994,-0.0027800000000000047,0.050449999999999995,"test_up_val_down,late_collapse" +film,rocauc,20,0.7921535126396236,0.7842136773595473,30,0.7633101851851851,0.7727785395623709,-0.028843327454438517,-0.01143513779717642,20,0.043240000000000056,30,100,0.05358000000000007,-0.003670000000000062,0.07297000000000009,"val_and_test_down,fixed_val_lags_classic,late_collapse" +gatv2,rocauc,20,0.7834576474622771,0.75625253481141,20,0.7835464432686655,0.746617354525966,8.879580638843088e-05,-0.009635180285443967,20,0.040959999999999996,20,100,0.09077000000000002,-0.0033800000000000496,0.09077000000000002,"val_up_test_down,late_collapse" +gcn,rocauc,30,0.7754323437193807,0.719778288495336,40,0.7454683519498334,0.7482879159504818,-0.029963991769547338,0.028509627455145847,30,0.04236999999999991,40,100,0.010009999999999963,-0.006759999999999988,0.10924999999999996,"test_up_val_down,fixed_val_lags_classic" +gen,rocauc,30,0.7530159954928474,0.7313524788041483,60,0.8127970066627475,0.7631375654222755,0.05978101116990009,0.03178508661812718,30,0.06394,60,100,0.07395999999999991,-0.015559999999999907,0.11785999999999996,"positive_or_tie,late_collapse" +gin,rocauc,40,0.816746889084852,0.7723980764402558,30,0.7523760533019792,0.7324378609088626,-0.06437083578287284,-0.03996021553139317,40,0.032930000000000015,30,100,0.013860000000000094,0.0015699999999999603,0.09743000000000002,"val_and_test_down,fixed_val_lags_classic" +gine,rocauc,70,0.7942448069762884,0.7445141852874717,40,0.7574588477366255,0.7400818864790746,-0.03678595923966288,-0.004432298808397128,70,0.008459999999999912,40,100,0.02404000000000006,-0.005790000000000073,0.14568000000000003,"val_and_test_down,fixed_val_lags_classic" +graphconv,rocauc,80,0.7706618655692731,0.7108113327796983,80,0.7712528169704094,0.6979180748952278,0.0005909514011362971,-0.012893257884470488,80,0.009280000000000066,80,100,0.004809999999999981,-9.999999999998899e-05,0.07740000000000002,val_up_test_down +graphsage,rocauc,40,0.7968596903782088,0.7625118291199134,20,0.7586759626690183,0.7641070704339598,-0.03818372770919054,0.001595241314046314,40,0.054950000000000054,20,100,0.022279999999999966,-0.008159999999999945,0.08989000000000003,"test_up_val_down,fixed_val_lags_classic" +mf,rocauc,60,0.784538506760729,0.7073504702678692,50,0.7930782137958065,0.7216728789663763,0.008539707035077448,0.014322408698507094,60,0.015589999999999993,50,100,0.04754000000000003,0.00019000000000002348,0.08803000000000005,"positive_or_tie,late_collapse" +pna,rocauc,60,0.7779523074661963,0.7647926765677203,60,0.7890395355673133,0.7629792000618011,0.011087228101117064,-0.0018134765059192315,60,0.05793999999999999,60,100,0.022619999999999973,-0.0008000000000000229,0.19358999999999993,val_up_test_down +resgated,rocauc,80,0.8143738977072311,0.7241738928909403,80,0.8173500881834216,0.7054809865003185,0.0029761904761904656,-0.01869290639062171,80,0.006010000000000071,80,100,0.014419999999999988,0.0013400000000000079,0.13631000000000004,val_up_test_down +sgc,rocauc,80,0.7478597148736037,0.7019100407501111,50,0.7481720311581422,0.7177311265184728,0.00031231628453853855,0.01582108576836172,80,0.01100000000000001,50,100,0.023460000000000036,-0.006759999999999988,0.06252000000000002,positive_or_tie +tag,rocauc,70,0.7528292181069958,0.7255354487340427,70,0.7803834754066236,0.7351764228741382,0.027554257299627793,0.00964097414009546,70,0.009939999999999949,70,100,0.010239999999999916,-0.0008799999999999919,0.17215999999999998,positive_or_tie +transformer,rocauc,30,0.7617332941407015,0.7547248884682979,40,0.8088103811483441,0.7413024585256572,0.04707708700764268,-0.013422429942640646,30,0.04059999999999997,40,100,0.09591000000000005,-0.0031600000000000517,0.10176000000000007,"val_up_test_down,late_collapse" diff --git a/analysis/ogbg-molhiv_fixed-rrog_T3_ns3_diagnostics.md b/analysis/ogbg-molhiv_fixed-rrog_T3_ns3_diagnostics.md new file mode 100644 index 0000000..0379e0e --- /dev/null +++ b/analysis/ogbg-molhiv_fixed-rrog_T3_ns3_diagnostics.md @@ -0,0 +1,47 @@ +# ogbg-molhiv fixed-rrog T=3 ns=3 diagnostics + +- rows: 17 +- val+test positive: 5 +- val up, test down: 5 +- val down, test up: 3 +- val+test down: 4 +- maybe undertrained: 1 +- late collapse: 7 + +- mean val delta: -0.0054 +- mean test delta: -0.0007 +- val/test delta corr: 0.4504 + +## Label Counts + +| label | n | +| --- | --- | +| fixed_val_lags_classic | 6 | +| late_collapse | 7 | +| maybe_undertrained | 1 | +| positive_or_tie | 5 | +| test_up_val_down | 3 | +| val_and_test_down | 4 | +| val_up_test_down | 5 | + +## Per-Backbone Rows + +| view | base_val | cand_val | d_val | base_test | cand_test | d_test | cand_ep | cand_final_gap | labels | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| appnp | 0.7675 | 0.7203 | -0.0471 | 0.7000 | 0.6825 | -0.0175 | 30 | 0.0477 | val_and_test_down,fixed_val_lags_classic,late_collapse | +| arma | 0.7872 | 0.7926 | 0.0054 | 0.7296 | 0.7318 | 0.0021 | 90 | 0.0011 | positive_or_tie,maybe_undertrained | +| cheb | 0.7831 | 0.7735 | -0.0096 | 0.7282 | 0.7426 | 0.0144 | 40 | 0.0346 | test_up_val_down,late_collapse | +| film | 0.7922 | 0.7633 | -0.0288 | 0.7842 | 0.7728 | -0.0114 | 30 | 0.0536 | val_and_test_down,fixed_val_lags_classic,late_collapse | +| gatv2 | 0.7835 | 0.7835 | 0.0001 | 0.7563 | 0.7466 | -0.0096 | 20 | 0.0908 | val_up_test_down,late_collapse | +| gcn | 0.7754 | 0.7455 | -0.0300 | 0.7198 | 0.7483 | 0.0285 | 40 | 0.0100 | test_up_val_down,fixed_val_lags_classic | +| gen | 0.7530 | 0.8128 | 0.0598 | 0.7314 | 0.7631 | 0.0318 | 60 | 0.0740 | positive_or_tie,late_collapse | +| gin | 0.8167 | 0.7524 | -0.0644 | 0.7724 | 0.7324 | -0.0400 | 30 | 0.0139 | val_and_test_down,fixed_val_lags_classic | +| gine | 0.7942 | 0.7575 | -0.0368 | 0.7445 | 0.7401 | -0.0044 | 40 | 0.0240 | val_and_test_down,fixed_val_lags_classic | +| graphconv | 0.7707 | 0.7713 | 0.0006 | 0.7108 | 0.6979 | -0.0129 | 80 | 0.0048 | val_up_test_down | +| graphsage | 0.7969 | 0.7587 | -0.0382 | 0.7625 | 0.7641 | 0.0016 | 20 | 0.0223 | test_up_val_down,fixed_val_lags_classic | +| mf | 0.7845 | 0.7931 | 0.0085 | 0.7074 | 0.7217 | 0.0143 | 50 | 0.0475 | positive_or_tie,late_collapse | +| pna | 0.7780 | 0.7890 | 0.0111 | 0.7648 | 0.7630 | -0.0018 | 60 | 0.0226 | val_up_test_down | +| resgated | 0.8144 | 0.8174 | 0.0030 | 0.7242 | 0.7055 | -0.0187 | 80 | 0.0144 | val_up_test_down | +| sgc | 0.7479 | 0.7482 | 0.0003 | 0.7019 | 0.7177 | 0.0158 | 50 | 0.0235 | positive_or_tie | +| tag | 0.7528 | 0.7804 | 0.0276 | 0.7255 | 0.7352 | 0.0096 | 70 | 0.0102 | positive_or_tie | +| transformer | 0.7617 | 0.8088 | 0.0471 | 0.7547 | 0.7413 | -0.0134 | 40 | 0.0959 | val_up_test_down,late_collapse | diff --git a/diag/aggregate.py b/diag/aggregate.py index b0f737a..4ded30f 100644 --- a/diag/aggregate.py +++ b/diag/aggregate.py @@ -1,4 +1,4 @@ -"""Aggregate multi-seed coloring results -> mean+/-std per (grad_mode, pe, contract).""" +"""Aggregate multi-seed coloring results -> mean+/-std per architecture/config.""" import glob, json import numpy as np from collections import defaultdict @@ -22,7 +22,8 @@ def load(pat): def key(d): - return (d.get('conv', 'gin'), d.get('pe'), d.get('grad_mode'), 'ctr' if d.get('contract') else '-') + return (d.get('arch', 'legacy'), d.get('conv', 'gin'), d.get('pe'), + d.get('grad_mode'), 'ctr' if d.get('contract') else '-') solve, le, ml = defaultdict(list), defaultdict(list), defaultdict(list) diff --git a/diag/cin_color.py b/diag/cin_color.py index 324215f..53ed158 100644 --- a/diag/cin_color.py +++ b/diag/cin_color.py @@ -131,7 +131,8 @@ def main(): print(f"[cin/{args.grad_mode}] solve={best:.3f} LE AUROC={auc:.3f} mean_lam={lams.mean():+.3f} " f"passK={passk/n:.3f} lamsel={lamsel/n:.3f} ({time.time()-t0:.0f}s)") base = f"cin_{args.grad_mode}_none_n50_k3_p0.2_T3_ns3_s{args.seed}" - com = {'conv': 'cin', 'pe': 'none', 'grad_mode': args.grad_mode, 'contract': False, 'seed': args.seed} + com = {'conv': 'cin', 'pe': 'none', 'grad_mode': args.grad_mode, 'contract': False, + 'seed': args.seed, 'arch': 'rrog_once_agg_node_compute'} json.dump({**com, 'solve_rate': best}, open(os.path.join(OUT, f"color_{base}.json"), 'w')) json.dump({**com, 'auroc': float(auc), 'mean_lam': float(lams.mean())}, open(os.path.join(OUT, f"le_color_{base}.json"), 'w')) json.dump({**com, 'det': 1 - float(fails.mean()), diff --git a/diag/esan_color.py b/diag/esan_color.py index 7be050c..b283641 100644 --- a/diag/esan_color.py +++ b/diag/esan_color.py @@ -131,7 +131,8 @@ def main(): print(f"[esan/{args.grad_mode}] solve={best:.3f} LE AUROC={auc:.3f} mean_lam={lams.mean():+.3f} " f"passK={passk/n:.3f} lamsel={lamsel/n:.3f} ({time.time()-t0:.0f}s)") base = f"esan_{args.grad_mode}_none_n50_k3_p0.2_T3_ns3_s{args.seed}" - com = {'conv': 'esan', 'pe': 'none', 'grad_mode': args.grad_mode, 'contract': False, 'seed': args.seed} + com = {'conv': 'esan', 'pe': 'none', 'grad_mode': args.grad_mode, 'contract': False, + 'seed': args.seed, 'arch': 'rrog_once_agg_node_compute'} json.dump({**com, 'solve_rate': best}, open(os.path.join(OUT, f"color_{base}.json"), 'w')) json.dump({**com, 'auroc': float(auc), 'mean_lam': float(lams.mean())}, open(os.path.join(OUT, f"le_color_{base}.json"), 'w')) diff --git a/diag/eval_rec_ttc.py b/diag/eval_rec_ttc.py new file mode 100644 index 0000000..e0e789e --- /dev/null +++ b/diag/eval_rec_ttc.py @@ -0,0 +1,113 @@ +"""Evaluate deterministic test-time compute for RRoG/TRM-on-GNN checkpoints. + +Loads a trained ``diag/train_rec.py`` checkpoint, overrides ``model.T`` at eval time, +and reports raw MAE on ZINC cycle-count. This separates training-time T from +test-time recursion depth. + +Run: + PYTHONPATH=/home/yurenh2/rrog python3 diag/eval_rec_ttc.py \ + --ckpt runs/ckpt_rec_rrog_full_sig0.0_K1_bestq_T1_ns3_s0.pt --eval_Ts 0 1 2 3 5 8 +""" +import argparse +import json +import os + +import torch + +from diag.train_rec import RecGIN, evaluate, evaluate_trace, loader +from diag.train_cycle import prepare + +OUT = '/home/yurenh2/rrog/runs' + + +def load_model(ckpt, dev): + ck = torch.load(ckpt, weights_only=False, map_location='cpu') + cfg = ck['cfg'] + model = RecGIN( + cfg['n_atom'], + cfg['hidden'], + cfg['T'], + cfg['n_sup'], + sigma=0.0, + grad_mode=cfg.get('grad_mode', 'full'), + agg_layers=cfg.get('agg_layers', 5), + compute_layers=cfg.get('compute_layers', 2), + ).to(dev) + model.load_state_dict(ck['state']) + model.eval() + return model, ck + + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument('--ckpt', required=True) + ap.add_argument('--eval_Ts', type=int, nargs='+', default=[0, 1, 2, 3, 5, 8]) + ap.add_argument('--eval_n_sup', type=int, default=None) + ap.add_argument('--adaptive', action='store_true', + help='choose the first trace step with q_halt > 0, otherwise the last step') + ap.add_argument('--bs', type=int, default=256) + ap.add_argument('--split', choices=['val', 'test'], default='test') + args = ap.parse_args() + + dev = 'cuda' if torch.cuda.is_available() else 'cpu' + model, ck = load_model(args.ckpt, dev) + cfg = ck['cfg'] + ymu, ysd = ck['ymu'], ck['ysd'] + + recs = prepare(args.split) + for r in recs: + r['y'] = (r['y'] - ymu) / ysd + ld = loader(recs, args.bs, False) + + original_T = model.T + original_n_sup = model.n_sup + if args.eval_n_sup is not None: + model.n_sup = args.eval_n_sup + elif args.adaptive and cfg.get('act'): + model.n_sup = cfg.get('halt_max_steps', cfg['n_sup']) + eval_n_sup_used = model.n_sup + + rows = [] + print(f"ckpt={os.path.basename(args.ckpt)} train_T={cfg['T']} train_n_sup={cfg['n_sup']} split={args.split} adaptive={args.adaptive}") + print(f"{'T_eval':>6} {'n_sup':>6} {'mae_c5':>10} {'mae_c6':>10} {'sum':>10} {'avg_steps':>10}") + for T in args.eval_Ts: + model.T = T + if args.adaptive: + mae, avg_steps = evaluate_trace(model, ld, dev, ymu, ysd, model.n_sup, adaptive=True) + else: + mae, _ = evaluate(model, ld, dev, ymu, ysd, K=1, select='none') + avg_steps = float(model.n_sup) + row = { + 'T_eval': T, + 'n_sup_eval': model.n_sup, + 'adaptive': args.adaptive, + 'avg_steps': avg_steps, + 'mae': mae, + 'mae_sum': float(sum(mae)), + } + rows.append(row) + print(f"{T:6d} {model.n_sup:6d} {mae[0]:10.4f} {mae[1]:10.4f} {sum(mae):10.4f} {avg_steps:10.2f}") + + model.T = original_T + model.n_sup = original_n_sup + + os.makedirs(OUT, exist_ok=True) + base = os.path.basename(args.ckpt).replace('ckpt_', '').replace('.pt', '') + out = { + 'ckpt': args.ckpt, + 'split': args.split, + 'train_T': cfg['T'], + 'train_n_sup': cfg['n_sup'], + 'eval_n_sup': eval_n_sup_used, + 'adaptive': args.adaptive, + 'rows': rows, + } + suffix = "_adaptive" if args.adaptive else "" + fp = os.path.join(OUT, f"ttc_{base}_ns{out['eval_n_sup']}_{args.split}{suffix}.json") + with open(fp, 'w') as f: + json.dump(out, f, indent=2) + print("wrote", fp) + + +if __name__ == '__main__': + main() diff --git a/diag/lyap.py b/diag/lyap.py index 93b90bf..e676568 100644 --- a/diag/lyap.py +++ b/diag/lyap.py @@ -1,12 +1,12 @@ """LE diagnostic for the recursive (TRM-ish) GNN — ports the flossing finding to graphs. -Per-graph top Lyapunov exponent lambda1 of the recursion z <- block(z+h0), via Benettin +Per-graph top Lyapunov exponent lambda1 of the edge-free recursion z <- block(z, ctx), via Benettin power-iteration on a single tangent vector (JVP + renormalize, accumulate log-growth) over the model's n_sup*T recursion steps. Bucket graphs by success/failure (rounded ring counts exact) and compare lambda1 distributions + AUROC(fail | lambda1) — mirroring plot_trm_lyap_hist.py. Hypothesis: failed graphs are MORE chaotic (higher lambda1). -Run: PYTHONPATH=/home/yurenh2/rrog python3 diag/lyap.py --ckpt runs/ckpt_rec_full_..._s0.pt +Run: PYTHONPATH=/home/yurenh2/rrog python3 diag/lyap.py --ckpt runs/ckpt_rec_rrog_full_..._s0.pt """ import argparse import numpy as np @@ -21,18 +21,19 @@ except Exception: def build(ck, dev): c = ck['cfg'] - m = RecGIN(c['n_atom'], c['hidden'], c['T'], c['n_sup'], 0.0, grad_mode=c['grad_mode']).to(dev) + m = RecGIN(c['n_atom'], c['hidden'], c['T'], c['n_sup'], 0.0, grad_mode=c['grad_mode'], + agg_layers=c.get('agg_layers', 1), compute_layers=c.get('compute_layers', 2)).to(dev) m.load_state_dict(ck['state']); m.eval() return m, c def lyap1(model, x, ei, n_steps, dev, seed=0): g = torch.Generator(device=dev).manual_seed(seed) - h0 = model.emb(x).detach() - z = torch.zeros_like(h0) - v = torch.randn(h0.shape, generator=g, device=dev); v = v / (v.norm() + 1e-12) + ctx = model.aggregate(x, ei).detach() + z = ctx.detach() + v = torch.randn(ctx.shape, generator=g, device=dev); v = v / (v.norm() + 1e-12) def step_fn(zz): - return model.block(zz + h0, ei) + return model.block(zz, ctx) lam = 0.0 for _ in range(n_steps): z_next, Jv = torch.autograd.functional.jvp(step_fn, z, v) @@ -72,10 +73,13 @@ def main(): lams, fails = np.array(lams), np.array(fails) s, f = lams[fails == 0], lams[fails == 1] auc = (roc_auc_score(fails, lams) if roc_auc_score and len(s) and len(f) else float('nan')) + sm, ss = (s.mean(), s.std()) if len(s) else (float('nan'), float('nan')) + fm, fs = (f.mean(), f.std()) if len(f) else (float('nan'), float('nan')) + sep = fm - sm if len(s) and len(f) else float('nan') print(f"[{cfg['grad_mode']}] n={len(lams)} fail_rate={fails.mean():.2f} | " - f"lambda1 SUCC mean {s.mean():+.4f} std {s.std():.4f} (n={len(s)}) | " - f"FAIL mean {f.mean():+.4f} std {f.std():.4f} (n={len(f)}) | " - f"sep(fail-succ)={f.mean()-s.mean() if len(s) and len(f) else float('nan'):+.4f} | " + f"lambda1 SUCC mean {sm:+.4f} std {ss:.4f} (n={len(s)}) | " + f"FAIL mean {fm:+.4f} std {fs:.4f} (n={len(f)}) | " + f"sep(fail-succ)={sep:+.4f} | " f"AUROC(fail|lambda1)={auc:.3f} | mean_lambda1={lams.mean():+.4f}") diff --git a/diag/ptrm_color.py b/diag/ptrm_color.py index 4004297..b24097f 100644 --- a/diag/ptrm_color.py +++ b/diag/ptrm_color.py @@ -3,7 +3,7 @@ deterministic / pass@K (conflict-min, ground truth) / lambda-select (min lambda1) / random. -Run: PYTHONPATH=/home/yurenh2/rrog python3 diag/ptrm_color.py --ckpt runs/ckpt_color_full_...pt +Run: PYTHONPATH=/home/yurenh2/rrog python3 diag/ptrm_color.py --ckpt runs/ckpt_color_rrog_trm_gin_full_...pt """ import argparse, json, os import numpy as np @@ -18,20 +18,24 @@ OUT = '/home/yurenh2/rrog/runs' def rollout(model, xin, ei, sigma, n_sup, T, dev, seed): gen = torch.Generator(device=dev).manual_seed(seed) - h0 = model.lin_in(xin) - z = torch.zeros_like(h0) - v = torch.randn(h0.shape, generator=gen, device=dev); v = v / (v.norm() + 1e-12) - def step(zz): - return model.block(zz + h0, ei) + ctx = model.aggregate(xin, ei) + y, z = ctx, torch.zeros_like(ctx) + state = torch.cat([y, z], dim=-1) + v = torch.randn(state.shape, generator=gen, device=dev); v = v / (v.norm() + 1e-12) + def step(ss): + yy, zz = ss.chunk(2, dim=-1) + yy, zz = model.recurse(yy, zz, ctx, noise=False) + return torch.cat([yy, zz], dim=-1) lam = 0.0 for _ in range(n_sup * T): - z_det, Jv = torch.autograd.functional.jvp(step, z, v) + state_det, Jv = torch.autograd.functional.jvp(step, state, v) nv = Jv.norm(); lam += torch.log(nv + 1e-12).item(); v = (Jv / (nv + 1e-12)).detach() - z = z_det.detach() + state = state_det.detach() if sigma > 0: - z = z + sigma * torch.randn(z.shape, generator=gen, device=dev) - lam /= (n_sup * T) - col = model.head(z).argmax(-1) + state = state + sigma * torch.randn(state.shape, generator=gen, device=dev) + lam /= max(n_sup * T, 1) + y, _ = state.chunk(2, dim=-1) + col = model.head(y).argmax(-1) conf = (col[ei[0]] == col[ei[1]]).sum().item() // 2 return conf, lam @@ -47,7 +51,11 @@ def main(): ck = torch.load(args.ckpt, weights_only=False); c = ck['cfg'] deg = torch.tensor(c['deg']) if c.get('deg') else None model = RecGINColor(c['in_dim'], c['hidden'], c['k'], c['T'], c['n_sup'], - grad_mode=c['grad_mode'], conv=c.get('conv', 'gin'), deg=deg).to(dev) + grad_mode=c['grad_mode'], conv=c.get('conv', 'gin'), deg=deg, + agg_layers=c.get('agg_layers', 1), + compute_layers=c.get('compute_layers', 2), + compute=(c.get('compute') if c.get('compute') == 'trm' else 'trm'), + attn_heads=c.get('attn_heads', 4)).to(dev) model.load_state_dict(ck['state']); model.eval() nsup, T = c['n_sup'], c['T'] te = featurize(make_split('test', 50, 3, 0.2, 8, 500, 100000), c.get('pe', 'none'), c.get('rwse_k', 16)) @@ -56,6 +64,7 @@ def main(): det = sum(rollout(model, r['xin'].to(dev), r['edge_index'].to(dev), 0.0, nsup, T, dev, 0)[0] == 0 for r in te) / n out = {'conv': c.get('conv', 'gin'), 'pe': c.get('pe', 'none'), 'seed': c.get('seed'), + 'arch': c.get('arch', 'legacy'), 'grad_mode': c['grad_mode'], 'contract': c.get('contract', False), 'det': det, 'sigmas': {}} print(f"[pe={out['pe']} s{out['seed']}] deterministic solve_rate = {det:.3f} (n={n}, K={args.K})") print(f"{'sigma':>6} {'pass@K':>8} {'lam-sel':>8} {'random':>8} {'perRoll':>8} {'AUROC(s|-lam)':>14}") diff --git a/diag/run_archA.sh b/diag/run_archA.sh index 5385152..6cc6042 100644 --- a/diag/run_archA.sh +++ b/diag/run_archA.sh @@ -1,16 +1,15 @@ #!/usr/bin/env bash -# Conv axis (pe=none): gcn, sage, gat. 5 seeds, train+LE+PTRM. (pin GPU at launch.) +# One-shot aggregation axis (pe=none): gcn, sage, gat. 5 seeds, train+LE. set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog echo "A start gpu=${CUDA_VISIBLE_DEVICES:-?} $(date -Is)" for s in 0 1 2 3 4; do for conv in gcn sage gat; do - ck=runs/ckpt_color_${conv}_full_none_n50_k3_p0.2_T3_ns3_s${s}.pt + ck=runs/ckpt_color_rrog_trm_${conv}_full_none_n50_k3_p0.2_T3_ns3_s${s}.pt echo "== A s$s conv=$conv ==" python3 diag/train_color.py --mode train --conv "$conv" --pe none --p 0.2 --epochs 150 --seed "$s" || echo "!! train $conv s$s" python3 diag/train_color.py --mode le --ckpt "$ck" || echo "!! le $conv s$s" - python3 diag/ptrm_color.py --ckpt "$ck" --K 16 --n_graphs 150 --sigmas 0.2 || echo "!! ptrm $conv s$s" done done echo "doneA=$(date -Is)" diff --git a/diag/run_archB.sh b/diag/run_archB.sh index 317638f..ddc6069 100644 --- a/diag/run_archB.sh +++ b/diag/run_archB.sh @@ -1,21 +1,19 @@ #!/usr/bin/env bash -# GPS transformer backbone + feature axis (gin + lappe / all). 5 seeds. (pin GPU at launch.) +# One-shot GPS encoder + feature axis (gin + lappe / all). 5 seeds. (pin GPU at launch.) set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog echo "B start gpu=${CUDA_VISIBLE_DEVICES:-?} $(date -Is)" for s in 0 1 2 3 4; do - ck=runs/ckpt_color_gps_full_none_n50_k3_p0.2_T3_ns3_s${s}.pt + ck=runs/ckpt_color_rrog_trm_gps_full_none_n50_k3_p0.2_T3_ns3_s${s}.pt echo "== B s$s conv=gps ==" python3 diag/train_color.py --mode train --conv gps --pe none --p 0.2 --epochs 150 --seed "$s" || echo "!! train gps s$s" python3 diag/train_color.py --mode le --ckpt "$ck" || echo "!! le gps s$s" - python3 diag/ptrm_color.py --ckpt "$ck" --K 16 --n_graphs 150 --sigmas 0.2 || echo "!! ptrm gps s$s" for pe in lappe all; do - ck2=runs/ckpt_color_gin_full_${pe}_n50_k3_p0.2_T3_ns3_s${s}.pt + ck2=runs/ckpt_color_rrog_trm_gin_full_${pe}_n50_k3_p0.2_T3_ns3_s${s}.pt echo "== B s$s gin pe=$pe ==" python3 diag/train_color.py --mode train --conv gin --pe "$pe" --p 0.2 --epochs 150 --seed "$s" || echo "!! train $pe s$s" python3 diag/train_color.py --mode le --ckpt "$ck2" || echo "!! le $pe s$s" - python3 diag/ptrm_color.py --ckpt "$ck2" --K 16 --n_graphs 150 --sigmas 0.2 || echo "!! ptrm $pe s$s" done done echo "doneB=$(date -Is)" diff --git a/diag/run_color.sh b/diag/run_color.sh index ad3c406..82c522a 100644 --- a/diag/run_color.sh +++ b/diag/run_color.sh @@ -1,15 +1,12 @@ #!/usr/bin/env bash -# Step-2 (TRM regime, large output): graph 3-coloring, TRM full vs HRM 1-step + LE diagnostic. +# RRoG/TRM-on-GNN: graph 3-coloring, deterministic T=1 lower bound vs T=3 extra compute. set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog echo "host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES:-?} start=$(date -Is)" -for gm in full 1step; do - echo "===== train $gm =====" - python3 diag/train_color.py --mode train --grad_mode "$gm" --p 0.2 --epochs 150 --seed 0 \ - || echo "!! train $gm failed" +for T in 1 3; do + echo "===== train T=$T =====" + python3 diag/train_color.py --mode train --grad_mode full --T "$T" --p 0.2 --epochs 150 --seed 0 \ + || echo "!! train T=$T failed" done -echo "===== LE diagnostic (lambda1: solved vs unsolved) =====" -python3 diag/train_color.py --mode le --ckpt runs/ckpt_color_full_n50_k3_p0.2_T3_ns3_s0.pt || echo "!! le full failed" -python3 diag/train_color.py --mode le --ckpt runs/ckpt_color_1step_n50_k3_p0.2_T3_ns3_s0.pt || echo "!! le 1step failed" echo "done=$(date -Is)" diff --git a/diag/run_le.sh b/diag/run_le.sh index 8fc31ea..07d6a63 100644 --- a/diag/run_le.sh +++ b/diag/run_le.sh @@ -1,5 +1,5 @@ #!/usr/bin/env bash -# Step-2(iii): TRM-ish GIN full-recursion vs 1-step-gradient, then LE diagnostic on each. +# RRoG/TRM-on-GNN GIN full-recursion vs 1-step-gradient, then LE diagnostic on each. set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog @@ -7,6 +7,6 @@ echo "host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES:-?} start=$(date -Is)" python3 diag/train_rec.py --grad_mode full --sigma 0 --K 1 --epochs 200 --seed 0 || echo "!! train full failed" python3 diag/train_rec.py --grad_mode 1step --sigma 0 --K 1 --epochs 200 --seed 0 || echo "!! train 1step failed" echo "===== LE diagnostic (lambda1: success vs failure) =====" -python3 diag/lyap.py --ckpt runs/ckpt_rec_full_sig0.0_K1_bestq_T3_ns3_s0.pt --n_graphs 300 || echo "!! lyap full failed" -python3 diag/lyap.py --ckpt runs/ckpt_rec_1step_sig0.0_K1_bestq_T3_ns3_s0.pt --n_graphs 300 || echo "!! lyap 1step failed" +python3 diag/lyap.py --ckpt runs/ckpt_rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0.pt --n_graphs 300 || echo "!! lyap full failed" +python3 diag/lyap.py --ckpt runs/ckpt_rec_rrog_1step_sig0.0_K1_bestq_T3_ns3_s0.pt --n_graphs 300 || echo "!! lyap 1step failed" echo "done=$(date -Is)" diff --git a/diag/run_pe.sh b/diag/run_pe.sh index 8350160..1e587ce 100644 --- a/diag/run_pe.sh +++ b/diag/run_pe.sh @@ -1,6 +1,5 @@ #!/usr/bin/env bash -# Roadmap #1: RRoG on PE-augmented backbone. GIN vs GIN+RWSE on coloring: -# does RRoG-noise add headroom on top of static structural encoding, or is it redundant? +# RRoG on PE-augmented one-shot GIN encoder. GIN vs GIN+RWSE on coloring. set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog @@ -12,13 +11,7 @@ for pe in none rwse; do done echo "===== LE (full, both pe) =====" for pe in none rwse; do - python3 diag/train_color.py --mode le --ckpt runs/ckpt_color_full_${pe}_n50_k3_p0.2_T3_ns3_s0.pt \ + python3 diag/train_color.py --mode le --ckpt runs/ckpt_color_rrog_trm_gin_full_${pe}_n50_k3_p0.2_T3_ns3_s0.pt \ || echo "!! le $pe failed" done -echo "===== PTRM noise + lambda-select (both pe) =====" -for pe in none rwse; do - echo "--- pe=$pe ---" - python3 diag/ptrm_color.py --ckpt runs/ckpt_color_full_${pe}_n50_k3_p0.2_T3_ns3_s0.pt \ - --K 16 --n_graphs 150 --sigmas 0.1 0.2 0.4 || echo "!! ptrm $pe failed" -done echo "done=$(date -Is)" diff --git a/diag/run_pe2.sh b/diag/run_pe2.sh index db7bd8a..dc9f88b 100644 --- a/diag/run_pe2.sh +++ b/diag/run_pe2.sh @@ -1,17 +1,15 @@ #!/usr/bin/env bash -# Roadmap #2: RRoG on a GSN-style motif backbone (per-node K3/wedge substructure counts). -# full-recursion, 5 seeds; train + LE + PTRM(sigma=0.2). Aggregate vs none/rwse. +# RRoG on a GSN-style motif-augmented one-shot encoder. Full recursion, 5 seeds; train + LE. set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog echo "host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES:-?} start=$(date -Is)" for s in 0 1 2 3 4; do - ck=runs/ckpt_color_full_gsn_n50_k3_p0.2_T3_ns3_s${s}.pt + ck=runs/ckpt_color_rrog_trm_gin_full_gsn_n50_k3_p0.2_T3_ns3_s${s}.pt echo "===== seed=$s full gsn =====" python3 diag/train_color.py --mode train --grad_mode full --pe gsn --p 0.2 --epochs 150 --seed "$s" \ || echo "!! train gsn s$s failed" python3 diag/train_color.py --mode le --ckpt "$ck" || echo "!! le gsn s$s failed" - python3 diag/ptrm_color.py --ckpt "$ck" --K 16 --n_graphs 150 --sigmas 0.2 || echo "!! ptrm gsn s$s failed" done echo "===== AGGREGATE (all pe: none/rwse/gsn) =====" python3 diag/aggregate.py diff --git a/diag/run_pe3.sh b/diag/run_pe3.sh index a978393..2a6744b 100644 --- a/diag/run_pe3.sh +++ b/diag/run_pe3.sh @@ -1,22 +1,20 @@ #!/usr/bin/env bash -# Roadmap #3 (subgraph/ego features) + #4 (IGNN-style forced contraction), 5 seeds. +# Subgraph/ego features + forced contraction, 5 seeds. Deterministic train + LE. # #3: full --pe sub. #4: full --pe none --contract (vs free full/none baseline). set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog echo "host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES:-?} start=$(date -Is)" for s in 0 1 2 3 4; do - ck=runs/ckpt_color_full_sub_n50_k3_p0.2_T3_ns3_s${s}.pt + ck=runs/ckpt_color_rrog_trm_gin_full_sub_n50_k3_p0.2_T3_ns3_s${s}.pt echo "===== seed=$s #3 full sub =====" python3 diag/train_color.py --mode train --grad_mode full --pe sub --p 0.2 --epochs 150 --seed "$s" || echo "!! train sub s$s failed" python3 diag/train_color.py --mode le --ckpt "$ck" || echo "!! le sub s$s failed" - python3 diag/ptrm_color.py --ckpt "$ck" --K 16 --n_graphs 150 --sigmas 0.2 || echo "!! ptrm sub s$s failed" - ck2=runs/ckpt_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s${s}.pt + ck2=runs/ckpt_color_rrog_trm_gin_full_none_ctr_n50_k3_p0.2_T3_ns3_s${s}.pt echo "===== seed=$s #4 full none --contract =====" python3 diag/train_color.py --mode train --grad_mode full --pe none --contract --p 0.2 --epochs 150 --seed "$s" || echo "!! train ctr s$s failed" python3 diag/train_color.py --mode le --ckpt "$ck2" || echo "!! le ctr s$s failed" - python3 diag/ptrm_color.py --ckpt "$ck2" --K 16 --n_graphs 150 --sigmas 0.2 || echo "!! ptrm ctr s$s failed" done echo "===== AGGREGATE =====" python3 diag/aggregate.py diff --git a/diag/run_pna.sh b/diag/run_pna.sh index 897315d..157d8ac 100644 --- a/diag/run_pna.sh +++ b/diag/run_pna.sh @@ -4,10 +4,9 @@ cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog echo "PNA start gpu=${CUDA_VISIBLE_DEVICES:-?} $(date -Is)" for s in 0 1 2 3 4; do - ck=runs/ckpt_color_pna_full_none_n50_k3_p0.2_T3_ns3_s${s}.pt + ck=runs/ckpt_color_rrog_trm_pna_full_none_n50_k3_p0.2_T3_ns3_s${s}.pt echo "== pna s$s ==" python3 diag/train_color.py --mode train --conv pna --pe none --p 0.2 --epochs 150 --seed "$s" || echo "!! train pna s$s" python3 diag/train_color.py --mode le --ckpt "$ck" || echo "!! le pna s$s" - python3 diag/ptrm_color.py --ckpt "$ck" --K 16 --n_graphs 150 --sigmas 0.2 || echo "!! ptrm pna s$s" done echo "donePNA=$(date -Is)" diff --git a/diag/run_rec.sh b/diag/run_rec.sh index 632498d..c436c4e 100644 --- a/diag/run_rec.sh +++ b/diag/run_rec.sh @@ -1,13 +1,12 @@ #!/usr/bin/env bash -# Step-2: recursive GNN + full PTRM on ZINC ring-counting. Does per-step noise + best-Q@K -# selection break the 1-WL counting ceiling that input-RNI couldn't? Averaging vs selection. +# RRoG/TRM-on-GNN on ZINC ring-counting. Deterministic view-only vs recursive compute. set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog echo "host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES:-?} start=$(date -Is)" -run() { echo "===== $* ====="; python3 diag/train_rec.py "$@" --epochs 200 --seed 0 || echo "!! FAILED $*"; } -run --sigma 0 --K 1 --select bestq # deterministic recursive baseline (~1-WL ceiling) -run --sigma 0.1 --K 8 --select none # averaging over rollouts (RNI-style null) -run --sigma 0.1 --K 8 --select bestq # PTRM-proper: per-step noise + best-Q@K selection -run --sigma 0.2 --K 16 --select bestq # scaled noise + rollouts +run() { echo "===== $* ====="; python3 diag/train_rec.py "$@" --epochs 40 --hidden 64 --bs 256 --seed 0 || echo "!! FAILED $*"; } +run --grad_mode full --T 0 --n_sup 3 --sigma 0 --K 1 --select none +run --grad_mode full --T 1 --n_sup 3 --sigma 0 --K 1 --select none +run --grad_mode full --T 3 --n_sup 3 --sigma 0 --K 1 --select none +run --grad_mode full --T 1 --n_sup 3 --act --halt_max_steps 8 --halt_target binary --sigma 0 --K 1 --select none echo "done=$(date -Is)" diff --git a/diag/run_seeds.sh b/diag/run_seeds.sh index 77f22c8..85b67d1 100644 --- a/diag/run_seeds.sh +++ b/diag/run_seeds.sh @@ -1,5 +1,5 @@ #!/usr/bin/env bash -# Harden coloring results with 5 seeds: full-vs-1step solve, LE AUROC, PTRM(sigma=0.2) for none/rwse. +# Harden corrected RRoG coloring results with 5 seeds: full-vs-1step solve + LE AUROC. set -uo pipefail cd /home/yurenh2/rrog export PYTHONPATH=/home/yurenh2/rrog @@ -7,14 +7,11 @@ echo "host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES:-?} start=$(date -Is)" for s in 0 1 2 3 4; do for cfg in "full none" "full rwse" "1step none"; do set -- $cfg; gm=$1; pe=$2 - ck=runs/ckpt_color_${gm}_${pe}_n50_k3_p0.2_T3_ns3_s${s}.pt + ck=runs/ckpt_color_rrog_trm_gin_${gm}_${pe}_n50_k3_p0.2_T3_ns3_s${s}.pt echo "===== seed=$s $gm $pe =====" python3 diag/train_color.py --mode train --grad_mode "$gm" --pe "$pe" --p 0.2 --epochs 150 --seed "$s" \ || echo "!! train $gm $pe s$s failed" python3 diag/train_color.py --mode le --ckpt "$ck" || echo "!! le $gm $pe s$s failed" - if [ "$gm" = "full" ]; then - python3 diag/ptrm_color.py --ckpt "$ck" --K 16 --n_graphs 150 --sigmas 0.2 || echo "!! ptrm $pe s$s failed" - fi done done echo "===== AGGREGATE =====" diff --git a/diag/train_color.py b/diag/train_color.py index 36f8496..b9d0c23 100644 --- a/diag/train_color.py +++ b/diag/train_color.py @@ -1,7 +1,11 @@ -"""Recursive (TRM-ish) GNN graph 3-coloring with swappable BACKBONE for the RRoG roadmap. +"""RRoG/TRM-on-GNN graph 3-coloring. ---conv gin|gcn|sage|gat|gps : message-passing operator (gps = GraphGPS local MPNN + global - attention = TRM's original transformer backbone, on the graph). +The graph is encoded once into a fixed per-node context. Recursion then refines hidden state +with a shared compute block that never reads edge_index. This is the RRoG split: +the GNN encoder supplies the view/context x, TRM-style recurrence supplies computation. + +--conv gin|gcn|sage|gat|gps : message-passing operator used only by the one-shot encoder + (gps = GraphGPS local MPNN + global attention). --pe none|rwse|gsn|sub|lappe|all : input structural features (random sym-break [+ encoding]). --contract : reverse-flossing lambda-penalty during training (force contraction; roadmap #4). --grad_mode full|1step : TRM full recursion vs HRM 1-step gradient. @@ -142,48 +146,83 @@ def make_conv(conv, hidden, deg=None): class RecGINColor(nn.Module): - def __init__(self, in_dim, hidden, k, T=3, n_sup=3, inner=2, grad_mode='full', sigma=0.0, conv='gin', deg=None): + def __init__(self, in_dim, hidden, k, T=3, n_sup=3, inner=2, grad_mode='full', + sigma=0.0, conv='gin', deg=None, agg_layers=4, compute_layers=None, + compute='trm', attn_heads=4): super().__init__() self.conv_type = conv + self.agg_layers = agg_layers + self.compute_layers = compute_layers or inner + self.compute = compute + self.attn_heads = attn_heads self.lin_in = nn.Linear(in_dim, hidden) - self.convs = nn.ModuleList([make_conv(conv, hidden, deg) for _ in range(inner)]) - self.bns = nn.ModuleList([nn.BatchNorm1d(hidden) for _ in range(inner)]) + self.agg_convs = nn.ModuleList([make_conv(conv, hidden, deg) for _ in range(agg_layers)]) + self.agg_bns = nn.ModuleList([nn.BatchNorm1d(hidden) for _ in range(agg_layers)]) + if compute not in ('trm',): + raise ValueError(compute) + core = [] + d = hidden + for _ in range(self.compute_layers - 1): + core += [nn.Linear(d, hidden), nn.GELU()] + d = hidden + core.append(nn.Linear(d, hidden)) + self.core_norm = nn.LayerNorm(hidden) + self.core = nn.Sequential(*core) + nn.init.zeros_(self.core[-1].weight) + nn.init.zeros_(self.core[-1].bias) self.head = nn.Linear(hidden, k) self.T, self.n_sup, self.grad_mode, self.sigma = T, n_sup, grad_mode, sigma - def block(self, z, ei, batch=None): + def aggregate(self, xin, ei, batch=None): if self.conv_type == 'gps' and batch is None: - batch = z.new_zeros(z.size(0), dtype=torch.long) - for conv, bn in zip(self.convs, self.bns): - z = conv(z, ei, batch) if self.conv_type == 'gps' else conv(z, ei) - z = bn(z).relu() - return z - - def _inner(self, z, h0, ei, noise, batch): - z = self.block(z + h0, ei, batch) + batch = xin.new_zeros(xin.size(0), dtype=torch.long) + h = self.lin_in(xin) + for conv, bn in zip(self.agg_convs, self.agg_bns): + h = conv(h, ei, batch) if self.conv_type == 'gps' else conv(h, ei) + h = bn(h).relu() + return h + + def core_step(self, combined, state): + """Shared TRM compute core. Deliberately edge-free.""" + return state + self.core(self.core_norm(combined)) + + def _z_step(self, y, z, ctx, noise): + z = self.core_step(ctx + y + z, z) if noise and self.sigma > 0: z = z + self.sigma * torch.randn_like(z) return z - def recurse(self, z, h0, ei, noise, batch, one_step=False): + def _y_step(self, y, z, noise): + y = self.core_step(y + z, y) + if noise and self.sigma > 0: + y = y + self.sigma * torch.randn_like(y) + return y + + def recurse(self, y, z, ctx, noise, one_step=False): + if self.T == 0: + return y, z if one_step: with torch.no_grad(): for _ in range(self.T - 1): - z = self._inner(z, h0, ei, noise, batch) + z = self._z_step(y, z, ctx, noise) z = z.detach() - return self._inner(z, h0, ei, noise, batch) + z = self._z_step(y, z, ctx, noise) + y = self._y_step(y, z, noise) + return y, z for _ in range(self.T): - z = self._inner(z, h0, ei, noise, batch) - return z + z = self._z_step(y, z, ctx, noise) + y = self._y_step(y, z, noise) + return y, z def forward(self, xin, ei, batch=None, noise=False): - h0 = self.lin_in(xin) - z = torch.zeros_like(h0) + ctx = self.aggregate(xin, ei, batch) + y = ctx + z = torch.zeros_like(ctx) outs = [] for s in range(self.n_sup): - z = self.recurse(z, h0, ei, noise, batch, one_step=(self.grad_mode == '1step')) - outs.append(self.head(z)) - z = z.detach() + y, z = self.recurse(y, z, ctx, noise, one_step=(self.grad_mode == '1step')) + outs.append(self.head(y)) + y, z = y.detach(), z.detach() return outs @@ -206,15 +245,17 @@ def solve_stats(model, recs, dev, sample=None): def lyap1(model, xin, ei, n_steps, dev, seed=0): g = torch.Generator(device=dev).manual_seed(seed) - h0 = model.lin_in(xin).detach() - z = torch.zeros_like(h0) - v = torch.randn(h0.shape, generator=g, device=dev); v = v / (v.norm() + 1e-12) - def step_fn(zz): - return model.block(zz + h0, ei) + ctx = model.aggregate(xin, ei).detach() + state = torch.cat([ctx, torch.zeros_like(ctx)], dim=-1).detach() + v = torch.randn(state.shape, generator=g, device=dev); v = v / (v.norm() + 1e-12) + def step_fn(ss): + y, z = ss.chunk(2, dim=-1) + y, z = model.recurse(y, z, ctx, noise=False) + return torch.cat([y, z], dim=-1) lam = 0.0 for _ in range(n_steps): - z_next, Jv = torch.autograd.functional.jvp(step_fn, z, v) - z = z_next.detach(); nv = Jv.norm() + state_next, Jv = torch.autograd.functional.jvp(step_fn, state, v) + state = state_next.detach(); nv = Jv.norm() lam += torch.log(nv + 1e-12).item(); v = (Jv / (nv + 1e-12)).detach() return lam / n_steps @@ -246,11 +287,16 @@ def run_le(model, recs, dev, n_steps, n_graphs=300): def lyap_penalty(model, x, ei, batch, target=-0.5): - h0 = model.lin_in(x) + ctx = model.aggregate(x, ei, batch) with torch.no_grad(): - zr = model.recurse(torch.zeros_like(h0), h0.detach(), ei, False, batch) - v = torch.randn_like(zr); v = v / (v.norm() + 1e-12) - _, Jv = torch.autograd.functional.jvp(lambda zz: model.block(zz + h0, ei, batch), zr, v, create_graph=True) + yr, zr = model.recurse(ctx.detach(), torch.zeros_like(ctx).detach(), ctx.detach(), False) + state = torch.cat([yr, zr], dim=-1) + v = torch.randn_like(state); v = v / (v.norm() + 1e-12) + def step_fn(ss): + y, z = ss.chunk(2, dim=-1) + y, z = model.recurse(y, z, ctx, noise=False) + return torch.cat([y, z], dim=-1) + _, Jv = torch.autograd.functional.jvp(step_fn, state, v, create_graph=True) return (torch.log(Jv.norm() + 1e-12) - target) ** 2 @@ -267,6 +313,10 @@ def main(): ap.add_argument('--p', type=float, default=0.2); ap.add_argument('--r', type=int, default=8) ap.add_argument('--hidden', type=int, default=128); ap.add_argument('--T', type=int, default=3) ap.add_argument('--n_sup', type=int, default=3); ap.add_argument('--epochs', type=int, default=150) + ap.add_argument('--agg_layers', type=int, default=4) + ap.add_argument('--compute_layers', type=int, default=2) + ap.add_argument('--compute', choices=['trm'], default='trm') + ap.add_argument('--attn_heads', type=int, default=4) ap.add_argument('--lr', type=float, default=1e-3); ap.add_argument('--bs', type=int, default=32) ap.add_argument('--seed', type=int, default=0) args = ap.parse_args() @@ -280,13 +330,18 @@ def main(): c.get('pe', 'none'), c.get('rwse_k', 16)) deg = torch.tensor(c['deg']) if c.get('deg') else None model = RecGINColor(c['in_dim'], c['hidden'], c['k'], c['T'], c['n_sup'], - grad_mode=c['grad_mode'], conv=c.get('conv', 'gin'), deg=deg).to(dev) + grad_mode=c['grad_mode'], conv=c.get('conv', 'gin'), deg=deg, + agg_layers=c.get('agg_layers', 1), + compute_layers=c.get('compute_layers', 2), + compute=(c.get('compute') if c.get('compute') == 'trm' else 'trm'), + attn_heads=c.get('attn_heads', 4)).to(dev) model.load_state_dict(ck['state']); model.eval() res = run_le(model, te, dev, c['n_sup'] * c['T']) base = os.path.basename(args.ckpt).replace('ckpt_', '').replace('.pt', '') with open(os.path.join(OUT, f"le_{base}.json"), 'w') as fjs: json.dump({'conv': c.get('conv', 'gin'), 'grad_mode': c['grad_mode'], 'pe': c.get('pe', 'none'), - 'contract': c.get('contract', False), 'seed': c.get('seed'), **res}, fjs, indent=2) + 'contract': c.get('contract', False), 'seed': c.get('seed'), + 'arch': c.get('arch', 'legacy'), **res}, fjs, indent=2) return te = featurize(make_split('test', args.n, args.k, args.p, args.r, 500, 100000), args.pe, args.rwse_k) @@ -296,7 +351,9 @@ def main(): trl = DataLoader(data, batch_size=args.bs, shuffle=True, drop_last=True) deg = deg_hist(tr) if args.conv == 'pna' else None model = RecGINColor(in_dim, args.hidden, args.k, args.T, args.n_sup, - grad_mode=args.grad_mode, conv=args.conv, deg=deg).to(dev) + grad_mode=args.grad_mode, conv=args.conv, deg=deg, + agg_layers=args.agg_layers, compute_layers=args.compute_layers, + compute=args.compute, attn_heads=args.attn_heads).to(dev) opt = torch.optim.Adam(model.parameters(), lr=args.lr, weight_decay=1e-5) sched = torch.optim.lr_scheduler.CosineAnnealingLR(opt, args.epochs) @@ -329,15 +386,18 @@ def main(): print(f"ep{ep+1} solve_rate={sr:.3f} mean_conflicts={mc:.2f}", flush=True) sfx = ('_ctr' if args.contract else '') - tag = f"color_{args.conv}_{args.grad_mode}_{args.pe}{sfx}_n{args.n}_k{args.k}_p{args.p}_T{args.T}_ns{args.n_sup}_s{args.seed}" + tag = f"color_rrog_{args.compute}_{args.conv}_{args.grad_mode}_{args.pe}{sfx}_n{args.n}_k{args.k}_p{args.p}_T{args.T}_ns{args.n_sup}_s{args.seed}" rep = {'task': 'graph3coloring', 'tag': tag, **vars(args), 'in_dim': in_dim, - 'sec': round(time.time() - t0, 1), **best} + 'arch': 'rrog_once_agg_hidden_compute', 'sec': round(time.time() - t0, 1), **best} print(f"[{tag}] best solve_rate={best.get('solve_rate')} @ep{best.get('ep')} ({rep['sec']}s)") with open(os.path.join(OUT, f"{tag}.json"), 'w') as f: json.dump(rep, f, indent=2) torch.save({'state': best_state, 'cfg': {'in_dim': in_dim, 'hidden': args.hidden, 'k': args.k, 'T': args.T, 'n_sup': args.n_sup, 'grad_mode': args.grad_mode, 'pe': args.pe, 'rwse_k': args.rwse_k, 'contract': args.contract, 'conv': args.conv, 'seed': args.seed, + 'agg_layers': args.agg_layers, 'compute_layers': args.compute_layers, + 'compute': args.compute, 'attn_heads': args.attn_heads, + 'arch': 'rrog_once_agg_hidden_compute', 'deg': (deg.tolist() if deg is not None else None)}}, os.path.join(OUT, f"ckpt_{tag}.pt")) print(" wrote", os.path.join(OUT, f"ckpt_{tag}.pt")) diff --git a/diag/train_cycle.py b/diag/train_cycle.py index d2342f3..598e349 100644 --- a/diag/train_cycle.py +++ b/diag/train_cycle.py @@ -24,9 +24,14 @@ from torch_geometric.loader import DataLoader from torch_geometric.utils import to_networkx from torch_geometric.nn import GINConv, GCNConv, global_add_pool -ROOT = '/home/yurenh2/rrog/data/zinc' -CACHE = '/home/yurenh2/rrog/data/cycle_cache' -OUT = '/home/yurenh2/rrog/runs' +PROJECT_ROOT = os.environ.get( + 'RROG_ROOT', + os.path.abspath(os.path.join(os.path.dirname(__file__), '..')), +) +DATA_ROOT = os.environ.get('RROG_DATA_DIR', os.path.join(PROJECT_ROOT, 'data')) +OUT = os.environ.get('RROG_RUNS_DIR', os.path.join(PROJECT_ROOT, 'runs')) +ROOT = os.path.join(DATA_ROOT, 'zinc') +CACHE = os.path.join(DATA_ROOT, 'cycle_cache') RWSE_K = 16 diff --git a/diag/train_rec.py b/diag/train_rec.py index 9866f28..9db7eb1 100644 --- a/diag/train_rec.py +++ b/diag/train_rec.py @@ -1,11 +1,10 @@ -"""Step-2: Recursive (TRM-ish) GNN on ZINC ring-counting + optional PTRM noise/selection. +"""Step-2: RRoG/TRM-on-GNN for ZINC ring-counting. -Recurrent shared-weight GIN block, deep-supervised over n_sup steps (TRM-style: carry latent -detached between steps). --grad_mode controls the LAST supervision step's recursion: +The graph is encoded once with a GIN encoder. A shared edge-free node-wise compute block then +refines hidden state over n_sup*T recurrent steps (TRM-style: carry latent detached between +deep-supervision steps). --grad_mode controls the LAST supervision step's recursion: full : backprop through all T inner recursions (TRM) 1step : backprop only the last inner recursion, first T-1 detached (HRM 1-step-gradient) -Optional per-step Gaussian noise (sigma) + K stochastic rollouts selected by a value head -(best-Q@K) for the PTRM experiments. Saves a checkpoint for the LE diagnostic (diag/lyap.py). Run: PYTHONPATH=/home/yurenh2/rrog python3 diag/train_rec.py --grad_mode full --sigma 0 --K 1 """ @@ -14,66 +13,218 @@ import numpy as np import torch import torch.nn as nn from torch_geometric.loader import DataLoader -from torch_geometric.data import Data -from torch_geometric.nn import GINConv, global_add_pool +from torch_geometric.data import Batch, Data +from torch_geometric.nn import ( + APPNP, + ARMAConv, + ChebConv, + FiLMConv, + GATv2Conv, + GCNConv, + GENConv, + GINEConv, + GINConv, + GraphConv, + MFConv, + PNAConv, + ResGatedGraphConv, + SAGEConv, + SGConv, + TAGConv, + TransformerConv, + global_add_pool, +) +from torch_geometric.utils import degree from diag.train_cycle import prepare -OUT = '/home/yurenh2/rrog/runs' +PROJECT_ROOT = os.environ.get( + 'RROG_ROOT', + os.path.abspath(os.path.join(os.path.dirname(__file__), '..')), +) +OUT = os.environ.get('RROG_RUNS_DIR', os.path.join(PROJECT_ROOT, 'runs')) +SUPPORTED_VIEWS = [ + 'gin', 'gine', 'gcn', 'graphsage', 'gatv2', 'graphconv', 'transformer', 'pna', + 'gen', 'film', 'resgated', 'tag', 'sgc', 'cheb', 'arma', 'mf', 'appnp', +] -def loader(recs, bs, shuffle, drop_last=False): - data = [Data(x=r['x'], edge_index=r['edge_index'], y=r['y'].view(1, 2), +def data_list(recs): + return [Data(x=r['x'], edge_index=r['edge_index'], y=r['y'].view(1, 2), num_nodes=r['x'].numel()) for r in recs] + + +def loader(recs, bs, shuffle, drop_last=False): + data = recs if recs and isinstance(recs[0], Data) else data_list(recs) return DataLoader(data, batch_size=bs, shuffle=shuffle, drop_last=drop_last) +def degree_histogram(data): + max_degree = 0 + degs = [] + for graph in data: + deg = degree(graph.edge_index[1], num_nodes=graph.num_nodes, dtype=torch.long) + degs.append(deg) + if deg.numel(): + max_degree = max(max_degree, int(deg.max().item())) + hist = torch.zeros(max_degree + 1, dtype=torch.long) + for deg in degs: + hist += torch.bincount(deg, minlength=hist.numel()) + return hist + + +def make_view_layer(view, hidden, deg): + if view == 'gin': + return GINConv(nn.Sequential( + nn.Linear(hidden, hidden), nn.ReLU(), nn.Linear(hidden, hidden)), train_eps=True) + if view == 'gine': + return GINEConv(nn.Sequential( + nn.Linear(hidden, hidden), nn.ReLU(), nn.Linear(hidden, hidden)), + train_eps=True, edge_dim=hidden) + if view == 'gcn': + return GCNConv(hidden, hidden) + if view == 'graphsage': + return SAGEConv(hidden, hidden) + if view == 'gatv2': + return GATv2Conv(hidden, hidden, heads=4, concat=False) + if view == 'graphconv': + return GraphConv(hidden, hidden) + if view == 'transformer': + return TransformerConv(hidden, hidden, heads=4, concat=False) + if view == 'pna': + if deg is None: + raise ValueError('PNA view requires a training-set degree histogram') + return PNAConv( + hidden, hidden, + aggregators=['mean', 'min', 'max', 'std'], + scalers=['identity', 'amplification', 'attenuation'], + deg=deg, + ) + if view == 'gen': + return GENConv(hidden, hidden) + if view == 'film': + return FiLMConv(hidden, hidden) + if view == 'resgated': + return ResGatedGraphConv(hidden, hidden) + if view == 'tag': + return TAGConv(hidden, hidden, K=3) + if view == 'sgc': + return SGConv(hidden, hidden, K=2, cached=False) + if view == 'cheb': + return ChebConv(hidden, hidden, K=3) + if view == 'arma': + return ARMAConv(hidden, hidden, num_stacks=1, num_layers=2) + if view == 'mf': + return MFConv(hidden, hidden) + if view == 'appnp': + return APPNP(K=5, alpha=0.1) + raise ValueError(f'unsupported view: {view}') + + class RecGIN(nn.Module): - def __init__(self, n_atom, hidden=128, T=3, n_sup=3, sigma=0.0, inner=2, grad_mode='full'): + def __init__(self, n_atom, hidden=128, T=3, n_sup=3, sigma=0.0, inner=2, + grad_mode='full', agg_layers=5, compute_layers=None, view='gin', deg=None): super().__init__() + self.view = view + self.agg_layers = agg_layers + self.compute_layers = compute_layers or inner self.emb = nn.Embedding(n_atom, hidden) - self.convs = nn.ModuleList([GINConv(nn.Sequential( - nn.Linear(hidden, hidden), nn.ReLU(), nn.Linear(hidden, hidden)), train_eps=True) - for _ in range(inner)]) - self.bns = nn.ModuleList([nn.BatchNorm1d(hidden) for _ in range(inner)]) + self.edge_emb = nn.Embedding(1, hidden) if view == 'gine' else None + self.agg_convs = nn.ModuleList() + for _ in range(agg_layers): + self.agg_convs.append(make_view_layer(view, hidden, deg)) + self.agg_bns = nn.ModuleList([nn.BatchNorm1d(hidden) for _ in range(agg_layers)]) + core = [] + d = hidden + for _ in range(self.compute_layers - 1): + core += [nn.Linear(d, hidden), nn.GELU()] + d = hidden + core.append(nn.Linear(d, hidden)) + self.core_norm = nn.LayerNorm(hidden) + self.core = nn.Sequential(*core) + nn.init.zeros_(self.core[-1].weight) + nn.init.zeros_(self.core[-1].bias) self.head = nn.Sequential(nn.Linear(hidden, hidden), nn.ReLU(), nn.Linear(hidden, 2)) self.qhead = nn.Sequential(nn.Linear(hidden, hidden), nn.ReLU(), nn.Linear(hidden, 1)) + with torch.no_grad(): + self.qhead[-1].weight.zero_() + self.qhead[-1].bias.fill_(-5.0) self.T, self.n_sup, self.sigma, self.grad_mode = T, n_sup, sigma, grad_mode - def block(self, z, ei): - for conv, bn in zip(self.convs, self.bns): - z = bn(conv(z, ei)).relu() - return z + def aggregate(self, x, ei): + h = self.emb(x) + for conv, bn in zip(self.agg_convs, self.agg_bns): + if self.view == 'gine': + edge_attr = self.edge_emb(torch.zeros(ei.size(1), dtype=torch.long, device=ei.device)) + h = bn(conv(h, ei, edge_attr)).relu() + else: + h = bn(conv(h, ei)).relu() + return h + + def core_step(self, combined, state): + """Shared TRM compute core. Deliberately edge-free.""" + return state + self.core(self.core_norm(combined)) - def _inner(self, z, h0, ei, noise): - z = self.block(z + h0, ei) + def _z_step(self, y, z, ctx, noise): + z = self.core_step(ctx + y + z, z) if noise and self.sigma > 0: z = z + self.sigma * torch.randn_like(z) return z - def recurse(self, z, h0, ei, noise, one_step=False): + def _y_step(self, y, z, noise): + y = self.core_step(y + z, y) + if noise and self.sigma > 0: + y = y + self.sigma * torch.randn_like(y) + return y + + def recurse(self, y, z, ctx, noise, one_step=False): + if self.T == 0: + return y, z if one_step: # HRM 1-step gradient with torch.no_grad(): for _ in range(self.T - 1): - z = self._inner(z, h0, ei, noise) + z = self._z_step(y, z, ctx, noise) z = z.detach() - return self._inner(z, h0, ei, noise) # only last inner carries grad + z = self._z_step(y, z, ctx, noise) # only last inner carries grad + y = self._y_step(y, z, noise) + return y, z for _ in range(self.T): # TRM full recursion - z = self._inner(z, h0, ei, noise) - return z + z = self._z_step(y, z, ctx, noise) + y = self._y_step(y, z, noise) + return y, z + + def predict(self, y, batch): + pooled = global_add_pool(y, batch) + return self.head(pooled), self.qhead(pooled).view(-1) + + def forward_trace(self, x, ei, batch, steps, noise=False): + ctx = self.aggregate(x, ei) + y = ctx + z = torch.zeros_like(ctx) + preds, q_logits = [], [] + for s in range(steps): + y, z = self.recurse(y, z, ctx, noise, one_step=(self.grad_mode == '1step')) + pred, q = self.predict(y, batch) + preds.append(pred) + q_logits.append(q) + if s < steps - 1: + y, z = y.detach(), z.detach() + return preds, q_logits def forward(self, x, ei, batch, noise=False): - h0 = self.emb(x) - z = torch.zeros_like(h0) + ctx = self.aggregate(x, ei) + y = ctx + z = torch.zeros_like(ctx) preds = [] for s in range(self.n_sup): if s < self.n_sup - 1: with torch.no_grad(): - z = self.recurse(z, h0, ei, noise) - z = z.detach() + y, z = self.recurse(y, z, ctx, noise) + y, z = y.detach(), z.detach() else: - z = self.recurse(z, h0, ei, noise, one_step=(self.grad_mode == '1step')) - preds.append(self.head(global_add_pool(z, batch))) - q = self.qhead(global_add_pool(z, batch)).view(-1) + y, z = self.recurse(y, z, ctx, noise, one_step=(self.grad_mode == '1step')) + pred, _ = self.predict(y, batch) + preds.append(pred) + _, q = self.predict(y, batch) return preds, q @@ -102,6 +253,113 @@ def evaluate(model, ld, dev, ymu, ysd, K=1, select='none'): return (ae / n).tolist(), (ae_or / n).tolist() +@torch.no_grad() +def evaluate_trace(model, ld, dev, ymu, ysd, steps, adaptive=False): + model.eval() + ysd_d, ymu_d = ysd.to(dev), ymu.to(dev) + ae = torch.zeros(2) + n = 0 + step_sum = 0.0 + for b in ld: + b = b.to(dev) + preds, q_logits = model.forward_trace(b.x, b.edge_index, b.batch, steps, noise=False) + P = torch.stack(preds, dim=0) + if adaptive: + Q = torch.stack(q_logits, dim=0) + halted = Q > 0 + any_halt = halted.any(dim=0) + first_halt = halted.to(torch.int64).argmax(dim=0) + fallback = torch.full_like(first_halt, steps - 1) + idx = torch.where(any_halt, first_halt, fallback) + chosen = P[idx, torch.arange(P.size(1), device=dev)] + step_sum += (idx.to(torch.float32) + 1).sum().item() + else: + chosen = P[-1] + step_sum += steps * b.num_graphs + ae += ((chosen * ysd_d + ymu_d) - (b.y * ysd_d + ymu_d)).abs().sum(0).cpu() + n += b.num_graphs + return (ae / n).tolist(), step_sum / max(n, 1) + + +def _split_nodes(t, ptr): + return [t[ptr[i].item():ptr[i + 1].item()].detach() for i in range(ptr.numel() - 1)] + + +def act_train_step(model, state, replacement_batch, opt, dev, args): + replacement = replacement_batch.to_data_list() + batch_size = len(replacement) + if state is None: + state = { + 'graphs': [None for _ in range(batch_size)], + 'y': [None for _ in range(batch_size)], + 'z': [None for _ in range(batch_size)], + 'steps': torch.zeros(batch_size, dtype=torch.long, device=dev), + 'halted': torch.ones(batch_size, dtype=torch.bool, device=dev), + } + + halted_cpu = state['halted'].detach().cpu().tolist() + for i, halted in enumerate(halted_cpu): + if halted: + state['graphs'][i] = replacement[i] + + b = Batch.from_data_list(state['graphs']).to(dev) + ctx = model.aggregate(b.x, b.edge_index) + ptr = b.ptr + y_parts, z_parts = [], [] + for i in range(batch_size): + start, end = ptr[i].item(), ptr[i + 1].item() + if halted_cpu[i] or state['y'][i] is None: + y_parts.append(ctx[start:end]) + z_parts.append(torch.zeros_like(ctx[start:end])) + else: + y_parts.append(state['y'][i].to(dev)) + z_parts.append(state['z'][i].to(dev)) + y = torch.cat(y_parts, dim=0) + z = torch.cat(z_parts, dim=0) + + opt.zero_grad() + y, z = model.recurse(y, z, ctx, noise=False, one_step=(model.grad_mode == '1step')) + pred, q = model.predict(y, b.batch) + per_graph_err = (pred - b.y).abs().mean(1) + pred_loss = per_graph_err.mean() + with torch.no_grad(): + if args.halt_target == 'binary': + halt_target = (per_graph_err <= args.halt_norm_threshold).to(q.dtype) + else: + halt_target = torch.sigmoid((args.halt_norm_threshold - per_graph_err) / args.halt_temp) + q_loss = nn.functional.binary_cross_entropy_with_logits(q, halt_target) + loss = pred_loss + 0.5 * args.lam_q * q_loss + y_det, z_det = y.detach(), z.detach() + loss.backward() + torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0) + opt.step() + + state['y'] = _split_nodes(y_det, ptr) + state['z'] = _split_nodes(z_det, ptr) + with torch.no_grad(): + was_halted = state['halted'] + steps = torch.where(was_halted, torch.zeros_like(state['steps']), state['steps']) + 1 + halted = (steps >= args.halt_max_steps) | (q.detach() > 0) + if args.halt_exploration_prob > 0 and args.halt_max_steps > 1: + explore = torch.rand_like(q) < args.halt_exploration_prob + min_steps = torch.where( + explore, + torch.randint(2, args.halt_max_steps + 1, steps.shape, device=dev), + torch.zeros_like(steps), + ) + halted = halted & (steps >= min_steps) + state['steps'] = steps + state['halted'] = halted + + return state, { + 'loss': float(loss.detach().cpu()), + 'pred_loss': float(pred_loss.detach().cpu()), + 'q_loss': float(q_loss.detach().cpu()), + 'halted_frac': float(state['halted'].to(torch.float32).mean().detach().cpu()), + 'steps': float(state['steps'].to(torch.float32).mean().detach().cpu()), + } + + def main(): ap = argparse.ArgumentParser() ap.add_argument('--grad_mode', choices=['full', '1step'], default='full') @@ -111,14 +369,27 @@ def main(): ap.add_argument('--T', type=int, default=3) ap.add_argument('--n_sup', type=int, default=3) ap.add_argument('--hidden', type=int, default=128) + ap.add_argument('--agg_layers', type=int, default=5) + ap.add_argument('--compute_layers', type=int, default=2) + ap.add_argument('--view', choices=SUPPORTED_VIEWS, default='gin') ap.add_argument('--epochs', type=int, default=200) ap.add_argument('--lr', type=float, default=1e-3) ap.add_argument('--bs', type=int, default=128) ap.add_argument('--lam_q', type=float, default=1.0) + ap.add_argument('--act', action='store_true', + help='train all recurrent depths up to halt_max_steps and train qhead as a halt head') + ap.add_argument('--halt_max_steps', type=int, default=8) + ap.add_argument('--halt_norm_threshold', type=float, default=0.30) + ap.add_argument('--halt_temp', type=float, default=0.10) + ap.add_argument('--halt_target', choices=['soft', 'binary'], default='soft') + ap.add_argument('--halt_exploration_prob', type=float, default=0.1) + ap.add_argument('--loss_mode', choices=['last', 'trace'], default='trace') ap.add_argument('--seed', type=int, default=0) + ap.add_argument('--device', default='auto') args = ap.parse_args() torch.manual_seed(args.seed); np.random.seed(args.seed) - dev = 'cuda' if torch.cuda.is_available() else 'cpu' + dev = 'cuda' if args.device == 'auto' and torch.cuda.is_available() else ( + 'cpu' if args.device == 'auto' else args.device) os.makedirs(OUT, exist_ok=True) tr, va, te = prepare('train'), prepare('val'), prepare('test') @@ -127,45 +398,91 @@ def main(): for recs in (tr, va, te): for r in recs: r['y'] = (r['y'] - ymu) / ysd - trl = loader(tr, args.bs, True, drop_last=True) + train_data = data_list(tr) + trl = loader(train_data, args.bs, True, drop_last=True) val, tel = loader(va, 256, False), loader(te, 256, False) - model = RecGIN(n_atom, args.hidden, args.T, args.n_sup, args.sigma, grad_mode=args.grad_mode).to(dev) + deg = degree_histogram(train_data) if args.view == 'pna' else None + model = RecGIN(n_atom, args.hidden, args.T, args.n_sup, args.sigma, grad_mode=args.grad_mode, + agg_layers=args.agg_layers, compute_layers=args.compute_layers, + view=args.view, deg=deg).to(dev) opt = torch.optim.Adam(model.parameters(), lr=args.lr, weight_decay=1e-5) sched = torch.optim.lr_scheduler.CosineAnnealingLR(opt, args.epochs) l1 = nn.L1Loss() + act_steps = max(1, args.halt_max_steps) - t0 = time.time(); best_val = 9e9; best = {}; best_state = None + t0 = time.time(); best_val = 9e9; best = {}; best_state = None; act_state = None for ep in range(args.epochs): model.train() + act_metrics = [] for b in trl: - b = b.to(dev); opt.zero_grad() - preds, q = model(b.x, b.edge_index, b.batch, noise=model.sigma > 0) - loss = sum(l1(p, b.y) for p in preds) / len(preds) - with torch.no_grad(): - tq = -(preds[-1] - b.y).abs().mean(1) - loss = loss + args.lam_q * nn.functional.mse_loss(q, tq) - loss.backward(); torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0); opt.step() + if args.act: + act_state, metrics = act_train_step(model, act_state, b, opt, dev, args) + act_metrics.append(metrics) + else: + b = b.to(dev); opt.zero_grad() + if args.loss_mode == 'trace': + preds, q_logits = model.forward_trace( + b.x, b.edge_index, b.batch, args.n_sup, noise=model.sigma > 0) + q = q_logits[-1] + else: + preds, q = model(b.x, b.edge_index, b.batch, noise=model.sigma > 0) + loss = sum(l1(p, b.y) for p in preds) / len(preds) + with torch.no_grad(): + tq = -(preds[-1] - b.y).abs().mean(1) + loss = loss + args.lam_q * nn.functional.mse_loss(q, tq) + loss.backward(); torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0); opt.step() sched.step() if (ep + 1) % 20 == 0 or ep == args.epochs - 1: - vm, _ = evaluate(model, val, dev, ymu, ysd, args.K, args.select) + if args.act: + vm, _ = evaluate_trace(model, val, dev, ymu, ysd, act_steps, adaptive=False) + else: + vm, _ = evaluate(model, val, dev, ymu, ysd, args.K, args.select) if sum(vm) < best_val: best_val = sum(vm) - tem, teo = evaluate(model, tel, dev, ymu, ysd, args.K, args.select) - best = {'ep': ep + 1, 'val_mae': vm, 'test_mae': tem, 'test_mae_oracle': teo} + if args.act: + tem, fixed_steps = evaluate_trace(model, tel, dev, ymu, ysd, act_steps, adaptive=False) + tea, adaptive_steps = evaluate_trace(model, tel, dev, ymu, ysd, act_steps, adaptive=True) + best = {'ep': ep + 1, 'val_mae': vm, 'test_mae': tem, + 'test_mae_adaptive': tea, 'fixed_steps': fixed_steps, + 'adaptive_steps': adaptive_steps} + else: + tem, teo = evaluate(model, tel, dev, ymu, ysd, args.K, args.select) + best = {'ep': ep + 1, 'val_mae': vm, 'test_mae': tem, 'test_mae_oracle': teo} best_state = {k: v.detach().cpu().clone() for k, v in model.state_dict().items()} - print(f"ep{ep+1} val_mae={[round(x,3) for x in vm]}", flush=True) + if args.act and act_metrics: + hm = sum(m['halted_frac'] for m in act_metrics) / len(act_metrics) + sm = sum(m['steps'] for m in act_metrics) / len(act_metrics) + print(f"ep{ep+1} val_mae={[round(x,3) for x in vm]} halt={hm:.2f} train_steps={sm:.2f}", flush=True) + else: + print(f"ep{ep+1} val_mae={[round(x,3) for x in vm]}", flush=True) - tag = f"rec_{args.grad_mode}_sig{args.sigma}_K{args.K}_{args.select}_T{args.T}_ns{args.n_sup}_s{args.seed}" + act_tag = f"_actfull{act_steps}_{args.halt_target}{args.halt_norm_threshold:g}_e{args.epochs}" if args.act else "" + loss_tag = f"_{args.loss_mode}" if (not args.act and args.loss_mode != 'last') else "" + view_tag = f"_{args.view}" if args.view != 'gin' else "" + tag = f"rec_rrog{view_tag}_{args.grad_mode}_sig{args.sigma}_K{args.K}_{args.select}_T{args.T}_ns{args.n_sup}{loss_tag}{act_tag}_s{args.seed}" rep = {'dataset': 'ZINC-cycle56', 'tag': tag, **vars(args), 'sec': round(time.time() - t0, 1), - 'dev': dev, 'y_std_raw': ysd.tolist(), **best} - print(f"[{tag}] test_mae={[round(x,3) for x in best.get('test_mae')]} " - f"oracle@K={[round(x,3) for x in best.get('test_mae_oracle')]} @ep{best.get('ep')} ({rep['sec']}s)") + 'dev': dev, 'arch': 'rrog_once_agg_node_compute', 'y_std_raw': ysd.tolist(), **best} + if args.act: + print(f"[{tag}] test_mae={[round(x,3) for x in best.get('test_mae')]} " + f"adaptive={[round(x,3) for x in best.get('test_mae_adaptive')]} " + f"steps={best.get('adaptive_steps'):.2f}/{best.get('fixed_steps'):.2f} " + f"@ep{best.get('ep')} ({rep['sec']}s)") + else: + print(f"[{tag}] test_mae={[round(x,3) for x in best.get('test_mae')]} " + f"oracle@K={[round(x,3) for x in best.get('test_mae_oracle')]} @ep{best.get('ep')} ({rep['sec']}s)") with open(os.path.join(OUT, f"{tag}.json"), 'w') as f: json.dump(rep, f, indent=2) torch.save({'state': best_state or model.state_dict(), 'cfg': {'n_atom': n_atom, 'hidden': args.hidden, 'T': args.T, 'n_sup': args.n_sup, - 'sigma': args.sigma, 'grad_mode': args.grad_mode}, + 'sigma': args.sigma, 'grad_mode': args.grad_mode, + 'agg_layers': args.agg_layers, 'compute_layers': args.compute_layers, + 'view': args.view, + 'loss_mode': args.loss_mode, + 'act': args.act, 'act_impl': 'persistent_recycle' if args.act else 'none', + 'halt_max_steps': act_steps, + 'halt_exploration_prob': args.halt_exploration_prob, + 'arch': 'rrog_once_agg_node_compute'}, 'ymu': ymu, 'ysd': ysd}, os.path.join(OUT, f"ckpt_{tag}.pt")) print(" wrote", os.path.join(OUT, f"ckpt_{tag}.pt")) diff --git a/logs/local_gpu3_act_ablation_20260624_102042.log b/logs/local_gpu3_act_ablation_20260624_102042.log new file mode 100644 index 0000000..99d42f7 --- /dev/null +++ b/logs/local_gpu3_act_ablation_20260624_102042.log @@ -0,0 +1,39 @@ +[gpu3-ablation] start Wed Jun 24 10:20:44 CDT 2026 +[gpu3-ablation] phase1 exact target, classification tasks, views=gin gcn sgc tag graphconv appnp pna resgated +[launch] cuda:3: ogbg-molhiv ogbg-molbbbp ogbg-molsider ogbg-molbace ogbg-moltox21 ogbg-molclintox +[launch] cuda:3: ogbg-molesol ogbg-mollipo ogbg-moltox21 ogbg-molclintox +[task] ogbg-molhiv on cuda:3 +[task] ogbg-molesol on cuda:3 +[run] ogbg-molesol view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +[run] ogbg-molhiv view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gin --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view gin --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +Downloading http://snap.stanford.edu/ogb/data/graphproppred/csv_mol_download/esol.zip + 0%| | 0/2 [00:00 + main() + ~~~~^^ + File "/home/yurenh2/rrog-gnn-runner/rrog/train_ogb_graphprop.py", line 601, in main + act_state, train_metrics = train_epoch( + ~~~~~~~~~~~^ + model, train_loader, opt, dev, args, act_state, ema_state, ep + 1, metric) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/yurenh2/rrog-gnn-runner/rrog/train_ogb_graphprop.py", line 507, in train_epoch + act_state, m = act_train_step(model, act_state, batch, opt, dev, args, epoch, metric) + ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/yurenh2/rrog-gnn-runner/rrog/train_ogb_graphprop.py", line 412, in act_train_step + raise ValueError(args.halt_target) +ValueError: exact diff --git a/logs/local_gpu3_act_ablation_retry_20260624_102233.log b/logs/local_gpu3_act_ablation_retry_20260624_102233.log new file mode 100644 index 0000000..52adc5f --- /dev/null +++ b/logs/local_gpu3_act_ablation_retry_20260624_102233.log @@ -0,0 +1,2105 @@ +[gpu3-ablation] start Wed Jun 24 10:22:35 CDT 2026 +[gpu3-ablation] phase1 exact target, classification tasks, views=gin gcn sgc tag graphconv appnp pna resgated +[launch] cuda:3: ogbg-molhiv ogbg-molbbbp ogbg-molsider ogbg-molbace ogbg-moltox21 ogbg-molclintox +[task] ogbg-molhiv on cuda:3 +[run] ogbg-molhiv view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view gin --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +ep10 val_rocauc=0.57684 val_adapt_rocauc=0.58405 adapt_steps=2.00 halt=0.47 train_steps=1.59 +ep20 val_rocauc=0.60452 val_adapt_rocauc=0.59144 adapt_steps=2.01 halt=0.47 train_steps=1.59 +ep30 val_rocauc=0.71542 val_adapt_rocauc=0.72246 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep40 val_rocauc=0.70211 val_adapt_rocauc=0.68285 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep50 val_rocauc=0.59821 val_adapt_rocauc=0.72487 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep60 val_rocauc=0.64796 val_adapt_rocauc=0.71730 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep70 val_rocauc=0.70277 val_adapt_rocauc=0.73025 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep80 val_rocauc=0.68902 val_adapt_rocauc=0.72341 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep90 val_rocauc=0.72762 val_adapt_rocauc=0.74793 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep100 val_rocauc=0.74125 val_adapt_rocauc=0.75760 adapt_steps=2.00 halt=0.48 train_steps=1.57 +[ogbg-molhiv_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.7412490201842054} test={'rocauc': 0.7254234342107805} adaptive={'rocauc': 0.7567005929044593} steps=2.00024313153416 + wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view gcn --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +ep10 val_rocauc=0.67913 val_adapt_rocauc=0.65745 adapt_steps=2.00 halt=0.47 train_steps=1.60 +ep20 val_rocauc=0.53086 val_adapt_rocauc=0.70728 adapt_steps=2.02 halt=0.47 train_steps=1.59 +ep30 val_rocauc=0.73614 val_adapt_rocauc=0.73784 adapt_steps=2.04 halt=0.48 train_steps=1.57 +ep40 val_rocauc=0.74062 val_adapt_rocauc=0.74468 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep50 val_rocauc=0.64917 val_adapt_rocauc=0.74024 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep60 val_rocauc=0.74111 val_adapt_rocauc=0.74943 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep70 val_rocauc=0.69073 val_adapt_rocauc=0.75506 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep80 val_rocauc=0.75837 val_adapt_rocauc=0.74771 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep90 val_rocauc=0.77126 val_adapt_rocauc=0.75543 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep100 val_rocauc=0.76237 val_adapt_rocauc=0.74920 adapt_steps=2.00 halt=0.48 train_steps=1.57 +[ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.7712620027434841} test={'rocauc': 0.7476081036713725} adaptive={'rocauc': 0.7387782691824871} steps=2.012156576707999 + wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view sgc --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +ep10 val_rocauc=0.56968 val_adapt_rocauc=0.68573 adapt_steps=2.01 halt=0.47 train_steps=1.60 +ep20 val_rocauc=0.65960 val_adapt_rocauc=0.64533 adapt_steps=2.00 halt=0.47 train_steps=1.59 +ep30 val_rocauc=0.73782 val_adapt_rocauc=0.74603 adapt_steps=2.03 halt=0.48 train_steps=1.57 +ep40 val_rocauc=0.70390 val_adapt_rocauc=0.72870 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep50 val_rocauc=0.68717 val_adapt_rocauc=0.73036 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep60 val_rocauc=0.68431 val_adapt_rocauc=0.72508 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep70 val_rocauc=0.69653 val_adapt_rocauc=0.73800 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep80 val_rocauc=0.70493 val_adapt_rocauc=0.74137 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep90 val_rocauc=0.69423 val_adapt_rocauc=0.73412 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep100 val_rocauc=0.69464 val_adapt_rocauc=0.74486 adapt_steps=2.00 halt=0.48 train_steps=1.57 +[ogbg-molhiv_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.7378227268273565} test={'rocauc': 0.7035709457502076} adaptive={'rocauc': 0.724386334228162} steps=2.0269876002917577 + wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view tag --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +ep10 val_rocauc=0.64438 val_adapt_rocauc=0.62773 adapt_steps=2.01 halt=0.47 train_steps=1.60 +ep20 val_rocauc=0.64326 val_adapt_rocauc=0.64524 adapt_steps=2.01 halt=0.47 train_steps=1.61 +ep30 val_rocauc=0.68766 val_adapt_rocauc=0.66943 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep40 val_rocauc=0.63871 val_adapt_rocauc=0.72422 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep50 val_rocauc=0.63257 val_adapt_rocauc=0.73165 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep60 val_rocauc=0.68678 val_adapt_rocauc=0.75939 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep70 val_rocauc=0.73265 val_adapt_rocauc=0.76437 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep80 val_rocauc=0.71019 val_adapt_rocauc=0.75081 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep90 val_rocauc=0.71181 val_adapt_rocauc=0.75327 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep100 val_rocauc=0.72871 val_adapt_rocauc=0.76052 adapt_steps=2.00 halt=0.48 train_steps=1.57 +[ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.7326450127376054} test={'rocauc': 0.759611039224396} adaptive={'rocauc': 0.7786419204696885} steps=2.0 + wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view graphconv --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +ep10 val_rocauc=0.62212 val_adapt_rocauc=0.62817 adapt_steps=2.01 halt=0.47 train_steps=1.60 +ep20 val_rocauc=0.61445 val_adapt_rocauc=0.69759 adapt_steps=2.00 halt=0.47 train_steps=1.59 +ep30 val_rocauc=0.68557 val_adapt_rocauc=0.71732 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep40 val_rocauc=0.47925 val_adapt_rocauc=0.71316 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep50 val_rocauc=0.61766 val_adapt_rocauc=0.69094 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep60 val_rocauc=0.73183 val_adapt_rocauc=0.73302 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep70 val_rocauc=0.72858 val_adapt_rocauc=0.73825 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep80 val_rocauc=0.74850 val_adapt_rocauc=0.74077 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep90 val_rocauc=0.73303 val_adapt_rocauc=0.74217 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep100 val_rocauc=0.73150 val_adapt_rocauc=0.73659 adapt_steps=2.00 halt=0.48 train_steps=1.57 +[ogbg-molhiv_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7484965951401137} test={'rocauc': 0.722140249908264} adaptive={'rocauc': 0.7285405280132873} steps=2.00024313153416 + wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view appnp --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +ep10 val_rocauc=0.70638 val_adapt_rocauc=0.68842 adapt_steps=2.01 halt=0.47 train_steps=1.60 +ep20 val_rocauc=0.64695 val_adapt_rocauc=0.67193 adapt_steps=2.00 halt=0.47 train_steps=1.59 +ep30 val_rocauc=0.71509 val_adapt_rocauc=0.75189 adapt_steps=2.01 halt=0.48 train_steps=1.58 +ep40 val_rocauc=0.65625 val_adapt_rocauc=0.68931 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep50 val_rocauc=0.73236 val_adapt_rocauc=0.74043 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep60 val_rocauc=0.68610 val_adapt_rocauc=0.70942 adapt_steps=2.01 halt=0.48 train_steps=1.58 +ep70 val_rocauc=0.71282 val_adapt_rocauc=0.71800 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep80 val_rocauc=0.70420 val_adapt_rocauc=0.71488 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep90 val_rocauc=0.71668 val_adapt_rocauc=0.72406 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep100 val_rocauc=0.71284 val_adapt_rocauc=0.72607 adapt_steps=2.00 halt=0.48 train_steps=1.57 +[ogbg-molhiv_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.7323571918479326} test={'rocauc': 0.7487070047702736} adaptive={'rocauc': 0.7287433129260897} steps=2.0063214198881596 + wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view pna --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep10 val_rocauc=0.52661 val_adapt_rocauc=0.57540 adapt_steps=2.02 halt=0.47 train_steps=1.60 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep20 val_rocauc=0.53124 val_adapt_rocauc=0.54271 adapt_steps=2.00 halt=0.48 train_steps=1.58 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep30 val_rocauc=0.64086 val_adapt_rocauc=0.71386 adapt_steps=2.00 halt=0.48 train_steps=1.57 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep40 val_rocauc=0.66964 val_adapt_rocauc=0.69129 adapt_steps=2.00 halt=0.48 train_steps=1.58 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep50 val_rocauc=0.63916 val_adapt_rocauc=0.69673 adapt_steps=2.00 halt=0.48 train_steps=1.57 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep60 val_rocauc=0.73238 val_adapt_rocauc=0.74287 adapt_steps=2.00 halt=0.48 train_steps=1.57 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep70 val_rocauc=0.73849 val_adapt_rocauc=0.76782 adapt_steps=2.00 halt=0.48 train_steps=1.57 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep80 val_rocauc=0.72881 val_adapt_rocauc=0.78390 adapt_steps=2.00 halt=0.48 train_steps=1.57 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep90 val_rocauc=0.73387 val_adapt_rocauc=0.77480 adapt_steps=2.00 halt=0.48 train_steps=1.57 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep100 val_rocauc=0.73341 val_adapt_rocauc=0.77625 adapt_steps=2.00 halt=0.48 train_steps=1.57 +[ogbg-molhiv_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.7384932882618068} test={'rocauc': 0.7185075030417737} adaptive={'rocauc': 0.7421078043222156} steps=2.0 + wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view resgated --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +ep10 val_rocauc=0.50096 val_adapt_rocauc=0.63103 adapt_steps=2.00 halt=0.47 train_steps=1.60 +ep20 val_rocauc=0.65405 val_adapt_rocauc=0.70279 adapt_steps=2.00 halt=0.47 train_steps=1.58 +ep30 val_rocauc=0.68276 val_adapt_rocauc=0.65325 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep40 val_rocauc=0.80097 val_adapt_rocauc=0.78965 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep50 val_rocauc=0.77943 val_adapt_rocauc=0.71584 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep60 val_rocauc=0.77564 val_adapt_rocauc=0.75634 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep70 val_rocauc=0.77493 val_adapt_rocauc=0.78545 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep80 val_rocauc=0.77393 val_adapt_rocauc=0.77547 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep90 val_rocauc=0.76533 val_adapt_rocauc=0.76729 adapt_steps=2.00 halt=0.48 train_steps=1.57 +ep100 val_rocauc=0.76010 val_adapt_rocauc=0.76356 adapt_steps=2.00 halt=0.48 train_steps=1.57 +[ogbg-molhiv_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.8009657309425828} test={'rocauc': 0.7787017903010873} adaptive={'rocauc': 0.7875702504876494} steps=2.0 + wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json +[task] ogbg-molbbbp on cuda:3 +[run] ogbg-molbbbp view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gin --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target exact --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:3 --num_workers 0 +Downloading http://snap.stanford.edu/ogb/data/graphproppred/csv_mol_download/bbbp.zip + 0%| | 0/2 [00:00 + main() + ~~~~^^ + File "/home/yurenh2/rrog-gnn-runner/rrog/train_ogb_graphprop.py", line 601, in main + act_state, train_metrics = train_epoch( + ~~~~~~~~~~~^ + model, train_loader, opt, dev, args, act_state, ema_state, ep + 1, metric) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/yurenh2/rrog-gnn-runner/rrog/train_ogb_graphprop.py", line 507, in train_epoch + act_state, m = act_train_step(model, act_state, batch, opt, dev, args, epoch, metric) + ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/yurenh2/rrog-gnn-runner/rrog/train_ogb_graphprop.py", line 412, in act_train_step + raise ValueError(args.halt_target) +ValueError: exact diff --git a/logs/ogbg-molesol_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-molesol_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..cd5a0e1 --- /dev/null +++ b/logs/ogbg-molesol_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,242 @@ +[run] ogbg-molesol view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gin --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.63809 val_adapt_rmse=2.39395 adapt_steps=6.48 halt=0.19 train_steps=3.84 +ep20 val_rmse=4.26988 val_adapt_rmse=3.11447 adapt_steps=3.99 halt=0.16 train_steps=4.33 +ep30 val_rmse=4.14634 val_adapt_rmse=3.52731 adapt_steps=4.76 halt=0.16 train_steps=4.14 +ep40 val_rmse=2.34153 val_adapt_rmse=1.55824 adapt_steps=2.54 halt=0.29 train_steps=2.64 +ep50 val_rmse=2.10126 val_adapt_rmse=1.29124 adapt_steps=2.93 halt=0.34 train_steps=2.23 +ep60 val_rmse=1.97711 val_adapt_rmse=1.38502 adapt_steps=3.55 halt=0.29 train_steps=2.55 +ep70 val_rmse=1.85198 val_adapt_rmse=1.17093 adapt_steps=2.89 halt=0.35 train_steps=2.24 +ep80 val_rmse=1.40467 val_adapt_rmse=0.94661 adapt_steps=2.88 halt=0.37 train_steps=2.11 +ep90 val_rmse=1.51603 val_adapt_rmse=0.96581 adapt_steps=2.71 halt=0.39 train_steps=1.94 +ep100 val_rmse=1.55791 val_adapt_rmse=0.98643 adapt_steps=2.61 halt=0.40 train_steps=1.96 +[ogbg-molesol_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.4046698)} test={'rmse': np.float32(2.0651195)} adaptive={'rmse': np.float32(0.96633816)} steps=2.982300884955752 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gine --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=3.38193 val_adapt_rmse=3.24861 adapt_steps=5.82 halt=0.18 train_steps=4.23 +ep20 val_rmse=2.14610 val_adapt_rmse=1.81691 adapt_steps=4.67 halt=0.18 train_steps=3.98 +ep30 val_rmse=2.42302 val_adapt_rmse=2.12907 adapt_steps=4.80 halt=0.19 train_steps=3.43 +ep40 val_rmse=1.72178 val_adapt_rmse=1.35344 adapt_steps=4.30 halt=0.24 train_steps=3.14 +ep50 val_rmse=2.54499 val_adapt_rmse=1.50567 adapt_steps=2.35 halt=0.30 train_steps=2.66 +ep60 val_rmse=1.52869 val_adapt_rmse=1.10370 adapt_steps=3.33 halt=0.34 train_steps=2.66 +ep70 val_rmse=1.72160 val_adapt_rmse=1.01718 adapt_steps=3.65 halt=0.35 train_steps=2.32 +ep80 val_rmse=1.64223 val_adapt_rmse=1.07042 adapt_steps=2.33 halt=0.38 train_steps=2.24 +ep90 val_rmse=1.31103 val_adapt_rmse=1.01651 adapt_steps=2.51 halt=0.41 train_steps=2.03 +ep100 val_rmse=1.36548 val_adapt_rmse=1.01212 adapt_steps=2.47 halt=0.40 train_steps=2.11 +[ogbg-molesol_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(1.3110343)} test={'rmse': np.float32(2.0394285)} adaptive={'rmse': np.float32(1.0992771)} steps=2.8849557522123894 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gcn --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.02916 val_adapt_rmse=1.75337 adapt_steps=4.50 halt=0.23 train_steps=3.50 +ep20 val_rmse=1.54387 val_adapt_rmse=1.38205 adapt_steps=4.77 halt=0.22 train_steps=3.63 +ep30 val_rmse=1.69653 val_adapt_rmse=1.49022 adapt_steps=4.99 halt=0.22 train_steps=3.20 +ep40 val_rmse=2.92037 val_adapt_rmse=1.90808 adapt_steps=3.73 halt=0.25 train_steps=3.16 +ep50 val_rmse=1.03997 val_adapt_rmse=0.90930 adapt_steps=3.62 halt=0.29 train_steps=2.79 +ep60 val_rmse=1.07837 val_adapt_rmse=1.00303 adapt_steps=3.17 halt=0.39 train_steps=2.10 +ep70 val_rmse=1.16818 val_adapt_rmse=0.92152 adapt_steps=3.02 halt=0.38 train_steps=2.08 +ep80 val_rmse=1.08067 val_adapt_rmse=0.92960 adapt_steps=3.04 halt=0.38 train_steps=2.18 +ep90 val_rmse=1.02939 val_adapt_rmse=0.87992 adapt_steps=2.79 halt=0.40 train_steps=2.00 +ep100 val_rmse=1.04713 val_adapt_rmse=0.88052 adapt_steps=2.70 halt=0.40 train_steps=1.98 +[ogbg-molesol_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(1.0293915)} test={'rmse': np.float32(1.2572919)} adaptive={'rmse': np.float32(0.92217094)} steps=2.7168141592920354 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view graphsage --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.09992 val_adapt_rmse=1.91741 adapt_steps=5.06 halt=0.15 train_steps=4.24 +ep20 val_rmse=1.34611 val_adapt_rmse=1.17463 adapt_steps=3.27 halt=0.20 train_steps=3.81 +ep30 val_rmse=2.05686 val_adapt_rmse=1.52317 adapt_steps=3.48 halt=0.24 train_steps=3.01 +ep40 val_rmse=1.58216 val_adapt_rmse=1.15681 adapt_steps=2.60 halt=0.34 train_steps=2.19 +ep50 val_rmse=1.32595 val_adapt_rmse=1.11669 adapt_steps=3.81 halt=0.24 train_steps=2.77 +ep60 val_rmse=1.68484 val_adapt_rmse=1.33655 adapt_steps=2.79 halt=0.38 train_steps=2.03 +ep70 val_rmse=1.46531 val_adapt_rmse=1.02634 adapt_steps=2.50 halt=0.36 train_steps=2.18 +ep80 val_rmse=1.21621 val_adapt_rmse=0.92526 adapt_steps=2.48 halt=0.40 train_steps=1.95 +ep90 val_rmse=1.15871 val_adapt_rmse=0.92033 adapt_steps=2.41 halt=0.43 train_steps=1.76 +ep100 val_rmse=1.19358 val_adapt_rmse=0.92401 adapt_steps=2.24 halt=0.44 train_steps=1.82 +[ogbg-molesol_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(1.1587086)} test={'rmse': np.float32(1.3228503)} adaptive={'rmse': np.float32(0.9323515)} steps=2.398230088495575 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gatv2 --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.71115 val_adapt_rmse=1.59292 adapt_steps=5.16 halt=0.19 train_steps=3.79 +ep20 val_rmse=2.04041 val_adapt_rmse=1.48254 adapt_steps=3.27 halt=0.19 train_steps=3.61 +ep30 val_rmse=2.19314 val_adapt_rmse=1.41846 adapt_steps=2.98 halt=0.26 train_steps=3.01 +ep40 val_rmse=1.26104 val_adapt_rmse=1.11810 adapt_steps=2.53 halt=0.31 train_steps=2.64 +ep50 val_rmse=1.35004 val_adapt_rmse=1.06584 adapt_steps=3.13 halt=0.32 train_steps=2.50 +ep60 val_rmse=1.14151 val_adapt_rmse=0.91810 adapt_steps=2.64 halt=0.39 train_steps=2.00 +ep70 val_rmse=1.08552 val_adapt_rmse=0.98888 adapt_steps=3.42 halt=0.35 train_steps=2.30 +ep80 val_rmse=1.01822 val_adapt_rmse=0.95246 adapt_steps=2.61 halt=0.44 train_steps=1.82 +ep90 val_rmse=0.98423 val_adapt_rmse=0.94151 adapt_steps=2.59 halt=0.44 train_steps=1.75 +ep100 val_rmse=1.02002 val_adapt_rmse=0.97264 adapt_steps=2.60 halt=0.46 train_steps=1.75 +[ogbg-molesol_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(0.9842344)} test={'rmse': np.float32(0.95342916)} adaptive={'rmse': np.float32(0.88059396)} steps=2.4867256637168142 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view graphconv --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=3.24691 val_adapt_rmse=3.06485 adapt_steps=5.43 halt=0.16 train_steps=4.14 +ep20 val_rmse=2.19544 val_adapt_rmse=1.92386 adapt_steps=4.11 halt=0.22 train_steps=3.14 +ep30 val_rmse=1.85038 val_adapt_rmse=1.84516 adapt_steps=5.91 halt=0.20 train_steps=3.80 +ep40 val_rmse=1.80320 val_adapt_rmse=1.53707 adapt_steps=4.28 halt=0.24 train_steps=3.32 +ep50 val_rmse=1.61943 val_adapt_rmse=1.16471 adapt_steps=4.05 halt=0.34 train_steps=2.62 +ep60 val_rmse=1.38128 val_adapt_rmse=1.12648 adapt_steps=4.63 halt=0.30 train_steps=2.80 +ep70 val_rmse=1.15362 val_adapt_rmse=0.98844 adapt_steps=2.86 halt=0.38 train_steps=2.03 +ep80 val_rmse=1.14805 val_adapt_rmse=1.00274 adapt_steps=3.15 halt=0.43 train_steps=1.82 +ep90 val_rmse=1.14935 val_adapt_rmse=1.02412 adapt_steps=3.17 halt=0.42 train_steps=1.87 +ep100 val_rmse=1.15233 val_adapt_rmse=1.03384 adapt_steps=3.10 halt=0.43 train_steps=1.84 +[ogbg-molesol_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.148049)} test={'rmse': np.float32(1.2080547)} adaptive={'rmse': np.float32(1.0046481)} steps=2.743362831858407 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view transformer --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.80556 val_adapt_rmse=1.57940 adapt_steps=5.16 halt=0.21 train_steps=3.72 +ep20 val_rmse=2.04585 val_adapt_rmse=1.53384 adapt_steps=4.59 halt=0.19 train_steps=3.46 +ep30 val_rmse=2.20692 val_adapt_rmse=1.76335 adapt_steps=2.60 halt=0.24 train_steps=3.17 +ep40 val_rmse=1.06643 val_adapt_rmse=1.01122 adapt_steps=2.19 halt=0.37 train_steps=2.20 +ep50 val_rmse=1.26673 val_adapt_rmse=1.02385 adapt_steps=2.27 halt=0.35 train_steps=2.07 +ep60 val_rmse=1.27758 val_adapt_rmse=1.04181 adapt_steps=2.62 halt=0.34 train_steps=2.26 +ep70 val_rmse=1.27827 val_adapt_rmse=1.01072 adapt_steps=2.54 halt=0.36 train_steps=2.05 +ep80 val_rmse=1.20543 val_adapt_rmse=1.03738 adapt_steps=2.62 halt=0.41 train_steps=1.93 +ep90 val_rmse=1.26838 val_adapt_rmse=1.02284 adapt_steps=2.44 halt=0.44 train_steps=1.75 +ep100 val_rmse=1.23701 val_adapt_rmse=1.02901 adapt_steps=2.45 halt=0.44 train_steps=1.76 +[ogbg-molesol_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rmse': np.float32(1.0664288)} test={'rmse': np.float32(0.95339394)} adaptive={'rmse': np.float32(0.8505217)} steps=2.2831858407079646 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view pna --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep10 val_rmse=2.43831 val_adapt_rmse=2.32531 adapt_steps=5.19 halt=0.16 train_steps=4.00 +ep20 val_rmse=2.56767 val_adapt_rmse=1.59439 adapt_steps=3.97 halt=0.17 train_steps=3.98 +ep30 val_rmse=1.46321 val_adapt_rmse=1.22048 adapt_steps=3.73 halt=0.24 train_steps=3.12 +ep40 val_rmse=1.91382 val_adapt_rmse=1.86215 adapt_steps=3.05 halt=0.22 train_steps=3.11 +ep50 val_rmse=1.55782 val_adapt_rmse=1.32158 adapt_steps=2.92 halt=0.32 train_steps=2.34 +ep60 val_rmse=1.68320 val_adapt_rmse=1.18630 adapt_steps=2.27 halt=0.35 train_steps=2.29 +ep70 val_rmse=1.38794 val_adapt_rmse=1.15712 adapt_steps=2.46 halt=0.33 train_steps=2.29 +ep80 val_rmse=1.28100 val_adapt_rmse=1.02706 adapt_steps=2.46 halt=0.35 train_steps=2.23 +ep90 val_rmse=1.47195 val_adapt_rmse=1.10808 adapt_steps=2.43 halt=0.35 train_steps=2.19 +ep100 val_rmse=1.45332 val_adapt_rmse=1.10590 adapt_steps=2.44 halt=0.35 train_steps=2.21 +[ogbg-molesol_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.2809987)} test={'rmse': np.float32(1.4175682)} adaptive={'rmse': np.float32(0.98294556)} steps=2.601769911504425 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gen --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.68554 val_adapt_rmse=1.40872 adapt_steps=4.66 halt=0.17 train_steps=4.16 +ep20 val_rmse=1.78903 val_adapt_rmse=1.34417 adapt_steps=3.88 halt=0.27 train_steps=2.88 +ep30 val_rmse=1.43062 val_adapt_rmse=1.26301 adapt_steps=2.82 halt=0.29 train_steps=2.68 +ep40 val_rmse=1.26387 val_adapt_rmse=1.08550 adapt_steps=2.36 halt=0.32 train_steps=2.40 +ep50 val_rmse=1.43121 val_adapt_rmse=1.00136 adapt_steps=2.40 halt=0.32 train_steps=2.47 +ep60 val_rmse=1.16224 val_adapt_rmse=1.00159 adapt_steps=2.69 halt=0.32 train_steps=2.49 +ep70 val_rmse=1.36256 val_adapt_rmse=1.13936 adapt_steps=2.18 halt=0.39 train_steps=2.13 +ep80 val_rmse=1.19902 val_adapt_rmse=0.99500 adapt_steps=2.50 halt=0.39 train_steps=1.97 +ep90 val_rmse=1.19996 val_adapt_rmse=1.00030 adapt_steps=2.23 halt=0.41 train_steps=1.93 +ep100 val_rmse=1.16268 val_adapt_rmse=0.98398 adapt_steps=2.26 halt=0.40 train_steps=2.02 +[ogbg-molesol_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rmse': np.float32(1.1622369)} test={'rmse': np.float32(1.4459299)} adaptive={'rmse': np.float32(1.0918992)} steps=2.6106194690265485 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view film --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.15953 val_adapt_rmse=1.69788 adapt_steps=5.27 halt=0.13 train_steps=4.40 +ep20 val_rmse=1.76413 val_adapt_rmse=1.78195 adapt_steps=5.78 halt=0.17 train_steps=4.04 +ep30 val_rmse=1.71072 val_adapt_rmse=1.54898 adapt_steps=4.97 halt=0.15 train_steps=3.94 +ep40 val_rmse=1.73032 val_adapt_rmse=1.23604 adapt_steps=4.69 halt=0.19 train_steps=3.30 +ep50 val_rmse=1.80233 val_adapt_rmse=1.54453 adapt_steps=4.03 halt=0.23 train_steps=3.17 +ep60 val_rmse=2.03690 val_adapt_rmse=1.28646 adapt_steps=3.64 halt=0.22 train_steps=3.11 +ep70 val_rmse=1.81923 val_adapt_rmse=1.44603 adapt_steps=4.35 halt=0.20 train_steps=3.30 +ep80 val_rmse=1.36738 val_adapt_rmse=1.27507 adapt_steps=4.00 halt=0.28 train_steps=2.75 +ep90 val_rmse=1.47914 val_adapt_rmse=1.26687 adapt_steps=3.88 halt=0.27 train_steps=2.67 +ep100 val_rmse=1.56815 val_adapt_rmse=1.29753 adapt_steps=3.90 halt=0.28 train_steps=2.80 +[ogbg-molesol_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.3673769)} test={'rmse': np.float32(1.364793)} adaptive={'rmse': np.float32(1.12864)} steps=3.6106194690265485 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view resgated --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.01199 val_adapt_rmse=1.99778 adapt_steps=6.58 halt=0.17 train_steps=4.21 +ep20 val_rmse=2.81354 val_adapt_rmse=1.57554 adapt_steps=3.77 halt=0.24 train_steps=3.39 +ep30 val_rmse=2.27715 val_adapt_rmse=1.78467 adapt_steps=2.41 halt=0.31 train_steps=2.96 +ep40 val_rmse=2.06149 val_adapt_rmse=1.59902 adapt_steps=4.17 halt=0.25 train_steps=2.81 +ep50 val_rmse=1.25669 val_adapt_rmse=1.02207 adapt_steps=3.41 halt=0.33 train_steps=2.60 +ep60 val_rmse=1.24545 val_adapt_rmse=1.02109 adapt_steps=3.96 halt=0.38 train_steps=2.21 +ep70 val_rmse=1.11263 val_adapt_rmse=0.97278 adapt_steps=2.63 halt=0.47 train_steps=1.62 +ep80 val_rmse=1.21134 val_adapt_rmse=1.06008 adapt_steps=3.45 halt=0.41 train_steps=1.89 +ep90 val_rmse=1.09389 val_adapt_rmse=0.97993 adapt_steps=3.27 halt=0.41 train_steps=1.90 +ep100 val_rmse=1.14293 val_adapt_rmse=1.00867 adapt_steps=3.06 halt=0.44 train_steps=1.83 +[ogbg-molesol_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(1.0938909)} test={'rmse': np.float32(1.0833443)} adaptive={'rmse': np.float32(0.9181242)} steps=3.230088495575221 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view tag --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=3.47158 val_adapt_rmse=2.85814 adapt_steps=6.48 halt=0.15 train_steps=4.28 +ep20 val_rmse=2.59229 val_adapt_rmse=2.29301 adapt_steps=4.50 halt=0.19 train_steps=3.54 +ep30 val_rmse=1.38104 val_adapt_rmse=1.23529 adapt_steps=3.79 halt=0.17 train_steps=4.02 +ep40 val_rmse=1.62549 val_adapt_rmse=1.31054 adapt_steps=3.39 halt=0.24 train_steps=3.04 +ep50 val_rmse=1.17882 val_adapt_rmse=1.00373 adapt_steps=3.59 halt=0.26 train_steps=2.89 +ep60 val_rmse=1.11478 val_adapt_rmse=1.01010 adapt_steps=2.65 halt=0.36 train_steps=2.17 +ep70 val_rmse=1.21310 val_adapt_rmse=1.04888 adapt_steps=2.49 halt=0.35 train_steps=2.14 +ep80 val_rmse=1.13492 val_adapt_rmse=1.00575 adapt_steps=2.39 halt=0.40 train_steps=1.92 +ep90 val_rmse=1.10848 val_adapt_rmse=0.98178 adapt_steps=2.41 halt=0.39 train_steps=1.99 +ep100 val_rmse=1.08712 val_adapt_rmse=0.96400 adapt_steps=2.39 halt=0.44 train_steps=1.82 +[ogbg-molesol_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rmse': np.float32(1.087122)} test={'rmse': np.float32(1.2508167)} adaptive={'rmse': np.float32(1.0189501)} steps=2.353982300884956 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view sgc --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.13452 val_adapt_rmse=1.54890 adapt_steps=4.80 halt=0.18 train_steps=4.20 +ep20 val_rmse=1.80887 val_adapt_rmse=1.55135 adapt_steps=4.19 halt=0.20 train_steps=3.79 +ep30 val_rmse=1.56727 val_adapt_rmse=1.38135 adapt_steps=3.77 halt=0.28 train_steps=3.18 +ep40 val_rmse=1.44096 val_adapt_rmse=1.19056 adapt_steps=5.21 halt=0.21 train_steps=3.29 +ep50 val_rmse=1.27696 val_adapt_rmse=1.20518 adapt_steps=2.98 halt=0.28 train_steps=2.83 +ep60 val_rmse=1.03453 val_adapt_rmse=1.03118 adapt_steps=3.41 halt=0.29 train_steps=2.72 +ep70 val_rmse=1.36152 val_adapt_rmse=1.19328 adapt_steps=2.70 halt=0.37 train_steps=2.20 +ep80 val_rmse=1.10044 val_adapt_rmse=1.00095 adapt_steps=2.53 halt=0.41 train_steps=1.89 +ep90 val_rmse=1.09772 val_adapt_rmse=1.00221 adapt_steps=2.59 halt=0.43 train_steps=1.80 +ep100 val_rmse=1.08154 val_adapt_rmse=1.01459 adapt_steps=2.57 halt=0.42 train_steps=1.90 +[ogbg-molesol_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rmse': np.float32(1.0345254)} test={'rmse': np.float32(1.0465622)} adaptive={'rmse': np.float32(0.97806746)} steps=3.2831858407079646 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view cheb --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.61304 val_adapt_rmse=1.41832 adapt_steps=3.95 halt=0.23 train_steps=3.80 +ep20 val_rmse=2.75789 val_adapt_rmse=2.14843 adapt_steps=3.42 halt=0.25 train_steps=3.13 +ep30 val_rmse=1.83964 val_adapt_rmse=1.52535 adapt_steps=3.04 halt=0.22 train_steps=3.33 +ep40 val_rmse=1.78527 val_adapt_rmse=1.47363 adapt_steps=2.77 halt=0.34 train_steps=2.29 +ep50 val_rmse=1.79619 val_adapt_rmse=1.39923 adapt_steps=2.56 halt=0.46 train_steps=1.75 +ep60 val_rmse=1.55892 val_adapt_rmse=1.29826 adapt_steps=2.79 halt=0.40 train_steps=2.14 +ep70 val_rmse=1.21742 val_adapt_rmse=1.01859 adapt_steps=2.35 halt=0.43 train_steps=1.82 +ep80 val_rmse=1.06434 val_adapt_rmse=0.91884 adapt_steps=2.42 halt=0.44 train_steps=1.73 +ep90 val_rmse=1.08489 val_adapt_rmse=0.95548 adapt_steps=2.42 halt=0.46 train_steps=1.66 +ep100 val_rmse=1.08888 val_adapt_rmse=0.95485 adapt_steps=2.50 halt=0.46 train_steps=1.74 +[ogbg-molesol_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.0643402)} test={'rmse': np.float32(1.034204)} adaptive={'rmse': np.float32(0.8497807)} steps=2.601769911504425 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view arma --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=4.56663 val_adapt_rmse=3.60617 adapt_steps=2.74 halt=0.19 train_steps=3.89 +ep20 val_rmse=1.79390 val_adapt_rmse=1.59002 adapt_steps=3.36 halt=0.18 train_steps=3.97 +ep30 val_rmse=2.24326 val_adapt_rmse=1.60470 adapt_steps=3.49 halt=0.18 train_steps=3.64 +ep40 val_rmse=1.96715 val_adapt_rmse=1.62786 adapt_steps=2.96 halt=0.23 train_steps=3.09 +ep50 val_rmse=1.30996 val_adapt_rmse=1.07779 adapt_steps=2.49 halt=0.31 train_steps=2.61 +ep60 val_rmse=1.59369 val_adapt_rmse=1.15346 adapt_steps=2.60 halt=0.31 train_steps=2.58 +ep70 val_rmse=1.33600 val_adapt_rmse=1.06852 adapt_steps=2.23 halt=0.39 train_steps=2.12 +ep80 val_rmse=1.51381 val_adapt_rmse=1.08174 adapt_steps=2.51 halt=0.36 train_steps=2.25 +ep90 val_rmse=1.57786 val_adapt_rmse=1.05584 adapt_steps=2.32 halt=0.37 train_steps=2.15 +ep100 val_rmse=1.51730 val_adapt_rmse=1.01467 adapt_steps=2.27 halt=0.39 train_steps=2.00 +[ogbg-molesol_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rmse': np.float32(1.3099641)} test={'rmse': np.float32(1.5309947)} adaptive={'rmse': np.float32(1.0385827)} steps=2.575221238938053 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view mf --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=3.91043 val_adapt_rmse=3.93609 adapt_steps=7.12 halt=0.15 train_steps=4.32 +ep20 val_rmse=1.56765 val_adapt_rmse=1.40924 adapt_steps=3.93 halt=0.21 train_steps=3.97 +ep30 val_rmse=2.21943 val_adapt_rmse=1.92857 adapt_steps=4.80 halt=0.21 train_steps=3.70 +ep40 val_rmse=1.34838 val_adapt_rmse=1.13183 adapt_steps=2.79 halt=0.24 train_steps=2.98 +ep50 val_rmse=2.04182 val_adapt_rmse=1.18497 adapt_steps=3.55 halt=0.32 train_steps=2.48 +ep60 val_rmse=1.07650 val_adapt_rmse=1.06298 adapt_steps=3.69 halt=0.38 train_steps=2.00 +ep70 val_rmse=1.17131 val_adapt_rmse=1.05686 adapt_steps=3.22 halt=0.40 train_steps=2.01 +ep80 val_rmse=1.16899 val_adapt_rmse=1.03185 adapt_steps=4.14 halt=0.37 train_steps=2.18 +ep90 val_rmse=1.09374 val_adapt_rmse=1.03779 adapt_steps=3.41 halt=0.41 train_steps=1.92 +ep100 val_rmse=1.13886 val_adapt_rmse=1.05515 adapt_steps=3.32 halt=0.42 train_steps=1.92 +[ogbg-molesol_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rmse': np.float32(1.0765038)} test={'rmse': np.float32(1.0843762)} adaptive={'rmse': np.float32(0.95887977)} steps=3.4070796460176993 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view appnp --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=5.21048 val_adapt_rmse=2.38789 adapt_steps=5.34 halt=0.15 train_steps=4.20 +ep20 val_rmse=2.82679 val_adapt_rmse=2.25175 adapt_steps=6.12 halt=0.18 train_steps=3.93 +ep30 val_rmse=1.68909 val_adapt_rmse=1.41500 adapt_steps=4.84 halt=0.19 train_steps=3.72 +ep40 val_rmse=2.08134 val_adapt_rmse=1.83294 adapt_steps=4.53 halt=0.20 train_steps=3.51 +ep50 val_rmse=1.95089 val_adapt_rmse=1.48969 adapt_steps=3.67 halt=0.26 train_steps=2.94 +ep60 val_rmse=1.80235 val_adapt_rmse=1.37428 adapt_steps=3.46 halt=0.33 train_steps=2.30 +ep70 val_rmse=1.62703 val_adapt_rmse=1.25301 adapt_steps=2.74 halt=0.42 train_steps=1.88 +ep80 val_rmse=1.70083 val_adapt_rmse=1.27133 adapt_steps=2.71 halt=0.39 train_steps=2.06 +ep90 val_rmse=1.71529 val_adapt_rmse=1.30814 adapt_steps=2.67 halt=0.40 train_steps=1.94 +ep100 val_rmse=1.69038 val_adapt_rmse=1.31634 adapt_steps=2.68 halt=0.40 train_steps=1.95 +[ogbg-molesol_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rmse': np.float32(1.6270279)} test={'rmse': np.float32(1.2973164)} adaptive={'rmse': np.float32(1.0733075)} steps=2.814159292035398 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json diff --git a/logs/ogbg-molfreesolv_0.log b/logs/ogbg-molfreesolv_0.log new file mode 100644 index 0000000..d163fe6 --- /dev/null +++ b/logs/ogbg-molfreesolv_0.log @@ -0,0 +1,791 @@ +[run] ogbg-molfreesolv view=gin compute=classic T=0 ns=1 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molfreesolv --view gin --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1 +Downloading http://snap.stanford.edu/ogb/data/graphproppred/csv_mol_download/freesolv.zip + 0%| | 0/2 [00:00 list[str]: + spec = find_run_spec(args.task, args.view, args.compute, args.modifier) + run_args = dict(spec.default_args) + for key in [ + "epochs", "hidden", "bs", "seed", "T", "n_sup", "halt_max_steps", "halt_target", + "halt_min_steps", "halt_loss_threshold", "halt_exploration_prob", "q_warmup_epochs", + "act_train_mode", + "eval_every", "max_train_batches", "max_eval_batches", "num_workers", "ema", "lr", "lam_q", + "device", + ]: + value = getattr(args, key) + if value is not None: + run_args[key] = value + run_args["compute"] = args.compute + return spec.command_builder(run_args) + + +def print_matrix(args): + tasks = [b for b in BENCHMARKS if args.tier == "all" or b.tier == args.tier] + tasks = sorted(tasks, key=lambda x: x.priority)[:args.limit_tasks] + + if args.kind == "main": + views = sorted(VIEWS, key=lambda x: x.priority)[:args.limit_views] + computes = [c for c in COMPUTES if c.name in ["classic", "view-only", "fixed-rrog", "rrog-act"]] + for task in tasks: + for view in views: + for compute in computes: + try: + find_run_spec(task.name, view.name, compute.name) + status = "implemented" + except KeyError: + status = "planned" + print(f"{task.name}\t{view.name}\t{compute.name}\tnone\t{status}") + return + + if args.kind == "modifier": + task_names = {"zinc-cycle56", "ogbg-molhiv", "peptides-struct", "peptides-func", "ogbn-arxiv", "qm9"} + mods = [m for m in sorted(MODIFIERS, key=lambda x: x.priority) if m.name != "none"] + for task in tasks: + if task.name not in task_names: + continue + for mod in mods: + print(f"{task.name}\tgin\tview-only\t{mod.name}\tplanned") + return + + raise ValueError(args.kind) + + +def main(): + ap = argparse.ArgumentParser() + sub = ap.add_subparsers(dest="cmd", required=True) + + lp = sub.add_parser("list") + lp.add_argument("axis", choices=["benchmarks", "views", "computes", "modifiers"]) + lp.add_argument("--json", action="store_true") + + rp = sub.add_parser("run") + rp.add_argument("--task", default="zinc-cycle56") + rp.add_argument("--view", default="gin") + rp.add_argument("--compute", default="rrog-act") + rp.add_argument("--modifier", default="none") + rp.add_argument("--epochs", type=int) + rp.add_argument("--hidden", type=int) + rp.add_argument("--bs", type=int) + rp.add_argument("--seed", type=int) + rp.add_argument("--T", type=int) + rp.add_argument("--n_sup", type=int) + rp.add_argument("--halt_max_steps", type=int) + rp.add_argument("--halt_target", choices=["soft", "binary", "exact", "loss"]) + rp.add_argument("--halt_min_steps", type=int) + rp.add_argument("--halt_loss_threshold", type=float) + rp.add_argument("--halt_exploration_prob", type=float) + rp.add_argument("--q_warmup_epochs", type=int) + rp.add_argument("--act_train_mode", choices=["stream", "trace"]) + rp.add_argument("--eval_every", type=int) + rp.add_argument("--max_train_batches", type=int) + rp.add_argument("--max_eval_batches", type=int) + rp.add_argument("--num_workers", type=int) + rp.add_argument("--ema", type=float) + rp.add_argument("--lr", type=float) + rp.add_argument("--lam_q", type=float) + rp.add_argument("--device") + rp.add_argument("--dry-run", action="store_true") + + mp = sub.add_parser("matrix") + mp.add_argument("--kind", choices=["main", "modifier"], default="main") + mp.add_argument("--tier", choices=["A", "B", "C", "all"], default="A") + mp.add_argument("--limit-tasks", type=int, default=20) + mp.add_argument("--limit-views", type=int, default=6) + + op = sub.add_parser("results") + op.add_argument("--runs-dir", default="runs") + op.add_argument("--glob", default="*.json") + op.add_argument("--min-epochs", type=int, default=10) + op.add_argument("--epochs", type=int) + op.add_argument("--digits", type=int, default=4) + + zp = sub.add_parser("zinc-results") + zp.add_argument("--runs-dir", default="runs") + zp.add_argument("--epochs", type=int) + zp.add_argument("--min-epochs", type=int, default=10) + zp.add_argument("--digits", type=int, default=4) + + args = ap.parse_args() + if args.cmd == "list": + list_axis(args.axis, args.json) + return + if args.cmd == "matrix": + print_matrix(args) + return + if args.cmd == "results": + print_tables(args) + return + if args.cmd == "zinc-results": + print_zinc(args) + return + + cmd = build_command(args) + env = dict(os.environ) + env["PYTHONPATH"] = os.getcwd() + os.pathsep + env.get("PYTHONPATH", "") + print(" ".join(cmd), flush=True) + if not args.dry_run: + raise SystemExit(subprocess.call(cmd, env=env)) + + +if __name__ == "__main__": + try: + main() + except BrokenPipeError: + raise SystemExit(0) diff --git a/rrog/collect_results.py b/rrog/collect_results.py new file mode 100644 index 0000000..85925ba --- /dev/null +++ b/rrog/collect_results.py @@ -0,0 +1,267 @@ +import argparse +import json +import math +from collections import defaultdict +from pathlib import Path + + +HIGHER_BETTER = { + "accuracy", + "ap", + "auc", + "f1", + "mrr", + "rocauc", +} + +LOWER_BETTER = { + "mae", + "raw-mae", + "rmse", +} + + +def _metric_direction(metric: str) -> int: + metric = metric.lower() + if metric in HIGHER_BETTER: + return 1 + if metric in LOWER_BETTER: + return -1 + if "mae" in metric or "rmse" in metric: + return -1 + return 1 + + +def _read(path: Path) -> dict | None: + try: + with path.open() as f: + rep = json.load(f) + except (OSError, json.JSONDecodeError): + return None + required = {"dataset", "view", "compute", "seed", "metric", "val"} + if not required.issubset(rep): + return None + return rep + + +def _score(rep: dict, split: str) -> float | None: + metric = rep.get("metric") + if not metric: + return None + value = rep.get(split, {}).get(metric) + if value is None: + return None + return float(value) + + +def _rank_key(rep: dict) -> tuple[int, int, int]: + return ( + int(rep.get("epochs", 0)), + int(rep.get("hidden", 0)), + int(rep.get("ep", 0) or 0), + ) + + +def _mean(xs: list[float]) -> float: + return sum(xs) / len(xs) + + +def _std(xs: list[float]) -> float: + if len(xs) < 2: + return 0.0 + mu = _mean(xs) + return math.sqrt(sum((x - mu) ** 2 for x in xs) / (len(xs) - 1)) + + +def _fmt(value: float | None, digits: int) -> str: + if value is None: + return "" + return f"{value:.{digits}f}" + + +def _is_classic_baseline(rep: dict) -> bool: + return rep.get("compute") == "classic" and int(rep.get("T", -1)) == 0 and int(rep.get("n_sup", -1)) == 1 + + +def _compute_label(rep: dict) -> str: + compute = str(rep["compute"]) + if _is_classic_baseline(rep): + label = "classic" + elif compute == "rrog-act": + target = str(rep.get("halt_target", "")) + if target == "loss": + target += f"{float(rep.get('halt_loss_threshold', 0.0) or 0.0):g}" + label = ( + f"{compute}-{rep.get('act_train_mode', 'stream')}-T{rep.get('T')}-ns{rep.get('n_sup')}" + f"-hm{rep.get('halt_max_steps')}-min{rep.get('halt_min_steps')}" + f"-{target}-lq{float(rep.get('lam_q', 0.0) or 0.0):g}" + f"-hex{float(rep.get('halt_exploration_prob', 0.0) or 0.0):g}" + f"-qw{rep.get('q_warmup_epochs', 0)}" + ) + else: + label = f"{compute}-T{rep.get('T')}-ns{rep.get('n_sup')}" + ema = float(rep.get("ema", 0.0) or 0.0) + if ema > 0: + label += f"+ema{ema:g}" + return label + + +def _choose_runs(paths: list[Path], min_epochs: int, epochs: int | None) -> list[dict]: + candidates: dict[tuple[str, str, str, int], dict] = {} + for path in paths: + rep = _read(path) + if rep is None: + continue + if epochs is not None and int(rep.get("epochs", -1)) != epochs: + continue + if int(rep.get("epochs", 0)) < min_epochs: + continue + val = _score(rep, "val") + test = _score(rep, "test") + if val is None or test is None: + continue + key = (str(rep["dataset"]), str(rep["view"]), _compute_label(rep), int(rep["seed"])) + old = candidates.get(key) + if old is None or _rank_key(rep) > _rank_key(old): + candidates[key] = rep + return list(candidates.values()) + + +def _group_by_cell(runs: list[dict]) -> dict[tuple[str, str, str], list[dict]]: + grouped: dict[tuple[str, str, str], list[dict]] = defaultdict(list) + for rep in runs: + grouped[(str(rep["dataset"]), str(rep["view"]), _compute_label(rep))].append(rep) + return dict(grouped) + + +def _summarize_cell(reps: list[dict], split: str) -> tuple[float, float, int]: + scores = [_score(rep, split) for rep in reps] + xs = [x for x in scores if x is not None] + return _mean(xs), _std(xs), len(xs) + + +def _markdown_table(headers: list[str], rows: list[list[str]]) -> str: + out = ["| " + " | ".join(headers) + " |", "| " + " | ".join(["---"] * len(headers)) + " |"] + out.extend("| " + " | ".join(row) + " |" for row in rows) + return "\n".join(out) + + +def print_tables(args) -> None: + paths = sorted(Path(args.runs_dir).glob(args.glob)) + runs = _choose_runs(paths, args.min_epochs, args.epochs) + grouped = _group_by_cell(runs) + + classic_cells = { + (task, view): reps + for (task, view, compute), reps in grouped.items() + if compute == "classic" + for reps in [[rep for rep in reps if _is_classic_baseline(rep)]] + if reps + } + + baseline_rows = [] + for (task, view), reps in sorted(classic_cells.items()): + metric = str(reps[0]["metric"]) + val_mu, val_sd, n = _summarize_cell(reps, "val") + test_mu, test_sd, _ = _summarize_cell(reps, "test") + baseline_rows.append([ + task, + view, + metric, + str(n), + f"{_fmt(val_mu, args.digits)} +/- {_fmt(val_sd, args.digits)}", + f"{_fmt(test_mu, args.digits)} +/- {_fmt(test_sd, args.digits)}", + ]) + + delta_rows = [] + for (task, view, compute), reps in sorted(grouped.items()): + if compute == "classic": + continue + base = classic_cells.get((task, view)) + if not base: + continue + metric = str(reps[0]["metric"]) + direction = _metric_direction(metric) + base_by_seed = {int(rep["seed"]): rep for rep in base} + paired = [] + for rep in reps: + seed = int(rep["seed"]) + if seed in base_by_seed: + paired.append((rep, base_by_seed[seed])) + if not paired: + base_test_mu, _, _ = _summarize_cell(base, "test") + base_val_mu, _, _ = _summarize_cell(base, "val") + paired = [(rep, None) for rep in reps] + else: + base_test_mu = None + base_val_mu = None + + val_scores, test_scores, val_deltas, test_deltas = [], [], [], [] + adaptive_test_scores, adaptive_test_deltas = [], [] + adaptive_steps = [] + for rep, base_rep in paired: + val = _score(rep, "val") + test = _score(rep, "test") + if val is None or test is None: + continue + if base_rep is None: + base_val = base_val_mu + base_test = base_test_mu + else: + base_val = _score(base_rep, "val") + base_test = _score(base_rep, "test") + if base_val is None or base_test is None: + continue + val_scores.append(val) + test_scores.append(test) + val_deltas.append(direction * (val - base_val)) + test_deltas.append(direction * (test - base_test)) + adaptive_test = _score(rep, "test_adaptive") + if adaptive_test is not None: + adaptive_test_scores.append(adaptive_test) + adaptive_test_deltas.append(direction * (adaptive_test - base_test)) + if rep.get("adaptive_steps") is not None: + adaptive_steps.append(float(rep["adaptive_steps"])) + + if not test_scores: + continue + adaptive_test_cell = "" + if adaptive_test_scores: + adaptive_test_cell = ( + f"{_fmt(_mean(adaptive_test_scores), args.digits)} " + f"({_fmt(_mean(adaptive_test_deltas), args.digits)})" + ) + delta_rows.append([ + task, + view, + compute, + metric, + str(len(test_scores)), + f"{_fmt(_mean(val_scores), args.digits)} ({_fmt(_mean(val_deltas), args.digits)})", + f"{_fmt(_mean(test_scores), args.digits)} ({_fmt(_mean(test_deltas), args.digits)})", + adaptive_test_cell, + _fmt(_mean(adaptive_steps), 2) if adaptive_steps else "", + ]) + + print("\nClassic baseline: task x backbone") + print(_markdown_table(["task", "backbone", "metric", "n", "val", "test"], baseline_rows)) + print("\nDelta vs matching classic") + print(_markdown_table([ + "task", "backbone", "compute", "metric", "n", "val score (delta)", "test score (delta)", + "adaptive test (delta)", "steps" + ], delta_rows)) + + +def main() -> None: + ap = argparse.ArgumentParser() + ap.add_argument("--runs-dir", default="runs") + ap.add_argument("--glob", default="*.json") + ap.add_argument("--min-epochs", type=int, default=10) + ap.add_argument("--epochs", type=int) + ap.add_argument("--digits", type=int, default=4) + args = ap.parse_args() + print_tables(args) + + +if __name__ == "__main__": + main() diff --git a/rrog/collect_zinc.py b/rrog/collect_zinc.py new file mode 100644 index 0000000..49ae1e9 --- /dev/null +++ b/rrog/collect_zinc.py @@ -0,0 +1,137 @@ +import argparse +import json +import math +from collections import defaultdict +from pathlib import Path + + +def _read(path: Path) -> dict | None: + try: + with path.open() as f: + rep = json.load(f) + except (OSError, json.JSONDecodeError): + return None + if rep.get("dataset") != "ZINC-cycle56": + return None + if rep.get("K") != 1 or rep.get("select") != "none" or float(rep.get("sigma", 0.0)) != 0.0: + return None + if "test_mae" not in rep or "val_mae" not in rep: + return None + return rep + + +def _compute(rep: dict) -> str: + if rep.get("act"): + return f"rrog-act-T{rep.get('T')}-ns{rep.get('n_sup')}" + if int(rep.get("T", -1)) == 0 and int(rep.get("n_sup", -1)) == 1: + return "classic" + label = f"fixed-rrog-T{rep.get('T')}-ns{rep.get('n_sup')}" + if rep.get("loss_mode") == "trace": + label += "+trace" + return label + + +def _view(rep: dict) -> str: + return str(rep.get("view", "gin")) + + +def _score(rep: dict, split: str) -> float: + return float(sum(rep[f"{split}_mae"])) + + +def _mean(xs: list[float]) -> float: + return sum(xs) / len(xs) + + +def _std(xs: list[float]) -> float: + if len(xs) < 2: + return 0.0 + mu = _mean(xs) + return math.sqrt(sum((x - mu) ** 2 for x in xs) / (len(xs) - 1)) + + +def _fmt(x: float, digits: int) -> str: + return f"{x:.{digits}f}" + + +def _markdown(headers: list[str], rows: list[list[str]]) -> str: + lines = ["| " + " | ".join(headers) + " |", "| " + " | ".join(["---"] * len(headers)) + " |"] + lines.extend("| " + " | ".join(row) + " |" for row in rows) + return "\n".join(lines) + + +def print_zinc(args) -> None: + by_cell: dict[tuple[str, str, int], dict] = {} + for path in sorted(Path(args.runs_dir).glob("rec_rrog*_sig0.0_K1_none_T*_s*.json")): + rep = _read(path) + if rep is None: + continue + if args.epochs is not None and int(rep.get("epochs", -1)) != args.epochs: + continue + if int(rep.get("epochs", 0)) < args.min_epochs: + continue + key = (_view(rep), _compute(rep), int(rep["seed"])) + old = by_cell.get(key) + if old is None or int(rep.get("epochs", 0)) > int(old.get("epochs", 0)): + by_cell[key] = rep + + grouped: dict[tuple[str, str], list[dict]] = defaultdict(list) + for rep in by_cell.values(): + grouped[(_view(rep), _compute(rep))].append(rep) + + classic_by_view = { + view: reps + for (view, compute), reps in grouped.items() + if compute == "classic" + } + + base_rows = [] + for view, classic in sorted(classic_by_view.items()): + vals = [_score(rep, "val") for rep in classic] + tests = [_score(rep, "test") for rep in classic] + base_rows.append([ + "zinc-cycle56", + view, + str(len(classic)), + f"{_fmt(_mean(vals), args.digits)} +/- {_fmt(_std(vals), args.digits)}", + f"{_fmt(_mean(tests), args.digits)} +/- {_fmt(_std(tests), args.digits)}", + ]) + + delta_rows = [] + for (view, compute), reps in sorted(grouped.items()): + if compute == "classic": + continue + base_by_seed = {int(rep["seed"]): rep for rep in classic_by_view.get(view, [])} + paired = [(rep, base_by_seed[int(rep["seed"])]) for rep in reps if int(rep["seed"]) in base_by_seed] + if not paired: + continue + vals = [_score(rep, "val") for rep, _ in paired] + tests = [_score(rep, "test") for rep, _ in paired] + val_deltas = [_score(base, "val") - _score(rep, "val") for rep, base in paired] + test_deltas = [_score(base, "test") - _score(rep, "test") for rep, base in paired] + delta_rows.append([ + "zinc-cycle56", + view, + compute, + str(len(paired)), + f"{_fmt(_mean(vals), args.digits)} ({_fmt(_mean(val_deltas), args.digits)})", + f"{_fmt(_mean(tests), args.digits)} ({_fmt(_mean(test_deltas), args.digits)})", + ]) + + print("\nZINC-cycle56 classic baseline") + print(_markdown(["task", "backbone", "n", "val MAE-sum", "test MAE-sum"], base_rows)) + print("\nZINC-cycle56 delta vs matching classic") + print(_markdown(["task", "backbone", "compute", "n", "val score (improvement)", "test score (improvement)"], delta_rows)) + + +def main() -> None: + ap = argparse.ArgumentParser() + ap.add_argument("--runs-dir", default="runs") + ap.add_argument("--epochs", type=int) + ap.add_argument("--min-epochs", type=int, default=10) + ap.add_argument("--digits", type=int, default=4) + print_zinc(ap.parse_args()) + + +if __name__ == "__main__": + main() diff --git a/rrog/registry.py b/rrog/registry.py new file mode 100644 index 0000000..7f6b6fe --- /dev/null +++ b/rrog/registry.py @@ -0,0 +1,57 @@ +from dataclasses import dataclass, field +from typing import Callable + + +@dataclass(frozen=True) +class BenchmarkSpec: + name: str + tier: str + domain: str + task_type: str + metric: str + priority: int + status: str = "planned" + notes: str = "" + + +@dataclass(frozen=True) +class ViewSpec: + name: str + family: str + graph_type: str + priority: int + status: str = "planned" + notes: str = "" + + +@dataclass(frozen=True) +class ComputeSpec: + name: str + family: str + priority: int + status: str = "planned" + notes: str = "" + + +@dataclass(frozen=True) +class ModifierSpec: + name: str + family: str + priority: int + status: str = "planned" + notes: str = "" + + +@dataclass(frozen=True) +class RunSpec: + task: str + view: str + compute: str + modifier: str = "none" + default_args: dict[str, object] = field(default_factory=dict) + command_builder: Callable[[dict[str, object]], list[str]] | None = None + + +def by_name(items): + return {item.name: item for item in items} + diff --git a/rrog/run_ogb_hiv_remaining.sh b/rrog/run_ogb_hiv_remaining.sh new file mode 100755 index 0000000..067e736 --- /dev/null +++ b/rrog/run_ogb_hiv_remaining.sh @@ -0,0 +1,49 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +DEVICE="${DEVICE:-cuda:3}" +EPOCHS="${EPOCHS:-100}" +SEED="${SEED:-0}" + +run_if_missing() { + local view="$1" + local compute="$2" + local t="$3" + local ns="$4" + local out="runs/ogbg-molhiv_${view}_${compute}_T${t}_ns${ns}_h128_e${EPOCHS}_s${SEED}.json" + if [[ -f "${out}" ]]; then + echo "[skip] ${out}" + return + fi + echo "[run] view=${view} compute=${compute} T=${t} ns=${ns} device=${DEVICE}" + python3 -m rrog.cli run \ + --task ogbg-molhiv \ + --view "${view}" \ + --compute "${compute}" \ + --epochs "${EPOCHS}" \ + --T "${t}" \ + --n_sup "${ns}" \ + --seed "${SEED}" \ + --device "${DEVICE}" +} + +# Complete remaining OGB-HIV backbone x {classic, fixed-RRoG} cells. +# Existing json files are skipped, so the queue can be restarted safely. +run_if_missing sgc fixed-rrog 3 3 +run_if_missing cheb classic 0 1 +run_if_missing cheb fixed-rrog 3 3 +run_if_missing arma classic 0 1 +run_if_missing arma fixed-rrog 3 3 +run_if_missing mf classic 0 1 +run_if_missing mf fixed-rrog 3 3 +run_if_missing appnp classic 0 1 +run_if_missing appnp fixed-rrog 3 3 +run_if_missing pna fixed-rrog 3 3 +run_if_missing gine classic 0 1 +run_if_missing gine fixed-rrog 3 3 + +python3 -m rrog.cli results --epochs "${EPOCHS}" diff --git a/rrog/run_zinc_gine.sh b/rrog/run_zinc_gine.sh new file mode 100755 index 0000000..1ca36e1 --- /dev/null +++ b/rrog/run_zinc_gine.sh @@ -0,0 +1,36 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +DEVICE="${DEVICE:-cuda:3}" +EPOCHS="${EPOCHS:-200}" +SEED="${SEED:-0}" + +run_if_missing() { + local compute="$1" + local t="$2" + local ns="$3" + local out="runs/rec_rrog_gine_full_sig0.0_K1_none_T${t}_ns${ns}_trace_s${SEED}.json" + if [[ -f "${out}" ]]; then + echo "[skip] ${out}" + return + fi + echo "[run] zinc-cycle56 view=gine compute=${compute} T=${t} ns=${ns} device=${DEVICE}" + python3 -m rrog.cli run \ + --task zinc-cycle56 \ + --view gine \ + --compute "${compute}" \ + --epochs "${EPOCHS}" \ + --T "${t}" \ + --n_sup "${ns}" \ + --seed "${SEED}" \ + --device "${DEVICE}" +} + +run_if_missing classic 0 1 +run_if_missing fixed-rrog 1 3 + +python3 -m rrog.cli zinc-results --epochs "${EPOCHS}" diff --git a/rrog/run_zinc_gine_after_pid.sh b/rrog/run_zinc_gine_after_pid.sh new file mode 100755 index 0000000..a4d24ae --- /dev/null +++ b/rrog/run_zinc_gine_after_pid.sh @@ -0,0 +1,14 @@ +#!/usr/bin/env bash +set -euo pipefail + +WAIT_PID="${1:?usage: run_zinc_gine_after_pid.sh }" +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" + +echo "[wait] OGB queue pid=${WAIT_PID}" +while kill -0 "${WAIT_PID}" 2>/dev/null; do + sleep 60 +done + +echo "[start] OGB queue exited; launching ZINC gine" +DEVICE="${DEVICE:-cuda:1}" EPOCHS="${EPOCHS:-200}" SEED="${SEED:-0}" ./rrog/run_zinc_gine.sh diff --git a/rrog/runspecs.py b/rrog/runspecs.py new file mode 100644 index 0000000..17c5ef4 --- /dev/null +++ b/rrog/runspecs.py @@ -0,0 +1,198 @@ +from rrog.registry import RunSpec + + +ZINC_VIEWS = [ + "gin", "gine", "gcn", "graphsage", "gatv2", "graphconv", "transformer", "pna", + "gen", "film", "resgated", "tag", "sgc", "cheb", "arma", "mf", "appnp", +] +OGB_MOL_VIEWS = [ + "gin", "gine", "gcn", "graphsage", "gatv2", "graphconv", "transformer", "pna", + "gen", "film", "resgated", "tag", "sgc", "cheb", "arma", "mf", "appnp", +] +OGB_MOL_TASKS = [ + "ogbg-molhiv", + "ogbg-molpcba", + "ogbg-molbbbp", + "ogbg-molbace", + "ogbg-moltox21", + "ogbg-molclintox", + "ogbg-molsider", + "ogbg-molesol", + "ogbg-molfreesolv", + "ogbg-mollipo", +] + + +def _zinc_cycle56_gin_command(args: dict[str, object]) -> list[str]: + compute = str(args.get("compute", "rrog-act")) + view = str(args.get("view", "gin")) + epochs = int(args.get("epochs", 200)) + hidden = int(args.get("hidden", 64)) + batch_size = int(args.get("bs", 256)) + seed = int(args.get("seed", 0)) + t = int(args.get("T", 1)) + n_sup = int(args.get("n_sup", 3)) + halt_max_steps = int(args.get("halt_max_steps", 8)) + halt_target = str(args.get("halt_target", "binary")) + + cmd = [ + "python3", "diag/train_rec.py", + "--grad_mode", "full", + "--T", str(t), + "--n_sup", str(n_sup), + "--hidden", str(hidden), + "--bs", str(batch_size), + "--epochs", str(epochs), + "--agg_layers", str(args.get("agg_layers", 5)), + "--compute_layers", str(args.get("compute_layers", 2)), + "--view", view, + "--sigma", "0", + "--K", "1", + "--select", "none", + "--seed", str(seed), + ] + + if compute in ["classic", "view-only"]: + cmd[cmd.index("--T") + 1] = "0" + elif compute == "fixed-rrog": + pass + elif compute == "rrog-act": + cmd.extend([ + "--act", + "--halt_max_steps", str(halt_max_steps), + "--halt_target", halt_target, + "--halt_norm_threshold", str(args.get("halt_norm_threshold", 0.3)), + ]) + else: + raise ValueError(f"unsupported compute for zinc-cycle56/{view}: {compute}") + if args.get("device") is not None: + cmd.extend(["--device", str(args["device"])]) + return cmd + + +def _ogb_graphprop_gin_command(args: dict[str, object]) -> list[str]: + task = str(args["task"]) + view = str(args.get("view", "gin")) + compute = str(args.get("compute", "rrog-act")) + cmd = [ + "python3", "rrog/train_ogb_graphprop.py", + "--dataset", task, + "--view", view, + "--compute", compute, + "--T", str(args.get("T", 1)), + "--n_sup", str(args.get("n_sup", 3)), + "--hidden", str(args.get("hidden", 128)), + "--bs", str(args.get("bs", 128)), + "--epochs", str(args.get("epochs", 100)), + "--eval_every", str(args.get("eval_every", 10)), + "--agg_layers", str(args.get("agg_layers", 5)), + "--compute_layers", str(args.get("compute_layers", 2)), + "--seed", str(args.get("seed", 0)), + ] + for key in ["lr", "lam_q"]: + if args.get(key) is not None: + cmd.extend([f"--{key}", str(args[key])]) + if compute == "rrog-act": + cmd.extend([ + "--halt_max_steps", str(args.get("halt_max_steps", 8)), + "--halt_min_steps", str(args.get("halt_min_steps", 2)), + "--halt_target", str(args.get("halt_target", "loss")), + "--halt_loss_threshold", str(args.get("halt_loss_threshold", 0.2)), + "--halt_exploration_prob", str(args.get("halt_exploration_prob", 0.1)), + "--act_train_mode", str(args.get("act_train_mode", "stream")), + ]) + if args.get("q_warmup_epochs") is not None: + cmd.extend(["--q_warmup_epochs", str(args["q_warmup_epochs"])]) + if float(args.get("ema", 0.0) or 0.0) > 0: + cmd.extend(["--ema", str(args["ema"])]) + if args.get("device") is not None: + cmd.extend(["--device", str(args["device"])]) + for key in ["max_train_batches", "max_eval_batches", "num_workers"]: + if args.get(key) is not None: + cmd.extend([f"--{key}", str(args[key])]) + return cmd + + +RUN_SPECS = [ +] + +for _view in ZINC_VIEWS: + RUN_SPECS.extend([ + RunSpec( + task="zinc-cycle56", + view=_view, + compute="classic", + default_args={"compute": "classic", "view": _view, "T": 0, "n_sup": 1, "epochs": 200}, + command_builder=_zinc_cycle56_gin_command, + ), + RunSpec( + task="zinc-cycle56", + view=_view, + compute="view-only", + default_args={"compute": "view-only", "view": _view, "T": 0, "n_sup": 3, "epochs": 200}, + command_builder=_zinc_cycle56_gin_command, + ), + RunSpec( + task="zinc-cycle56", + view=_view, + compute="fixed-rrog", + default_args={"compute": "fixed-rrog", "view": _view, "T": 3, "n_sup": 3, "epochs": 200}, + command_builder=_zinc_cycle56_gin_command, + ), + RunSpec( + task="zinc-cycle56", + view=_view, + compute="rrog-act", + default_args={"compute": "rrog-act", "view": _view, "T": 1, "n_sup": 3, "epochs": 200}, + command_builder=_zinc_cycle56_gin_command, + ), + ]) + +for _task in OGB_MOL_TASKS: + for _view in OGB_MOL_VIEWS: + RUN_SPECS.extend([ + RunSpec( + task=_task, + view=_view, + compute="classic", + default_args={"task": _task, "view": _view, "compute": "classic", "T": 0, "n_sup": 1, "epochs": 100}, + command_builder=_ogb_graphprop_gin_command, + ), + RunSpec( + task=_task, + view=_view, + compute="view-only", + default_args={"task": _task, "view": _view, "compute": "view-only", "T": 0, "n_sup": 3, "epochs": 100}, + command_builder=_ogb_graphprop_gin_command, + ), + RunSpec( + task=_task, + view=_view, + compute="fixed-rrog", + default_args={"task": _task, "view": _view, "compute": "fixed-rrog", "T": 3, "n_sup": 3, "epochs": 100}, + command_builder=_ogb_graphprop_gin_command, + ), + RunSpec( + task=_task, + view=_view, + compute="rrog-act", + default_args={ + "task": _task, + "view": _view, + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "epochs": 100, + "act_train_mode": "stream", + "lam_q": 0.1, + }, + command_builder=_ogb_graphprop_gin_command, + ), + ]) + + +def find_run_spec(task: str, view: str, compute: str, modifier: str = "none") -> RunSpec: + for spec in RUN_SPECS: + if (spec.task, spec.view, spec.compute, spec.modifier) == (task, view, compute, modifier): + return spec + raise KeyError(f"no implemented run spec for task={task} view={view} compute={compute} modifier={modifier}") diff --git a/rrog/train_ogb_graphprop.py b/rrog/train_ogb_graphprop.py new file mode 100644 index 0000000..0961359 --- /dev/null +++ b/rrog/train_ogb_graphprop.py @@ -0,0 +1,704 @@ +import argparse +from contextlib import contextmanager +import json +import os +import time + +import numpy as np +import torch +import torch.nn as nn +from ogb.graphproppred import Evaluator, PygGraphPropPredDataset +from ogb.graphproppred.mol_encoder import AtomEncoder, BondEncoder +from torch_geometric.data import Batch +from torch_geometric.loader import DataLoader +from torch_geometric.nn import ( + APPNP, + ARMAConv, + ChebConv, + FiLMConv, + GATv2Conv, + GCNConv, + GENConv, + GINEConv, + GraphConv, + MFConv, + PNAConv, + ResGatedGraphConv, + SAGEConv, + SGConv, + TAGConv, + TransformerConv, + global_add_pool, +) +from torch_geometric.utils import degree + + +PROJECT_ROOT = os.environ.get( + "RROG_ROOT", + os.path.abspath(os.path.join(os.path.dirname(__file__), "..")), +) +DATA_ROOT = os.environ.get("RROG_DATA_DIR", os.path.join(PROJECT_ROOT, "data")) +ROOT = os.path.join(DATA_ROOT, "ogb") +OUT = os.environ.get("RROG_RUNS_DIR", os.path.join(PROJECT_ROOT, "runs")) +SUPPORTED_VIEWS = [ + "gin", "gine", "gcn", "graphsage", "gatv2", "graphconv", "transformer", "pna", + "gen", "film", "resgated", "tag", "sgc", "cheb", "arma", "mf", "appnp", +] +SUPPORTED_MOL_DATASETS = [ + "ogbg-molhiv", + "ogbg-molpcba", + "ogbg-molbbbp", + "ogbg-molbace", + "ogbg-moltox21", + "ogbg-molclintox", + "ogbg-molsider", + "ogbg-molesol", + "ogbg-molfreesolv", + "ogbg-mollipo", +] +HIGHER_BETTER = {"rocauc", "ap", "auc", "accuracy", "acc", "f1"} +LOWER_BETTER = {"rmse", "mae"} + +_TORCH_LOAD = torch.load + + +def _torch_load_ogb_compat(*args, **kwargs): + kwargs.setdefault("weights_only", False) + return _TORCH_LOAD(*args, **kwargs) + + +torch.load = _torch_load_ogb_compat + + +def clone_state_dict(model): + return {k: v.detach().clone() for k, v in model.state_dict().items()} + + +@torch.no_grad() +def update_ema_state(ema_state, model, decay): + if ema_state is None: + return + for key, value in model.state_dict().items(): + if torch.is_floating_point(value): + ema_state[key].mul_(decay).add_(value.detach(), alpha=1.0 - decay) + else: + ema_state[key].copy_(value.detach()) + + +@contextmanager +def using_ema_state(model, ema_state): + if ema_state is None: + yield + return + raw_state = clone_state_dict(model) + model.load_state_dict(ema_state, strict=True) + try: + yield + finally: + model.load_state_dict(raw_state, strict=True) + + +def metric_direction(metric: str) -> int: + metric = metric.lower() + if metric in LOWER_BETTER or "rmse" in metric or "mae" in metric: + return -1 + return 1 + + +def is_regression_metric(metric: str) -> bool: + return metric_direction(metric) < 0 + + +def is_better(score: float, best: float | None, metric: str) -> bool: + if best is None: + return True + direction = metric_direction(metric) + return score > best if direction > 0 else score < best + + +def jsonable(obj): + if isinstance(obj, dict): + return {str(k): jsonable(v) for k, v in obj.items()} + if isinstance(obj, (list, tuple)): + return [jsonable(v) for v in obj] + if isinstance(obj, (np.integer, np.floating)): + return obj.item() + if isinstance(obj, torch.Tensor): + if obj.ndim == 0: + return obj.detach().cpu().item() + return obj.detach().cpu().tolist() + return obj + + +def degree_histogram(dataset) -> torch.Tensor: + max_degree = 0 + degs = [] + for graph in dataset: + deg = degree(graph.edge_index[1], num_nodes=graph.num_nodes, dtype=torch.long) + degs.append(deg) + if deg.numel(): + max_degree = max(max_degree, int(deg.max().item())) + hist = torch.zeros(max_degree + 1, dtype=torch.long) + for deg in degs: + hist += torch.bincount(deg, minlength=hist.numel()) + return hist + + +def make_view_layer(view: str, hidden: int, deg: torch.Tensor | None): + if view in {"gin", "gine"}: + mlp = nn.Sequential(nn.Linear(hidden, hidden), nn.ReLU(), nn.Linear(hidden, hidden)) + return GINEConv(mlp, train_eps=True) + if view == "gcn": + return GCNConv(hidden, hidden) + if view == "graphsage": + return SAGEConv(hidden, hidden) + if view == "gatv2": + return GATv2Conv(hidden, hidden, heads=4, concat=False, edge_dim=hidden) + if view == "graphconv": + return GraphConv(hidden, hidden) + if view == "transformer": + return TransformerConv(hidden, hidden, heads=4, concat=False, edge_dim=hidden) + if view == "pna": + if deg is None: + raise ValueError("PNA view requires a training-set degree histogram") + return PNAConv( + hidden, hidden, + aggregators=["mean", "min", "max", "std"], + scalers=["identity", "amplification", "attenuation"], + deg=deg, + edge_dim=hidden, + ) + if view == "gen": + return GENConv(hidden, hidden, edge_dim=hidden) + if view == "film": + return FiLMConv(hidden, hidden) + if view == "resgated": + return ResGatedGraphConv(hidden, hidden, edge_dim=hidden) + if view == "tag": + return TAGConv(hidden, hidden, K=3) + if view == "sgc": + return SGConv(hidden, hidden, K=2, cached=False) + if view == "cheb": + return ChebConv(hidden, hidden, K=3) + if view == "arma": + return ARMAConv(hidden, hidden, num_stacks=1, num_layers=2) + if view == "mf": + return MFConv(hidden, hidden) + if view == "appnp": + return APPNP(K=5, alpha=0.1) + raise ValueError(f"unsupported OGB view: {view}") + + +EDGE_ATTR_VIEWS = {"gin", "gine", "gatv2", "transformer", "pna", "gen", "resgated"} + + +class OGBRRoG(nn.Module): + def __init__( + self, hidden, num_tasks, view="gin", T=1, n_sup=3, agg_layers=5, + compute_layers=2, grad_mode="full", deg=None, + ): + super().__init__() + self.view = view + self.atom_encoder = AtomEncoder(hidden) + self.bond_encoder = BondEncoder(hidden) + self.agg_convs = nn.ModuleList() + self.agg_bns = nn.ModuleList() + for _ in range(agg_layers): + self.agg_convs.append(make_view_layer(view, hidden, deg)) + self.agg_bns.append(nn.BatchNorm1d(hidden)) + + core = [] + d = hidden + for _ in range(compute_layers - 1): + core += [nn.Linear(d, hidden), nn.GELU()] + d = hidden + core.append(nn.Linear(d, hidden)) + self.core_norm = nn.LayerNorm(hidden) + self.core = nn.Sequential(*core) + nn.init.zeros_(self.core[-1].weight) + nn.init.zeros_(self.core[-1].bias) + + self.head = nn.Sequential(nn.Linear(hidden, hidden), nn.ReLU(), nn.Linear(hidden, num_tasks)) + self.qhead = nn.Sequential(nn.Linear(hidden, hidden), nn.ReLU(), nn.Linear(hidden, 1)) + with torch.no_grad(): + self.qhead[-1].weight.zero_() + self.qhead[-1].bias.fill_(-5.0) + + self.T = T + self.n_sup = n_sup + self.grad_mode = grad_mode + self.agg_layers = agg_layers + self.compute_layers = compute_layers + self.hidden = hidden + self.num_tasks = num_tasks + + def aggregate(self, x, edge_index, edge_attr): + h = self.atom_encoder(x) + e = self.bond_encoder(edge_attr) + for conv, bn in zip(self.agg_convs, self.agg_bns): + if self.view in {"gin", "gine", "pna", "gen", "resgated"}: + h = bn(conv(h, edge_index, e)).relu() + elif self.view in {"gatv2", "transformer"}: + h = bn(conv(h, edge_index, edge_attr=e)).relu() + else: + h = bn(conv(h, edge_index)).relu() + return h + + def core_step(self, combined, state): + return state + self.core(self.core_norm(combined)) + + def _z_step(self, y, z, ctx): + return self.core_step(ctx + y + z, z) + + def _y_step(self, y, z): + return self.core_step(y + z, y) + + def recurse(self, y, z, ctx, one_step=False): + if self.T == 0: + return y, z + if one_step: + with torch.no_grad(): + for _ in range(self.T - 1): + z = self._z_step(y, z, ctx) + z = z.detach() + z = self._z_step(y, z, ctx) + y = self._y_step(y, z) + return y, z + for _ in range(self.T): + z = self._z_step(y, z, ctx) + y = self._y_step(y, z) + return y, z + + def predict(self, y, batch): + pooled = global_add_pool(y, batch) + return self.head(pooled), self.qhead(pooled).view(-1) + + def forward_trace(self, data, steps): + ctx = self.aggregate(data.x, data.edge_index, data.edge_attr) + y = ctx + z = torch.zeros_like(ctx) + preds, q_logits = [], [] + for s in range(steps): + y, z = self.recurse(y, z, ctx, one_step=(self.grad_mode == "1step")) + pred, q = self.predict(y, data.batch) + preds.append(pred) + q_logits.append(q) + if s < steps - 1: + y, z = y.detach(), z.detach() + return preds, q_logits + + def forward(self, data): + steps = self.n_sup + preds, q_logits = self.forward_trace(data, steps) + return preds, q_logits[-1] + + +def supervised_loss(logits, y, metric): + per_graph, has_label = per_graph_supervised_loss(logits, y, metric) + if not has_label.any(): + return logits.sum() * 0.0 + return per_graph[has_label].mean() + + +def per_graph_supervised_loss(logits, y, metric): + y = y.to(torch.float32) + mask = ~torch.isnan(y) + target = torch.where(mask, y, torch.zeros_like(y)) + if is_regression_metric(metric): + losses = (logits - target).pow(2) + else: + losses = nn.functional.binary_cross_entropy_with_logits(logits, target, reduction="none") + losses = torch.where(mask, losses, torch.zeros_like(losses)) + denom = mask.sum(dim=1).clamp_min(1) + return losses.sum(dim=1) / denom, mask.any(dim=1) + + +@torch.no_grad() +def halt_targets(logits, y): + y = y.to(torch.float32) + mask = ~torch.isnan(y) + pred = (logits > 0).to(y.dtype) + correct_or_missing = (~mask) | (pred == y) + has_label = mask.any(dim=1) + return (correct_or_missing.all(dim=1) & has_label).to(logits.dtype) + + +@torch.no_grad() +def evaluate(model, loader, evaluator, dev, steps=None, adaptive=False, halt_min_steps=1, max_batches=0): + model.eval() + ys, ps = [], [] + step_sum = 0.0 + n = 0 + for i, batch in enumerate(loader): + if max_batches and i >= max_batches: + break + batch = batch.to(dev) + if steps is None: + preds, _ = model(batch) + pred = preds[-1] + used_steps = float(model.n_sup) + else: + preds, qs = model.forward_trace(batch, steps) + stack = torch.stack(preds, dim=0) + if adaptive: + q = torch.stack(qs, dim=0) + step_ids = torch.arange(1, steps + 1, device=dev).view(-1, 1) + halted = (q > 0) & (step_ids >= halt_min_steps) + any_halt = halted.any(dim=0) + first_halt = halted.to(torch.int64).argmax(dim=0) + fallback = torch.full_like(first_halt, steps - 1) + idx = torch.where(any_halt, first_halt, fallback) + pred = stack[idx, torch.arange(stack.size(1), device=dev)] + used_steps = float((idx.to(torch.float32) + 1).sum().item()) + else: + pred = stack[-1] + used_steps = float(steps * batch.num_graphs) + ys.append(batch.y.detach().cpu()) + ps.append(pred.detach().cpu()) + step_sum += used_steps + n += batch.num_graphs + y_true = torch.cat(ys, dim=0) + y_pred = torch.cat(ps, dim=0) + result = evaluator.eval({"y_true": y_true, "y_pred": y_pred}) + return result, step_sum / max(n, 1) + + +def _split_nodes(t, ptr): + return [t[ptr[i].item():ptr[i + 1].item()].detach() for i in range(ptr.numel() - 1)] + + +def act_train_step(model, state, replacement_batch, opt, dev, args, epoch, metric): + replacement = replacement_batch.to_data_list() + batch_size = len(replacement) + if state is None: + state = { + "graphs": [None for _ in range(batch_size)], + "y": [None for _ in range(batch_size)], + "z": [None for _ in range(batch_size)], + "steps": torch.zeros(batch_size, dtype=torch.long, device=dev), + "halted": torch.ones(batch_size, dtype=torch.bool, device=dev), + } + + halted_cpu = state["halted"].detach().cpu().tolist() + for i, halted in enumerate(halted_cpu): + if halted: + state["graphs"][i] = replacement[i] + + batch = Batch.from_data_list(state["graphs"]).to(dev) + ctx = model.aggregate(batch.x, batch.edge_index, batch.edge_attr) + ptr = batch.ptr + y_parts, z_parts = [], [] + for i in range(batch_size): + start, end = ptr[i].item(), ptr[i + 1].item() + if halted_cpu[i] or state["y"][i] is None: + y_parts.append(ctx[start:end]) + z_parts.append(torch.zeros_like(ctx[start:end])) + else: + y_parts.append(state["y"][i].to(dev)) + z_parts.append(state["z"][i].to(dev)) + y = torch.cat(y_parts, dim=0) + z = torch.cat(z_parts, dim=0) + + opt.zero_grad() + y, z = model.recurse(y, z, ctx, one_step=(model.grad_mode == "1step")) + logits, q = model.predict(y, batch.batch) + pred_loss = supervised_loss(logits, batch.y, metric) + if args.halt_target == "exact" and not is_regression_metric(metric): + target = halt_targets(logits.detach(), batch.y) + elif args.halt_target == "loss": + per_graph_loss, has_label = per_graph_supervised_loss(logits.detach(), batch.y, metric) + target = ((per_graph_loss <= args.halt_loss_threshold) & has_label).to(logits.dtype) + else: + raise ValueError(args.halt_target) + if epoch <= args.q_warmup_epochs: + q_loss = pred_loss.detach() * 0.0 + loss = pred_loss + else: + q_loss = nn.functional.binary_cross_entropy_with_logits(q, target) + loss = pred_loss + 0.5 * args.lam_q * q_loss + y_det, z_det = y.detach(), z.detach() + loss.backward() + torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0) + opt.step() + + state["y"] = _split_nodes(y_det, ptr) + state["z"] = _split_nodes(z_det, ptr) + with torch.no_grad(): + was_halted = state["halted"] + steps = torch.where(was_halted, torch.zeros_like(state["steps"]), state["steps"]) + 1 + halted = (steps >= args.halt_max_steps) | ((q.detach() > 0) & (steps >= args.halt_min_steps)) + if args.halt_exploration_prob > 0 and args.halt_max_steps > 1: + explore = torch.rand_like(q) < args.halt_exploration_prob + min_steps = torch.where( + explore, + torch.randint(2, args.halt_max_steps + 1, steps.shape, device=dev), + torch.zeros_like(steps), + ) + halted = halted & (steps >= min_steps) + state["steps"] = steps + state["halted"] = halted + + return state, { + "loss": float(loss.detach().cpu()), + "pred_loss": float(pred_loss.detach().cpu()), + "q_loss": float(q_loss.detach().cpu()), + "halted_frac": float(state["halted"].to(torch.float32).mean().detach().cpu()), + "steps": float(state["steps"].to(torch.float32).mean().detach().cpu()), + } + + +def _halt_target(args, logits, y, metric): + if args.halt_target == "exact" and not is_regression_metric(metric): + return halt_targets(logits.detach(), y) + if args.halt_target == "loss": + per_graph_loss, has_label = per_graph_supervised_loss(logits.detach(), y, metric) + return ((per_graph_loss <= args.halt_loss_threshold) & has_label).to(logits.dtype) + raise ValueError(args.halt_target) + + +def act_trace_train_step(model, batch, opt, dev, args, epoch, metric): + batch = batch.to(dev) + steps = max(1, args.halt_max_steps) + opt.zero_grad() + preds, qs = model.forward_trace(batch, steps) + pred_loss = sum(supervised_loss(pred, batch.y, metric) for pred in preds) / len(preds) + if epoch <= args.q_warmup_epochs: + q_loss = pred_loss.detach() * 0.0 + loss = pred_loss + else: + q_losses = [] + for step_idx, (pred, q) in enumerate(zip(preds, qs), start=1): + target = _halt_target(args, pred, batch.y, metric) + if step_idx < args.halt_min_steps: + target = torch.zeros_like(target) + q_losses.append(nn.functional.binary_cross_entropy_with_logits(q, target)) + q_loss = sum(q_losses) / len(q_losses) + loss = pred_loss + 0.5 * args.lam_q * q_loss + loss.backward() + torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0) + opt.step() + + with torch.no_grad(): + q_stack = torch.stack(qs, dim=0) + step_ids = torch.arange(1, steps + 1, device=dev).view(-1, 1) + halted = (q_stack > 0) & (step_ids >= args.halt_min_steps) + any_halt = halted.any(dim=0) + first_halt = halted.to(torch.int64).argmax(dim=0) + fallback = torch.full_like(first_halt, steps - 1) + idx = torch.where(any_halt, first_halt, fallback) + + return { + "loss": float(loss.detach().cpu()), + "pred_loss": float(pred_loss.detach().cpu()), + "q_loss": float(q_loss.detach().cpu()), + "halted_frac": float(any_halt.to(torch.float32).mean().detach().cpu()), + "steps": float((idx.to(torch.float32) + 1).mean().detach().cpu()), + } + + +def train_epoch(model, loader, opt, dev, args, act_state, ema_state, epoch, metric): + model.train() + metrics = [] + for i, batch in enumerate(loader): + if args.max_train_batches and i >= args.max_train_batches: + break + if args.compute == "rrog-act": + if args.act_train_mode == "stream": + act_state, m = act_train_step(model, act_state, batch, opt, dev, args, epoch, metric) + else: + m = act_trace_train_step(model, batch, opt, dev, args, epoch, metric) + update_ema_state(ema_state, model, args.ema) + metrics.append(m) + continue + batch = batch.to(dev) + opt.zero_grad() + preds, _ = model(batch) + loss = sum(supervised_loss(pred, batch.y, metric) for pred in preds) / len(preds) + loss.backward() + torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0) + opt.step() + update_ema_state(ema_state, model, args.ema) + metrics.append({"loss": float(loss.detach().cpu()), "halted_frac": 0.0, "steps": float(model.n_sup)}) + return act_state, metrics + + +def metric_value(result, evaluator): + return float(result[evaluator.eval_metric]) + + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument("--dataset", choices=SUPPORTED_MOL_DATASETS, default="ogbg-molhiv") + ap.add_argument("--view", choices=SUPPORTED_VIEWS, default="gin") + ap.add_argument("--compute", choices=["classic", "view-only", "fixed-rrog", "rrog-act"], default="rrog-act") + ap.add_argument("--T", type=int, default=1) + ap.add_argument("--n_sup", type=int, default=3) + ap.add_argument("--hidden", type=int, default=128) + ap.add_argument("--agg_layers", type=int, default=5) + ap.add_argument("--compute_layers", type=int, default=2) + ap.add_argument("--epochs", type=int, default=100) + ap.add_argument("--eval_every", type=int, default=10) + ap.add_argument("--lr", type=float, default=1e-3) + ap.add_argument("--bs", type=int, default=128) + ap.add_argument("--lam_q", type=float, default=1.0) + ap.add_argument("--halt_max_steps", type=int, default=8) + ap.add_argument("--halt_min_steps", type=int, default=1) + ap.add_argument("--halt_target", choices=["exact", "loss"], default="loss") + ap.add_argument("--halt_loss_threshold", type=float, default=0.2) + ap.add_argument("--halt_exploration_prob", type=float, default=0.1) + ap.add_argument("--q_warmup_epochs", type=int, default=0) + ap.add_argument("--act_train_mode", choices=["stream", "trace"], default="stream") + ap.add_argument("--ema", type=float, default=0.0) + ap.add_argument("--seed", type=int, default=0) + ap.add_argument("--num_workers", type=int, default=0) + ap.add_argument("--max_train_batches", type=int, default=0) + ap.add_argument("--max_eval_batches", type=int, default=0) + ap.add_argument("--device", default="auto") + args = ap.parse_args() + + torch.manual_seed(args.seed) + np.random.seed(args.seed) + if args.compute == "classic": + args.n_sup = 1 + if args.device == "auto": + dev = "cuda" if torch.cuda.is_available() else "cpu" + else: + dev = args.device + os.makedirs(OUT, exist_ok=True) + + dataset = PygGraphPropPredDataset(name=args.dataset, root=ROOT) + split_idx = dataset.get_idx_split() + evaluator = Evaluator(args.dataset) + metric = evaluator.eval_metric + num_tasks = dataset.num_tasks + + train_dataset = dataset[split_idx["train"]] + valid_dataset = dataset[split_idx["valid"]] + test_dataset = dataset[split_idx["test"]] + train_loader = DataLoader(train_dataset, batch_size=args.bs, shuffle=True, + drop_last=True, num_workers=args.num_workers) + valid_loader = DataLoader(valid_dataset, batch_size=256, shuffle=False, + num_workers=args.num_workers) + test_loader = DataLoader(test_dataset, batch_size=256, shuffle=False, + num_workers=args.num_workers) + + T = 0 if args.compute in ["classic", "view-only"] else args.T + deg = degree_histogram(train_dataset) if args.view == "pna" else None + model = OGBRRoG(args.hidden, num_tasks, view=args.view, T=T, n_sup=args.n_sup, + agg_layers=args.agg_layers, compute_layers=args.compute_layers, deg=deg).to(dev) + opt = torch.optim.Adam(model.parameters(), lr=args.lr, weight_decay=1e-5) + sched = torch.optim.lr_scheduler.CosineAnnealingLR(opt, max(args.epochs, 1)) + ema_state = clone_state_dict(model) if args.ema > 0 else None + + t0 = time.time() + best_val = None + best = {} + best_state = None + act_state = None + steps = max(1, args.halt_max_steps) + + for ep in range(args.epochs): + act_state, train_metrics = train_epoch( + model, train_loader, opt, dev, args, act_state, ema_state, ep + 1, metric) + sched.step() + if (ep + 1) % args.eval_every == 0 or ep == args.epochs - 1: + with using_ema_state(model, ema_state): + if args.compute == "rrog-act": + val_result, fixed_val_steps = evaluate(model, valid_loader, evaluator, dev, steps=steps, + adaptive=False, halt_min_steps=args.halt_min_steps, + max_batches=args.max_eval_batches) + val_adapt, adaptive_val_steps = evaluate(model, valid_loader, evaluator, dev, steps=steps, + adaptive=True, halt_min_steps=args.halt_min_steps, + max_batches=args.max_eval_batches) + else: + val_result, _ = evaluate(model, valid_loader, evaluator, dev, + max_batches=args.max_eval_batches) + val_score = metric_value(val_result, evaluator) + if is_better(val_score, best_val, metric): + best_val = val_score + if args.compute == "rrog-act": + test_fixed, fixed_steps = evaluate(model, test_loader, evaluator, dev, steps=steps, + adaptive=False, halt_min_steps=args.halt_min_steps, + max_batches=args.max_eval_batches) + test_adapt, adaptive_steps = evaluate(model, test_loader, evaluator, dev, steps=steps, + adaptive=True, halt_min_steps=args.halt_min_steps, + max_batches=args.max_eval_batches) + best = { + "ep": ep + 1, + "val": val_result, + "val_adaptive": val_adapt, + "test": test_fixed, + "test_adaptive": test_adapt, + "fixed_val_steps": fixed_val_steps, + "adaptive_val_steps": adaptive_val_steps, + "fixed_steps": fixed_steps, + "adaptive_steps": adaptive_steps, + } + else: + test_result, _ = evaluate(model, test_loader, evaluator, dev, + max_batches=args.max_eval_batches) + best = {"ep": ep + 1, "val": val_result, "test": test_result} + best_state = {k: v.detach().cpu().clone() for k, v in model.state_dict().items()} + halted = sum(m.get("halted_frac", 0.0) for m in train_metrics) / max(len(train_metrics), 1) + train_steps = sum(m.get("steps", 0.0) for m in train_metrics) / max(len(train_metrics), 1) + msg = f"ep{ep+1} val_{evaluator.eval_metric}={val_score:.5f}" + if args.compute == "rrog-act": + msg += ( + f" val_adapt_{evaluator.eval_metric}={metric_value(val_adapt, evaluator):.5f}" + f" adapt_steps={adaptive_val_steps:.2f}" + ) + msg += f" halt={halted:.2f} train_steps={train_steps:.2f}" + print(msg, flush=True) + + ema_tag = f"_ema{args.ema:g}" if args.ema > 0 else "" + act_tag = "" + if args.compute == "rrog-act": + target_tag = args.halt_target + if args.halt_target == "loss": + target_tag += f"{args.halt_loss_threshold:g}" + act_tag = ( + f"_{args.act_train_mode}_hm{args.halt_max_steps}_hmin{args.halt_min_steps}_" + f"{target_tag}_lq{args.lam_q:g}_hex{args.halt_exploration_prob:g}_qw{args.q_warmup_epochs}" + ) + tag = ( + f"{args.dataset}_{args.view}_{args.compute}_T{T}_ns{args.n_sup}{act_tag}_" + f"h{args.hidden}_e{args.epochs}{ema_tag}_s{args.seed}" + ) + rep = { + "dataset": args.dataset, + "tag": tag, + **vars(args), + "metric": evaluator.eval_metric, + "sec": round(time.time() - t0, 1), + "dev": dev, + **best, + } + with open(os.path.join(OUT, f"{tag}.json"), "w") as f: + json.dump(jsonable(rep), f, indent=2) + torch.save({ + "state": best_state or model.state_dict(), + "cfg": { + "dataset": args.dataset, + "hidden": args.hidden, + "num_tasks": num_tasks, + "T": T, + "n_sup": args.n_sup, + "agg_layers": args.agg_layers, + "compute_layers": args.compute_layers, + "compute": args.compute, + "halt_max_steps": steps, + "halt_min_steps": args.halt_min_steps, + "halt_target": args.halt_target, + "halt_loss_threshold": args.halt_loss_threshold, + "halt_exploration_prob": args.halt_exploration_prob, + "act_train_mode": args.act_train_mode, + "view": args.view, + }, + }, os.path.join(OUT, f"ckpt_{tag}.pt")) + print(f"[{tag}] best_ep={best.get('ep')} val={best.get('val')} test={best.get('test')} " + f"adaptive={best.get('test_adaptive')} steps={best.get('adaptive_steps')}", flush=True) + print(" wrote", os.path.join(OUT, f"{tag}.json")) + + +if __name__ == "__main__": + main() diff --git a/run_two_a6000_72h.sbatch b/run_two_a6000_72h.sbatch new file mode 100644 index 0000000..ebb1c1a --- /dev/null +++ b/run_two_a6000_72h.sbatch @@ -0,0 +1,41 @@ +#!/bin/bash +#SBATCH --job-name=rrog-gnn-2xa6000 +#SBATCH --output=slurm-rrog-gnn-%j.out +#SBATCH --error=slurm-rrog-gnn-%j.err +#SBATCH --time=72:00:00 +#SBATCH --account=orion +#SBATCH --partition=orion +#SBATCH --nodes=1 +#SBATCH --ntasks-per-node=1 +#SBATCH --gres=gpu:a6000:2 +#SBATCH --cpus-per-task=16 +#SBATCH --mem=128G + +set -euo pipefail + +ROOT_DIR="${ROOT_DIR:-/orion/u/oscarwan/rrog}" +cd "${ROOT_DIR}" + +echo "Host: $(hostname)" +echo "Job ID: ${SLURM_JOB_ID:-local}" +echo "Workdir: $(pwd)" +echo "CUDA_VISIBLE_DEVICES=${CUDA_VISIBLE_DEVICES:-unset}" +echo "SKIP_SETUP=${SKIP_SETUP:-0}" +echo "ZINC_DEVICE=${ZINC_DEVICE:-cuda:0}" +echo "OGB_DEVICE=${OGB_DEVICE:-cuda:1}" +echo "ZINC_EPOCHS=${ZINC_EPOCHS:-200}" +echo "OGB_EPOCHS=${OGB_EPOCHS:-100}" +echo "OGB_TASK=${OGB_TASK:-ogbg-molhiv}" +echo "SEED=${SEED:-0}" + +nvidia-smi + +[[ -x ./scripts/setup_and_run_two_a6000.sh ]] || { + echo "FATAL: missing executable ./scripts/setup_and_run_two_a6000.sh" + exit 1 +} + +# This intentionally delegates to the repository's one-command runner unchanged. +# Override repo-supported options with sbatch --export, e.g.: +# sbatch --export=ALL,SKIP_SETUP=1 run_two_a6000_72h.sbatch +./scripts/setup_and_run_two_a6000.sh diff --git a/runs/.last_real_log b/runs/.last_real_log new file mode 100644 index 0000000..1c84084 --- /dev/null +++ b/runs/.last_real_log @@ -0,0 +1 @@ +/home/yurenh2/rrog/runs/real_sweep_20260616_081956.log diff --git a/runs/.last_sweep_log b/runs/.last_sweep_log new file mode 100644 index 0000000..cc8070e --- /dev/null +++ b/runs/.last_sweep_log @@ -0,0 +1 @@ +/home/yurenh2/rrog/runs/diag_sweep_20260616_074509.log diff --git a/runs/archA.log b/runs/archA.log new file mode 100644 index 0000000..4b2b4f7 --- /dev/null +++ b/runs/archA.log @@ -0,0 +1,242 @@ +A start gpu=0 2026-06-16T15:29:24-05:00 +== A s0 conv=gcn == +ep20 solve_rate=0.000 mean_conflicts=162.09 +ep40 solve_rate=0.000 mean_conflicts=129.86 +ep60 solve_rate=0.000 mean_conflicts=149.86 +ep80 solve_rate=0.000 mean_conflicts=47.19 +ep100 solve_rate=0.000 mean_conflicts=72.71 +ep120 solve_rate=0.000 mean_conflicts=153.69 +ep140 solve_rate=0.000 mean_conflicts=163.38 +ep150 solve_rate=0.000 mean_conflicts=163.18 +[color_gcn_full_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.0 @ep20 (199.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s0.pt +[gcn/full] LE n=300 fail=1.00 | SOLVED +nan UNSOLVED -1.276 sep=+nan AUROC=nan mean_lam=-1.276 +[pe=none s0] deterministic solve_rate = 0.000 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.000 0.000 0.000 0.000 nan + wrote /home/yurenh2/rrog/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s0.json +== A s0 conv=sage == +ep20 solve_rate=0.303 mean_conflicts=4.08 +ep40 solve_rate=0.703 mean_conflicts=1.23 +ep60 solve_rate=0.730 mean_conflicts=1.09 +ep80 solve_rate=0.720 mean_conflicts=1.05 +ep100 solve_rate=0.680 mean_conflicts=1.20 +ep120 solve_rate=0.707 mean_conflicts=1.28 +ep140 solve_rate=0.667 mean_conflicts=1.62 +ep150 solve_rate=0.660 mean_conflicts=1.76 +[color_sage_full_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.73 @ep60 (163.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.pt +[sage/full] LE n=300 fail=0.27 | SOLVED -0.131 UNSOLVED +0.052 sep=+0.183 AUROC=0.793 mean_lam=-0.082 +[pe=none s0] deterministic solve_rate = 0.747 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.953 0.813 0.767 0.762 0.771 + wrote /home/yurenh2/rrog/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json +== A s0 conv=gat == +ep20 solve_rate=0.000 mean_conflicts=152.21 +ep40 solve_rate=0.000 mean_conflicts=143.93 +ep60 solve_rate=0.007 mean_conflicts=116.76 +ep80 solve_rate=0.013 mean_conflicts=107.49 +ep100 solve_rate=0.000 mean_conflicts=102.05 +ep120 solve_rate=0.003 mean_conflicts=111.15 +ep140 solve_rate=0.000 mean_conflicts=163.45 +ep150 solve_rate=0.000 mean_conflicts=163.46 +[color_gat_full_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.0133 @ep80 (305.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gat_full_none_n50_k3_p0.2_T3_ns3_s0.pt +[gat/full] LE n=300 fail=0.99 | SOLVED -0.211 UNSOLVED -0.296 sep=-0.084 AUROC=0.353 mean_lam=-0.295 +[pe=none s0] deterministic solve_rate = 0.007 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.047 0.020 0.027 0.020 0.203 + wrote /home/yurenh2/rrog/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s0.json +== A s1 conv=gcn == +ep20 solve_rate=0.000 mean_conflicts=41.51 +ep40 solve_rate=0.000 mean_conflicts=35.89 +ep60 solve_rate=0.000 mean_conflicts=66.98 +ep80 solve_rate=0.000 mean_conflicts=73.91 +ep100 solve_rate=0.000 mean_conflicts=60.61 +ep120 solve_rate=0.000 mean_conflicts=61.23 +ep140 solve_rate=0.000 mean_conflicts=53.94 +ep150 solve_rate=0.003 mean_conflicts=47.46 +[color_gcn_full_none_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.0033 @ep150 (200.7s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s1.pt +[gcn/full] LE n=300 fail=1.00 | SOLVED -0.234 UNSOLVED -0.104 sep=+0.130 AUROC=0.893 mean_lam=-0.105 +[pe=none s1] deterministic solve_rate = 0.000 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.007 0.000 0.000 0.000 0.941 + wrote /home/yurenh2/rrog/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s1.json +== A s1 conv=sage == +ep20 solve_rate=0.223 mean_conflicts=4.59 +ep40 solve_rate=0.723 mean_conflicts=1.13 +ep60 solve_rate=0.760 mean_conflicts=0.84 +ep80 solve_rate=0.780 mean_conflicts=0.82 +ep100 solve_rate=0.750 mean_conflicts=0.96 +ep120 solve_rate=0.787 mean_conflicts=0.78 +ep140 solve_rate=0.760 mean_conflicts=0.81 +ep150 solve_rate=0.740 mean_conflicts=0.87 +[color_sage_full_none_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.7867 @ep120 (159.8s) + wrote /home/yurenh2/rrog/runs/ckpt_color_sage_full_none_n50_k3_p0.2_T3_ns3_s1.pt +[sage/full] LE n=300 fail=0.21 | SOLVED +0.063 UNSOLVED +0.160 sep=+0.097 AUROC=0.688 mean_lam=+0.084 +[pe=none s1] deterministic solve_rate = 0.827 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.973 0.873 0.793 0.781 0.702 + wrote /home/yurenh2/rrog/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s1.json +== A s1 conv=gat == +ep20 solve_rate=0.000 mean_conflicts=161.72 +ep40 solve_rate=0.000 mean_conflicts=146.74 +ep60 solve_rate=0.000 mean_conflicts=115.72 +ep80 solve_rate=0.007 mean_conflicts=81.21 +ep100 solve_rate=0.003 mean_conflicts=118.91 +ep120 solve_rate=0.000 mean_conflicts=111.77 +ep140 solve_rate=0.000 mean_conflicts=140.12 +ep150 solve_rate=0.000 mean_conflicts=141.12 +[color_gat_full_none_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.0067 @ep80 (870.5s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gat_full_none_n50_k3_p0.2_T3_ns3_s1.pt +[gat/full] LE n=300 fail=0.99 | SOLVED -0.101 UNSOLVED -0.253 sep=-0.153 AUROC=0.087 mean_lam=-0.252 +[pe=none s1] deterministic solve_rate = 0.013 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.033 0.020 0.013 0.014 0.177 + wrote /home/yurenh2/rrog/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s1.json +== A s2 conv=gcn == +ep20 solve_rate=0.000 mean_conflicts=40.93 +ep40 solve_rate=0.000 mean_conflicts=48.18 +ep60 solve_rate=0.000 mean_conflicts=92.76 +ep80 solve_rate=0.000 mean_conflicts=86.67 +ep100 solve_rate=0.003 mean_conflicts=60.79 +ep120 solve_rate=0.003 mean_conflicts=46.40 +ep140 solve_rate=0.003 mean_conflicts=59.99 +ep150 solve_rate=0.003 mean_conflicts=75.26 +[color_gcn_full_none_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.0033 @ep100 (676.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s2.pt +[gcn/full] LE n=300 fail=1.00 | SOLVED -0.221 UNSOLVED -0.262 sep=-0.041 AUROC=0.301 mean_lam=-0.262 +[pe=none s2] deterministic solve_rate = 0.007 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.007 0.007 0.000 0.003 0.563 + wrote /home/yurenh2/rrog/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s2.json +== A s2 conv=sage == +ep20 solve_rate=0.267 mean_conflicts=3.97 +ep40 solve_rate=0.727 mean_conflicts=1.07 +ep60 solve_rate=0.830 mean_conflicts=0.68 +ep80 solve_rate=0.827 mean_conflicts=0.54 +ep100 solve_rate=0.803 mean_conflicts=0.74 +ep120 solve_rate=0.680 mean_conflicts=1.54 +ep140 solve_rate=0.587 mean_conflicts=2.31 +ep150 solve_rate=0.527 mean_conflicts=2.94 +[color_sage_full_none_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.83 @ep60 (224.4s) + wrote /home/yurenh2/rrog/runs/ckpt_color_sage_full_none_n50_k3_p0.2_T3_ns3_s2.pt +[sage/full] LE n=300 fail=0.17 | SOLVED -0.105 UNSOLVED +0.102 sep=+0.207 AUROC=0.814 mean_lam=-0.070 +[pe=none s2] deterministic solve_rate = 0.847 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.980 0.907 0.833 0.820 0.790 + wrote /home/yurenh2/rrog/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s2.json +== A s2 conv=gat == +ep20 solve_rate=0.000 mean_conflicts=130.86 +ep40 solve_rate=0.000 mean_conflicts=163.47 +ep60 solve_rate=0.000 mean_conflicts=163.48 +ep80 solve_rate=0.000 mean_conflicts=163.48 +ep100 solve_rate=0.003 mean_conflicts=152.94 +ep120 solve_rate=0.000 mean_conflicts=156.99 +ep140 solve_rate=0.000 mean_conflicts=163.18 +ep150 solve_rate=0.000 mean_conflicts=163.48 +[color_gat_full_none_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.0033 @ep100 (871.7s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gat_full_none_n50_k3_p0.2_T3_ns3_s2.pt +[gat/full] LE n=300 fail=1.00 | SOLVED -0.133 UNSOLVED -0.253 sep=-0.120 AUROC=0.147 mean_lam=-0.252 +[pe=none s2] deterministic solve_rate = 0.007 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.033 0.013 0.020 0.013 0.248 + wrote /home/yurenh2/rrog/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s2.json +== A s3 conv=gcn == +ep20 solve_rate=0.000 mean_conflicts=44.52 +ep40 solve_rate=0.000 mean_conflicts=47.99 +ep60 solve_rate=0.000 mean_conflicts=91.15 +ep80 solve_rate=0.000 mean_conflicts=99.85 +ep100 solve_rate=0.003 mean_conflicts=69.26 +ep120 solve_rate=0.003 mean_conflicts=54.51 +ep140 solve_rate=0.003 mean_conflicts=59.94 +ep150 solve_rate=0.003 mean_conflicts=54.14 +[color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.0033 @ep100 (675.0s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3.pt +[gcn/full] LE n=300 fail=1.00 | SOLVED -0.372 UNSOLVED -0.330 sep=+0.042 AUROC=0.672 mean_lam=-0.330 +[pe=none s3] deterministic solve_rate = 0.007 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.013 0.000 0.007 0.004 0.697 + wrote /home/yurenh2/rrog/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3.json +== A s3 conv=sage == +ep20 solve_rate=0.227 mean_conflicts=4.44 +ep40 solve_rate=0.653 mean_conflicts=1.48 +ep60 solve_rate=0.767 mean_conflicts=0.88 +ep80 solve_rate=0.803 mean_conflicts=0.71 +ep100 solve_rate=0.797 mean_conflicts=0.72 +ep120 solve_rate=0.773 mean_conflicts=0.91 +ep140 solve_rate=0.747 mean_conflicts=1.25 +ep150 solve_rate=0.707 mean_conflicts=1.48 +[color_sage_full_none_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.8033 @ep80 (223.5s) + wrote /home/yurenh2/rrog/runs/ckpt_color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.pt +[sage/full] LE n=300 fail=0.20 | SOLVED +0.002 UNSOLVED +0.120 sep=+0.118 AUROC=0.680 mean_lam=+0.025 +[pe=none s3] deterministic solve_rate = 0.813 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.953 0.880 0.780 0.802 0.750 + wrote /home/yurenh2/rrog/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json +== A s3 conv=gat == +ep20 solve_rate=0.000 mean_conflicts=161.40 +ep40 solve_rate=0.027 mean_conflicts=28.43 +ep60 solve_rate=0.100 mean_conflicts=17.61 +ep80 solve_rate=0.063 mean_conflicts=13.36 +ep100 solve_rate=0.030 mean_conflicts=19.86 +ep120 solve_rate=0.007 mean_conflicts=53.33 +ep140 solve_rate=0.000 mean_conflicts=139.14 +ep150 solve_rate=0.000 mean_conflicts=140.87 +[color_gat_full_none_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.1 @ep60 (869.6s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gat_full_none_n50_k3_p0.2_T3_ns3_s3.pt +[gat/full] LE n=300 fail=0.90 | SOLVED -0.097 UNSOLVED -0.064 sep=+0.034 AUROC=0.585 mean_lam=-0.067 +[pe=none s3] deterministic solve_rate = 0.113 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.220 0.113 0.113 0.105 0.614 + wrote /home/yurenh2/rrog/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s3.json +== A s4 conv=gcn == +ep20 solve_rate=0.000 mean_conflicts=81.70 +ep40 solve_rate=0.000 mean_conflicts=39.68 +ep60 solve_rate=0.000 mean_conflicts=67.85 +ep80 solve_rate=0.000 mean_conflicts=58.58 +ep100 solve_rate=0.003 mean_conflicts=60.47 +ep120 solve_rate=0.000 mean_conflicts=54.07 +ep140 solve_rate=0.003 mean_conflicts=100.63 +ep150 solve_rate=0.003 mean_conflicts=106.05 +[color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.0033 @ep100 (676.5s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4.pt +[gcn/full] LE n=300 fail=1.00 | SOLVED -0.254 UNSOLVED -0.117 sep=+0.137 AUROC=0.943 mean_lam=-0.117 +[pe=none s4] deterministic solve_rate = 0.000 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.007 0.000 0.000 0.001 0.062 + wrote /home/yurenh2/rrog/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4.json +== A s4 conv=sage == +ep20 solve_rate=0.210 mean_conflicts=3.76 +ep40 solve_rate=0.717 mean_conflicts=0.97 +ep60 solve_rate=0.813 mean_conflicts=0.73 +ep80 solve_rate=0.803 mean_conflicts=0.72 +ep100 solve_rate=0.817 mean_conflicts=0.70 +ep120 solve_rate=0.817 mean_conflicts=0.65 +ep140 solve_rate=0.800 mean_conflicts=0.96 +ep150 solve_rate=0.773 mean_conflicts=1.14 +[color_sage_full_none_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.8167 @ep100 (215.8s) + wrote /home/yurenh2/rrog/runs/ckpt_color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.pt +[sage/full] LE n=300 fail=0.18 | SOLVED -0.011 UNSOLVED +0.182 sep=+0.193 AUROC=0.828 mean_lam=+0.024 +[pe=none s4] deterministic solve_rate = 0.840 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.987 0.893 0.847 0.835 0.752 + wrote /home/yurenh2/rrog/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json +== A s4 conv=gat == +ep20 solve_rate=0.000 mean_conflicts=155.28 +ep40 solve_rate=0.000 mean_conflicts=163.18 +ep60 solve_rate=0.000 mean_conflicts=111.24 +ep80 solve_rate=0.077 mean_conflicts=26.13 +ep100 solve_rate=0.060 mean_conflicts=47.08 +ep120 solve_rate=0.050 mean_conflicts=77.35 +ep140 solve_rate=0.080 mean_conflicts=76.13 +ep150 solve_rate=0.060 mean_conflicts=81.07 +[color_gat_full_none_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.08 @ep140 (871.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gat_full_none_n50_k3_p0.2_T3_ns3_s4.pt +[gat/full] LE n=300 fail=0.92 | SOLVED +0.013 UNSOLVED -0.019 sep=-0.032 AUROC=0.423 mean_lam=-0.016 +[pe=none s4] deterministic solve_rate = 0.133 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.227 0.147 0.120 0.113 0.454 + wrote /home/yurenh2/rrog/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s4.json +doneA=2026-06-16T18:14:25-05:00 diff --git a/runs/archB.log b/runs/archB.log new file mode 100644 index 0000000..fd9b1fb --- /dev/null +++ b/runs/archB.log @@ -0,0 +1,302 @@ +B start gpu=1 2026-06-16T15:29:24-05:00 +== B s0 conv=gps == +ep20 solve_rate=0.403 mean_conflicts=3.29 +ep40 solve_rate=0.437 mean_conflicts=2.99 +ep60 solve_rate=0.287 mean_conflicts=5.24 +ep80 solve_rate=0.463 mean_conflicts=2.91 +ep100 solve_rate=0.653 mean_conflicts=1.54 +ep120 solve_rate=0.797 mean_conflicts=0.81 +ep140 solve_rate=0.903 mean_conflicts=0.31 +ep150 solve_rate=0.913 mean_conflicts=0.29 +[color_gps_full_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.9133 @ep150 (591.9s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gps_full_none_n50_k3_p0.2_T3_ns3_s0.pt +[gps/full] LE n=300 fail=0.09 | SOLVED -0.390 UNSOLVED +0.044 sep=+0.434 AUROC=0.898 mean_lam=-0.352 +[pe=none s0] deterministic solve_rate = 0.940 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.987 0.960 0.920 0.925 0.819 + wrote /home/yurenh2/rrog/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s0.json +== B s0 gin pe=lappe == +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +ep20 solve_rate=0.000 mean_conflicts=161.60 +ep40 solve_rate=0.050 mean_conflicts=135.93 +ep60 solve_rate=0.253 mean_conflicts=47.45 +ep80 solve_rate=0.390 mean_conflicts=20.85 +ep100 solve_rate=0.090 mean_conflicts=71.30 +ep120 solve_rate=0.073 mean_conflicts=94.81 +ep140 solve_rate=0.073 mean_conflicts=61.36 +ep150 solve_rate=0.110 mean_conflicts=51.49 +[color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.39 @ep80 (150.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0.pt +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[gin/full] LE n=300 fail=0.61 | SOLVED -0.249 UNSOLVED -0.010 sep=+0.240 AUROC=0.843 mean_lam=-0.103 +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[pe=lappe s0] deterministic solve_rate = 0.420 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.760 0.600 0.387 0.378 0.839 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0.json +== B s0 gin pe=all == +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=36.32 +ep40 solve_rate=0.193 mean_conflicts=25.99 +ep60 solve_rate=0.260 mean_conflicts=53.12 +ep80 solve_rate=0.670 mean_conflicts=4.01 +ep100 solve_rate=0.543 mean_conflicts=30.14 +ep120 solve_rate=0.510 mean_conflicts=35.56 +ep140 solve_rate=0.557 mean_conflicts=28.97 +ep150 solve_rate=0.563 mean_conflicts=27.39 +[color_gin_full_all_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.67 @ep80 (151.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_all_n50_k3_p0.2_T3_ns3_s0.pt +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[gin/full] LE n=300 fail=0.33 | SOLVED -0.372 UNSOLVED +0.020 sep=+0.393 AUROC=0.875 mean_lam=-0.243 +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=all s0] deterministic solve_rate = 0.693 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.887 0.833 0.693 0.694 0.898 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s0.json +== B s1 conv=gps == +ep20 solve_rate=0.443 mean_conflicts=3.22 +ep40 solve_rate=0.350 mean_conflicts=4.18 +ep60 solve_rate=0.163 mean_conflicts=12.75 +ep80 solve_rate=0.397 mean_conflicts=4.12 +ep100 solve_rate=0.643 mean_conflicts=1.80 +ep120 solve_rate=0.837 mean_conflicts=0.64 +ep140 solve_rate=0.907 mean_conflicts=0.30 +ep150 solve_rate=0.927 mean_conflicts=0.30 +[color_gps_full_none_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.9267 @ep150 (2583.0s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gps_full_none_n50_k3_p0.2_T3_ns3_s1.pt +[gps/full] LE n=300 fail=0.07 | SOLVED -0.388 UNSOLVED +0.017 sep=+0.405 AUROC=0.863 mean_lam=-0.358 +[pe=none s1] deterministic solve_rate = 0.940 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.987 0.953 0.960 0.938 0.857 + wrote /home/yurenh2/rrog/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s1.json +== B s1 gin pe=lappe == +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +ep20 solve_rate=0.000 mean_conflicts=81.19 +ep40 solve_rate=0.193 mean_conflicts=23.68 +ep60 solve_rate=0.320 mean_conflicts=14.89 +ep80 solve_rate=0.397 mean_conflicts=7.99 +ep100 solve_rate=0.593 mean_conflicts=6.31 +ep120 solve_rate=0.247 mean_conflicts=63.22 +ep140 solve_rate=0.033 mean_conflicts=112.15 +ep150 solve_rate=0.017 mean_conflicts=118.57 +[color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.5933 @ep100 (224.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.pt +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[gin/full] LE n=300 fail=0.41 | SOLVED -0.233 UNSOLVED +0.025 sep=+0.258 AUROC=0.890 mean_lam=-0.128 +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[pe=lappe s1] deterministic solve_rate = 0.620 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.927 0.787 0.573 0.583 0.863 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.json +== B s1 gin pe=all == +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=57.12 +ep40 solve_rate=0.167 mean_conflicts=26.04 +ep60 solve_rate=0.190 mean_conflicts=119.01 +ep80 solve_rate=0.657 mean_conflicts=5.39 +ep100 solve_rate=0.643 mean_conflicts=16.68 +ep120 solve_rate=0.707 mean_conflicts=8.86 +ep140 solve_rate=0.697 mean_conflicts=10.20 +ep150 solve_rate=0.650 mean_conflicts=13.00 +[color_gin_full_all_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.7067 @ep120 (216.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_all_n50_k3_p0.2_T3_ns3_s1.pt +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[gin/full] LE n=300 fail=0.29 | SOLVED -0.214 UNSOLVED +0.091 sep=+0.305 AUROC=0.869 mean_lam=-0.125 +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=all s1] deterministic solve_rate = 0.760 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.940 0.820 0.773 0.735 0.878 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s1.json +== B s2 conv=gps == +ep20 solve_rate=0.390 mean_conflicts=3.38 +ep40 solve_rate=0.430 mean_conflicts=3.72 +ep60 solve_rate=0.173 mean_conflicts=12.65 +ep80 solve_rate=0.430 mean_conflicts=3.79 +ep100 solve_rate=0.660 mean_conflicts=1.73 +ep120 solve_rate=0.840 mean_conflicts=0.76 +ep140 solve_rate=0.913 mean_conflicts=0.34 +ep150 solve_rate=0.937 mean_conflicts=0.22 +[color_gps_full_none_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.9367 @ep150 (3039.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gps_full_none_n50_k3_p0.2_T3_ns3_s2.pt +[gps/full] LE n=300 fail=0.06 | SOLVED -0.410 UNSOLVED +0.012 sep=+0.422 AUROC=0.913 mean_lam=-0.384 +[pe=none s2] deterministic solve_rate = 0.953 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.980 0.953 0.927 0.935 0.872 + wrote /home/yurenh2/rrog/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s2.json +== B s2 gin pe=lappe == +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +ep20 solve_rate=0.000 mean_conflicts=109.99 +ep40 solve_rate=0.057 mean_conflicts=113.77 +ep60 solve_rate=0.087 mean_conflicts=31.41 +ep80 solve_rate=0.193 mean_conflicts=20.53 +ep100 solve_rate=0.373 mean_conflicts=25.48 +ep120 solve_rate=0.260 mean_conflicts=29.57 +ep140 solve_rate=0.197 mean_conflicts=45.54 +ep150 solve_rate=0.173 mean_conflicts=55.97 +[color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.3733 @ep100 (225.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2.pt +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[gin/full] LE n=300 fail=0.63 | SOLVED -0.206 UNSOLVED +0.000 sep=+0.206 AUROC=0.821 mean_lam=-0.077 +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[pe=lappe s2] deterministic solve_rate = 0.413 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.760 0.540 0.393 0.400 0.834 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2.json +== B s2 gin pe=all == +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=65.87 +ep40 solve_rate=0.327 mean_conflicts=21.26 +ep60 solve_rate=0.333 mean_conflicts=59.61 +ep80 solve_rate=0.097 mean_conflicts=67.57 +ep100 solve_rate=0.130 mean_conflicts=85.23 +ep120 solve_rate=0.160 mean_conflicts=68.36 +ep140 solve_rate=0.120 mean_conflicts=72.82 +ep150 solve_rate=0.100 mean_conflicts=68.99 +[color_gin_full_all_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.3333 @ep60 (233.5s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_all_n50_k3_p0.2_T3_ns3_s2.pt +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[gin/full] LE n=300 fail=0.67 | SOLVED -0.363 UNSOLVED -0.253 sep=+0.110 AUROC=0.623 mean_lam=-0.290 +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=all s2] deterministic solve_rate = 0.327 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.460 0.327 0.280 0.303 0.656 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s2.json +== B s3 conv=gps == +ep20 solve_rate=0.420 mean_conflicts=3.03 +ep40 solve_rate=0.457 mean_conflicts=2.82 +ep60 solve_rate=0.313 mean_conflicts=5.62 +ep80 solve_rate=0.457 mean_conflicts=3.50 +ep100 solve_rate=0.670 mean_conflicts=1.60 +ep120 solve_rate=0.823 mean_conflicts=0.81 +ep140 solve_rate=0.920 mean_conflicts=0.30 +ep150 solve_rate=0.943 mean_conflicts=0.23 +[color_gps_full_none_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.9433 @ep150 (3097.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.pt +[gps/full] LE n=300 fail=0.06 | SOLVED -0.397 UNSOLVED -0.056 sep=+0.341 AUROC=0.856 mean_lam=-0.378 +[pe=none s3] deterministic solve_rate = 0.933 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.987 0.973 0.953 0.940 0.866 + wrote /home/yurenh2/rrog/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json +== B s3 gin pe=lappe == +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +ep20 solve_rate=0.000 mean_conflicts=119.16 +ep40 solve_rate=0.127 mean_conflicts=97.26 +ep60 solve_rate=0.350 mean_conflicts=25.49 +ep80 solve_rate=0.523 mean_conflicts=6.35 +ep100 solve_rate=0.483 mean_conflicts=14.99 +ep120 solve_rate=0.353 mean_conflicts=36.89 +ep140 solve_rate=0.090 mean_conflicts=92.76 +ep150 solve_rate=0.063 mean_conflicts=95.97 +[color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.5233 @ep80 (234.0s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s3.pt +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[gin/full] LE n=300 fail=0.48 | SOLVED -0.311 UNSOLVED -0.045 sep=+0.266 AUROC=0.871 mean_lam=-0.184 +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[pe=lappe s3] deterministic solve_rate = 0.567 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.853 0.727 0.520 0.519 0.864 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s3.json +== B s3 gin pe=all == +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=63.12 +ep40 solve_rate=0.040 mean_conflicts=139.63 +ep60 solve_rate=0.457 mean_conflicts=22.17 +ep80 solve_rate=0.130 mean_conflicts=95.35 +ep100 solve_rate=0.097 mean_conflicts=82.22 +ep120 solve_rate=0.047 mean_conflicts=92.15 +ep140 solve_rate=0.027 mean_conflicts=93.55 +ep150 solve_rate=0.037 mean_conflicts=88.97 +[color_gin_full_all_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.4567 @ep60 (229.5s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_all_n50_k3_p0.2_T3_ns3_s3.pt +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[gin/full] LE n=300 fail=0.54 | SOLVED -0.265 UNSOLVED +0.014 sep=+0.280 AUROC=0.839 mean_lam=-0.113 +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=all s3] deterministic solve_rate = 0.467 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.760 0.627 0.427 0.456 0.891 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s3.json +== B s4 conv=gps == +ep20 solve_rate=0.440 mean_conflicts=3.41 +ep40 solve_rate=0.477 mean_conflicts=2.97 +ep60 solve_rate=0.420 mean_conflicts=3.52 +ep80 solve_rate=0.510 mean_conflicts=2.78 +ep100 solve_rate=0.660 mean_conflicts=1.68 +ep120 solve_rate=0.807 mean_conflicts=0.87 +ep140 solve_rate=0.930 mean_conflicts=0.31 +ep150 solve_rate=0.937 mean_conflicts=0.22 +[color_gps_full_none_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.9367 @ep150 (3113.0s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.pt +[gps/full] LE n=300 fail=0.06 | SOLVED -0.402 UNSOLVED +0.045 sep=+0.448 AUROC=0.936 mean_lam=-0.374 +[pe=none s4] deterministic solve_rate = 0.960 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.993 0.967 0.947 0.952 0.900 + wrote /home/yurenh2/rrog/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json +== B s4 gin pe=lappe == +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +ep20 solve_rate=0.000 mean_conflicts=96.50 +ep40 solve_rate=0.150 mean_conflicts=33.60 +ep60 solve_rate=0.313 mean_conflicts=31.99 +ep80 solve_rate=0.333 mean_conflicts=28.49 +ep100 solve_rate=0.260 mean_conflicts=36.77 +ep120 solve_rate=0.180 mean_conflicts=38.74 +ep140 solve_rate=0.147 mean_conflicts=47.98 +ep150 solve_rate=0.133 mean_conflicts=51.20 +[color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.3333 @ep80 (229.4s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4.pt +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[gin/full] LE n=300 fail=0.67 | SOLVED -0.220 UNSOLVED -0.063 sep=+0.156 AUROC=0.776 mean_lam=-0.115 +/home/yurenh2/rrog/diag/train_color.py:90: RuntimeWarning: divide by zero encountered in divide + di = np.where(deg > 0, 1.0 / np.sqrt(deg), 0.0) +[pe=lappe s4] deterministic solve_rate = 0.340 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.753 0.507 0.307 0.333 0.784 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4.json +== B s4 gin pe=all == +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=64.98 +ep40 solve_rate=0.360 mean_conflicts=13.46 +ep60 solve_rate=0.567 mean_conflicts=22.46 +ep80 solve_rate=0.523 mean_conflicts=32.14 +ep100 solve_rate=0.287 mean_conflicts=53.76 +ep120 solve_rate=0.343 mean_conflicts=43.17 +ep140 solve_rate=0.200 mean_conflicts=60.30 +ep150 solve_rate=0.177 mean_conflicts=63.07 +[color_gin_full_all_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.5667 @ep60 (233.8s) + wrote /home/yurenh2/rrog/runs/ckpt_color_gin_full_all_n50_k3_p0.2_T3_ns3_s4.pt +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[gin/full] LE n=300 fail=0.43 | SOLVED -0.376 UNSOLVED -0.027 sep=+0.349 AUROC=0.879 mean_lam=-0.225 +/home/yurenh2/rrog/diag/train_color.py:84: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=all s4] deterministic solve_rate = 0.593 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.787 0.707 0.567 0.575 0.901 + wrote /home/yurenh2/rrog/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s4.json +doneB=2026-06-16T21:03:05-05:00 diff --git a/runs/cin_sweep.log b/runs/cin_sweep.log new file mode 100644 index 0000000..c1759c1 --- /dev/null +++ b/runs/cin_sweep.log @@ -0,0 +1,58 @@ +PPGN done -> CIN +CIN start gpu=1 2026-06-17T04:31:06-05:00 +== cin s0 == +ep20 solve=0.063 +ep40 solve=0.423 +ep60 solve=0.340 +ep80 solve=0.397 +ep100 solve=0.417 +ep120 solve=0.460 +ep140 solve=0.477 +ep150 solve=0.470 +[cin/full] solve=0.477 LE AUROC=0.763 mean_lam=+0.074 passK=0.473 lamsel=0.473 (639s) + wrote cin_full_none_n50_k3_p0.2_T3_ns3_s0 +== cin s1 == +ep20 solve=0.013 +ep40 solve=0.413 +ep60 solve=0.443 +ep80 solve=0.467 +ep100 solve=0.313 +ep120 solve=0.507 +ep140 solve=0.533 +ep150 solve=0.520 +[cin/full] solve=0.533 LE AUROC=0.763 mean_lam=+0.134 passK=0.553 lamsel=0.553 (1125s) + wrote cin_full_none_n50_k3_p0.2_T3_ns3_s1 +== cin s2 == +ep20 solve=0.080 +ep40 solve=0.413 +ep60 solve=0.360 +ep80 solve=0.403 +ep100 solve=0.510 +ep120 solve=0.453 +ep140 solve=0.483 +ep150 solve=0.517 +[cin/full] solve=0.517 LE AUROC=0.713 mean_lam=+0.087 passK=0.567 lamsel=0.567 (1127s) + wrote cin_full_none_n50_k3_p0.2_T3_ns3_s2 +== cin s3 == +ep20 solve=0.070 +ep40 solve=0.470 +ep60 solve=0.453 +ep80 solve=0.493 +ep100 solve=0.463 +ep120 solve=0.550 +ep140 solve=0.597 +ep150 solve=0.577 +[cin/full] solve=0.597 LE AUROC=0.655 mean_lam=+0.162 passK=0.587 lamsel=0.587 (1112s) + wrote cin_full_none_n50_k3_p0.2_T3_ns3_s3 +== cin s4 == +ep20 solve=0.037 +ep40 solve=0.193 +ep60 solve=0.223 +ep80 solve=0.393 +ep100 solve=0.510 +ep120 solve=0.457 +ep140 solve=0.423 +ep150 solve=0.463 +[cin/full] solve=0.510 LE AUROC=0.752 mean_lam=+0.123 passK=0.527 lamsel=0.527 (1127s) + wrote cin_full_none_n50_k3_p0.2_T3_ns3_s4 +doneCIN=2026-06-17T05:57:37-05:00 diff --git a/runs/color_1step_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_1step_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..56cc6f8 --- /dev/null +++ b/runs/color_1step_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,22 @@ +{ + "task": "graph3coloring", + "tag": "color_1step_n50_k3_p0.2_T3_ns3_s0", + "mode": "train", + "grad_mode": "1step", + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 0, + "sec": 121.4, + "ep": 150, + "solve_rate": 0.2833, + "mean_conflicts": 5.193 +} \ No newline at end of file diff --git a/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..17e736a --- /dev/null +++ b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_1step_none_n50_k3_p0.2_T3_ns3_s0", + "mode": "train", + "grad_mode": "1step", + "pe": "none", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "sec": 127.1, + "ep": 60, + "solve_rate": 0.2, + "mean_conflicts": 18.333 +} \ No newline at end of file diff --git a/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..4c6ec55 --- /dev/null +++ b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_1step_none_n50_k3_p0.2_T3_ns3_s1", + "mode": "train", + "grad_mode": "1step", + "pe": "none", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 1, + "in_dim": 8, + "sec": 123.3, + "ep": 80, + "solve_rate": 0.3333, + "mean_conflicts": 8.7 +} \ No newline at end of file diff --git a/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..5a049d9 --- /dev/null +++ b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_1step_none_n50_k3_p0.2_T3_ns3_s2", + "mode": "train", + "grad_mode": "1step", + "pe": "none", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 2, + "in_dim": 8, + "sec": 131.6, + "ep": 100, + "solve_rate": 0.3567, + "mean_conflicts": 4.67 +} \ No newline at end of file diff --git a/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..cc9da6e --- /dev/null +++ b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_1step_none_n50_k3_p0.2_T3_ns3_s3", + "mode": "train", + "grad_mode": "1step", + "pe": "none", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 3, + "in_dim": 8, + "sec": 124.3, + "ep": 120, + "solve_rate": 0.3367, + "mean_conflicts": 7.227 +} \ No newline at end of file diff --git a/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..51bab30 --- /dev/null +++ b/runs/color_1step_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_1step_none_n50_k3_p0.2_T3_ns3_s4", + "mode": "train", + "grad_mode": "1step", + "pe": "none", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 4, + "in_dim": 8, + "sec": 120.8, + "ep": 60, + "solve_rate": 0.2367, + "mean_conflicts": 22.393 +} \ No newline at end of file diff --git a/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..3580f31 --- /dev/null +++ b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 0, "solve_rate": 0.4766666666666667} \ No newline at end of file diff --git a/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..cbd69ae --- /dev/null +++ b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 1, "solve_rate": 0.5333333333333333} \ No newline at end of file diff --git a/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..887f539 --- /dev/null +++ b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 2, "solve_rate": 0.5166666666666667} \ No newline at end of file diff --git a/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..2e3be07 --- /dev/null +++ b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 3, "solve_rate": 0.5966666666666667} \ No newline at end of file diff --git a/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..cd8d485 --- /dev/null +++ b/runs/color_cin_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 4, "solve_rate": 0.51} \ No newline at end of file diff --git a/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..ebd9a08 --- /dev/null +++ b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 0, "solve_rate": 0.49666666666666665} \ No newline at end of file diff --git a/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..481b197 --- /dev/null +++ b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 1, "solve_rate": 0.48333333333333334} \ No newline at end of file diff --git a/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..9f89fcc --- /dev/null +++ b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 2, "solve_rate": 0.7133333333333334} \ No newline at end of file diff --git a/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..cc17641 --- /dev/null +++ b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 3, "solve_rate": 0.5633333333333334} \ No newline at end of file diff --git a/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..4f05b5c --- /dev/null +++ b/runs/color_esan_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 4, "solve_rate": 0.67} \ No newline at end of file diff --git a/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..3072e52 --- /dev/null +++ b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_full_gsn_n50_k3_p0.2_T3_ns3_s0", + "mode": "train", + "grad_mode": "full", + "pe": "gsn", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 10, + "sec": 153.5, + "ep": 80, + "solve_rate": 0.6433, + "mean_conflicts": 2.77 +} \ No newline at end of file diff --git a/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s1.json b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..90e63c6 --- /dev/null +++ b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_full_gsn_n50_k3_p0.2_T3_ns3_s1", + "mode": "train", + "grad_mode": "full", + "pe": "gsn", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 1, + "in_dim": 10, + "sec": 150.6, + "ep": 80, + "solve_rate": 0.5333, + "mean_conflicts": 19.95 +} \ No newline at end of file diff --git a/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s2.json b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..293548e --- /dev/null +++ b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_full_gsn_n50_k3_p0.2_T3_ns3_s2", + "mode": "train", + "grad_mode": "full", + "pe": "gsn", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 2, + "in_dim": 10, + "sec": 154.1, + "ep": 80, + "solve_rate": 0.65, + "mean_conflicts": 9.427 +} \ No newline at end of file diff --git a/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..a7108c4 --- /dev/null +++ b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_full_gsn_n50_k3_p0.2_T3_ns3_s3", + "mode": "train", + "grad_mode": "full", + "pe": "gsn", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 3, + "in_dim": 10, + "sec": 150.0, + "ep": 80, + "solve_rate": 0.5767, + "mean_conflicts": 7.477 +} \ No newline at end of file diff --git a/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..4978587 --- /dev/null +++ b/runs/color_full_gsn_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_full_gsn_n50_k3_p0.2_T3_ns3_s4", + "mode": "train", + "grad_mode": "full", + "pe": "gsn", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 4, + "in_dim": 10, + "sec": 153.1, + "ep": 100, + "solve_rate": 0.5767, + "mean_conflicts": 7.393 +} \ No newline at end of file diff --git a/runs/color_full_n50_k3_p0.15_T3_ns3_s0.json b/runs/color_full_n50_k3_p0.15_T3_ns3_s0.json new file mode 100644 index 0000000..e31bd27 --- /dev/null +++ b/runs/color_full_n50_k3_p0.15_T3_ns3_s0.json @@ -0,0 +1,22 @@ +{ + "task": "graph3coloring", + "tag": "color_full_n50_k3_p0.15_T3_ns3_s0", + "mode": "train", + "grad_mode": "full", + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.15, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 120, + "lr": 0.001, + "bs": 32, + "seed": 0, + "sec": 116.5, + "ep": 60, + "solve_rate": 0.2033, + "mean_conflicts": 3.24 +} \ No newline at end of file diff --git a/runs/color_full_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_full_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..3b96fd4 --- /dev/null +++ b/runs/color_full_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,22 @@ +{ + "task": "graph3coloring", + "tag": "color_full_n50_k3_p0.2_T3_ns3_s0", + "mode": "train", + "grad_mode": "full", + "ckpt": null, + "n": 50, + "k": 3, 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a/runs/color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1.json b/runs/color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..a0f3b6c --- /dev/null +++ b/runs/color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,26 @@ +{ + "task": "graph3coloring", + "tag": "color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1", + "mode": "train", + "grad_mode": "full", + "pe": "none", + "contract": true, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 1, + "in_dim": 8, + "sec": 206.4, + "ep": 20, + "solve_rate": 0.0, + "mean_conflicts": 107.593 +} \ No newline at end of file diff --git a/runs/color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2.json b/runs/color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..13e785a --- /dev/null +++ b/runs/color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,26 @@ +{ + "task": "graph3coloring", + "tag": 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a/runs/color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..9dd65cd --- /dev/null +++ b/runs/color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,25 @@ +{ + "task": "graph3coloring", + "tag": "color_full_rwse_n50_k3_p0.2_T3_ns3_s4", + "mode": "train", + "grad_mode": "full", + "pe": "rwse", + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 4, + "in_dim": 24, + "sec": 154.2, + "ep": 100, + "solve_rate": 0.5467, + "mean_conflicts": 6.193 +} \ No newline at end of file diff --git a/runs/color_full_sub_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_full_sub_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..3190cee --- /dev/null +++ b/runs/color_full_sub_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,26 @@ +{ + "task": "graph3coloring", + "tag": "color_full_sub_n50_k3_p0.2_T3_ns3_s0", + "mode": 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end of file diff --git a/runs/color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..9e7baec --- /dev/null +++ b/runs/color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3", + "mode": "train", + "conv": "gcn", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 3, + "in_dim": 8, + "sec": 675.0, + "ep": 100, + "solve_rate": 0.0033, + "mean_conflicts": 69.257 +} \ No newline at end of file diff --git a/runs/color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..f4e9c85 --- /dev/null +++ b/runs/color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,27 @@ +{ + 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index 0000000..e9c392f --- /dev/null +++ b/runs/color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1", + "mode": "train", + "conv": "gin", + "grad_mode": "full", + "pe": "lappe", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 1, + "in_dim": 16, + "sec": 224.3, + "ep": 100, + "solve_rate": 0.5933, + "mean_conflicts": 6.31 +} \ No newline at end of file diff --git a/runs/color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2.json b/runs/color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..36be7ed --- /dev/null +++ b/runs/color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2", + "mode": "train", + "conv": "gin", + "grad_mode": "full", + 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b/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_gps_full_none_n50_k3_p0.2_T3_ns3_s0", + "mode": "train", + "conv": "gps", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "sec": 591.9, + "ep": 150, + "solve_rate": 0.9133, + "mean_conflicts": 0.287 +} \ No newline at end of file diff --git a/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..5c5cc97 --- /dev/null +++ b/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_gps_full_none_n50_k3_p0.2_T3_ns3_s1", + "mode": "train", + "conv": "gps", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + 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end of file diff --git a/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..7adf4c6 --- /dev/null +++ b/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_gps_full_none_n50_k3_p0.2_T3_ns3_s3", + "mode": "train", + "conv": "gps", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 3, + "in_dim": 8, + "sec": 3097.1, + "ep": 150, + "solve_rate": 0.9433, + "mean_conflicts": 0.227 +} \ No newline at end of file diff --git a/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..4128e17 --- /dev/null +++ b/runs/color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,27 @@ +{ + 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b/runs/color_pna_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..0abace8 --- /dev/null +++ b/runs/color_pna_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_pna_full_none_n50_k3_p0.2_T3_ns3_s2", + "mode": "train", + "conv": "pna", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 2, + "in_dim": 8, + "sec": 714.9, + "ep": 150, + "solve_rate": 0.9167, + "mean_conflicts": 0.197 +} \ No newline at end of file diff --git a/runs/color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..c8c6c59 --- /dev/null +++ b/runs/color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": 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a/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..0af6f22 --- /dev/null +++ b/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,8 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 2, + "solve_rate": 0.9333333333333333 +} \ No newline at end of file diff --git a/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..69cda09 --- /dev/null +++ b/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,8 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 3, + "solve_rate": 0.9466666666666667 +} \ No newline at end of file diff --git a/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..748da35 --- /dev/null +++ b/runs/color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,8 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 4, + "solve_rate": 0.9233333333333333 +} \ No newline at end of file diff --git a/runs/color_rrog_attn_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json b/runs/color_rrog_attn_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json new file mode 100644 index 0000000..eb12b67 --- /dev/null +++ b/runs/color_rrog_attn_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json @@ -0,0 +1,32 @@ +{ + "task": "graph3coloring", + "tag": "color_rrog_attn_gin_full_none_n50_k3_p0.2_T1_ns3_s0", + "mode": "train", + "conv": "gin", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 1, + "n_sup": 3, + "epochs": 80, + "agg_layers": 1, + "compute_layers": 2, + "compute": "attn", + "attn_heads": 4, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "arch": "rrog_once_agg_hidden_compute", + "sec": 96.3, + "ep": 20, + "solve_rate": 0.0, + "mean_conflicts": 50.673 +} \ No newline at end of file diff --git a/runs/color_rrog_gin_1step_none_n12_k3_p0.2_T2_ns2_s7.json b/runs/color_rrog_gin_1step_none_n12_k3_p0.2_T2_ns2_s7.json new file mode 100644 index 0000000..4c3017b --- /dev/null +++ b/runs/color_rrog_gin_1step_none_n12_k3_p0.2_T2_ns2_s7.json @@ -0,0 +1,30 @@ +{ + "task": "graph3coloring", + "tag": "color_rrog_gin_1step_none_n12_k3_p0.2_T2_ns2_s7", + "mode": "train", + "conv": "gin", + "grad_mode": "1step", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 12, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 16, + "T": 2, + "n_sup": 2, + "epochs": 1, + "agg_layers": 1, + "compute_layers": 2, + "lr": 0.001, + "bs": 1024, + "seed": 7, + "in_dim": 8, + "arch": "rrog_once_agg_node_compute", + "sec": 1.4, + "ep": 1, + "solve_rate": 0.0, + "mean_conflicts": 8.867 +} \ No newline at end of file diff --git a/runs/color_rrog_gin_full_none_n12_k3_p0.2_T2_ns2_s7.json b/runs/color_rrog_gin_full_none_n12_k3_p0.2_T2_ns2_s7.json new file mode 100644 index 0000000..4074d2a --- /dev/null +++ b/runs/color_rrog_gin_full_none_n12_k3_p0.2_T2_ns2_s7.json @@ -0,0 +1,30 @@ +{ + "task": "graph3coloring", + "tag": "color_rrog_gin_full_none_n12_k3_p0.2_T2_ns2_s7", + "mode": "train", + "conv": "gin", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 12, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 16, + "T": 2, + "n_sup": 2, + "epochs": 1, + "agg_layers": 1, + "compute_layers": 2, + "lr": 0.001, + "bs": 1024, + "seed": 7, + "in_dim": 8, + "arch": "rrog_once_agg_node_compute", + "sec": 1.4, + "ep": 1, + "solve_rate": 0.0, + "mean_conflicts": 8.867 +} \ No newline at end of file diff --git a/runs/color_rrog_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json b/runs/color_rrog_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json new file mode 100644 index 0000000..78fdd5c --- /dev/null +++ b/runs/color_rrog_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json @@ -0,0 +1,30 @@ +{ + "task": "graph3coloring", + "tag": "color_rrog_gin_full_none_n50_k3_p0.2_T1_ns3_s0", + "mode": "train", + "conv": "gin", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 1, + "n_sup": 3, + "epochs": 150, + "agg_layers": 1, + "compute_layers": 2, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "arch": "rrog_once_agg_node_compute", + "sec": 127.8, + "ep": 20, + "solve_rate": 0.0, + "mean_conflicts": 61.333 +} \ No newline at end of file diff --git a/runs/color_rrog_gin_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_rrog_gin_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..8cdba1c --- /dev/null +++ b/runs/color_rrog_gin_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,30 @@ +{ + "task": "graph3coloring", + "tag": "color_rrog_gin_full_none_n50_k3_p0.2_T3_ns3_s0", + "mode": "train", + "conv": "gin", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "agg_layers": 1, + "compute_layers": 2, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "arch": "rrog_once_agg_node_compute", + "sec": 141.4, + "ep": 20, + "solve_rate": 0.0, + "mean_conflicts": 66.637 +} \ No newline at end of file diff --git a/runs/color_rrog_node_gcn_full_none_n50_k3_p0.2_T0_ns3_s0.json b/runs/color_rrog_node_gcn_full_none_n50_k3_p0.2_T0_ns3_s0.json new file mode 100644 index 0000000..3a1a8bf --- /dev/null +++ b/runs/color_rrog_node_gcn_full_none_n50_k3_p0.2_T0_ns3_s0.json @@ -0,0 +1,32 @@ +{ + "task": "graph3coloring", + "tag": "color_rrog_node_gcn_full_none_n50_k3_p0.2_T0_ns3_s0", + "mode": "train", + "conv": "gcn", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 0, + "n_sup": 3, + "epochs": 150, + "agg_layers": 4, + "compute_layers": 2, + "compute": "node", + "attn_heads": 4, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "arch": "rrog_once_agg_hidden_compute", + "sec": 72.9, + "ep": 120, + "solve_rate": 0.0067, + "mean_conflicts": 20.977 +} \ No newline at end of file diff --git a/runs/color_rrog_node_gin_full_none_n50_k3_p0.2_T0_ns3_s0.json b/runs/color_rrog_node_gin_full_none_n50_k3_p0.2_T0_ns3_s0.json new file mode 100644 index 0000000..0df9c45 --- /dev/null +++ b/runs/color_rrog_node_gin_full_none_n50_k3_p0.2_T0_ns3_s0.json @@ -0,0 +1,32 @@ +{ + "task": "graph3coloring", + "tag": "color_rrog_node_gin_full_none_n50_k3_p0.2_T0_ns3_s0", + "mode": "train", + "conv": "gin", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 0, + "n_sup": 3, + "epochs": 150, + "agg_layers": 4, + "compute_layers": 2, + "compute": "node", + "attn_heads": 4, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "arch": "rrog_once_agg_hidden_compute", + "sec": 69.4, + "ep": 20, + "solve_rate": 0.0, + "mean_conflicts": 81.17 +} \ No newline at end of file diff --git a/runs/color_rrog_node_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json b/runs/color_rrog_node_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json new file mode 100644 index 0000000..bdd9c8a --- /dev/null +++ b/runs/color_rrog_node_gin_full_none_n50_k3_p0.2_T1_ns3_s0.json @@ -0,0 +1,32 @@ +{ + "task": "graph3coloring", + "tag": "color_rrog_node_gin_full_none_n50_k3_p0.2_T1_ns3_s0", + "mode": "train", + "conv": "gin", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 1, + "n_sup": 3, + "epochs": 80, + "agg_layers": 4, + "compute_layers": 2, + "compute": "node", + "attn_heads": 4, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "arch": "rrog_once_agg_hidden_compute", + "sec": 54.3, + "ep": 20, + "solve_rate": 0.0, + "mean_conflicts": 58.17 +} \ No newline at end of file diff --git a/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..3a7c8e5 --- /dev/null +++ b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_sage_full_none_n50_k3_p0.2_T3_ns3_s0", + "mode": "train", + "conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 0, + "in_dim": 8, + "sec": 163.3, + "ep": 60, + "solve_rate": 0.73, + "mean_conflicts": 1.087 +} \ No newline at end of file diff --git a/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..5756b5f --- /dev/null +++ b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_sage_full_none_n50_k3_p0.2_T3_ns3_s1", + "mode": "train", + "conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 1, + "in_dim": 8, + "sec": 159.8, + "ep": 120, + "solve_rate": 0.7867, + "mean_conflicts": 0.777 +} \ No newline at end of file diff --git a/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..ac70950 --- /dev/null +++ b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_sage_full_none_n50_k3_p0.2_T3_ns3_s2", + "mode": "train", + "conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 2, + "in_dim": 8, + "sec": 224.4, + "ep": 60, + "solve_rate": 0.83, + "mean_conflicts": 0.677 +} \ No newline at end of file diff --git a/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..36cb84b --- /dev/null +++ b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_sage_full_none_n50_k3_p0.2_T3_ns3_s3", + "mode": "train", + "conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 3, + "in_dim": 8, + "sec": 223.5, + "ep": 80, + "solve_rate": 0.8033, + "mean_conflicts": 0.713 +} \ No newline at end of file diff --git a/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..6c7d058 --- /dev/null +++ b/runs/color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,27 @@ +{ + "task": "graph3coloring", + "tag": "color_sage_full_none_n50_k3_p0.2_T3_ns3_s4", + "mode": "train", + "conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "rwse_k": 16, + "ckpt": null, + "n": 50, + "k": 3, + "p": 0.2, + "r": 8, + "hidden": 128, + "T": 3, + "n_sup": 3, + "epochs": 150, + "lr": 0.001, + "bs": 32, + "seed": 4, + "in_dim": 8, + "sec": 215.8, + "ep": 100, + "solve_rate": 0.8167, + "mean_conflicts": 0.697 +} \ No newline at end of file diff --git a/runs/color_sweep.log b/runs/color_sweep.log new file mode 100644 index 0000000..f93d0ac --- /dev/null +++ b/runs/color_sweep.log @@ -0,0 +1,27 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T10:47:27-05:00 +===== train full ===== +ep20 solve_rate=0.000 mean_conflicts=159.45 +ep40 solve_rate=0.137 mean_conflicts=51.42 +ep60 solve_rate=0.503 mean_conflicts=19.50 +ep80 solve_rate=0.357 mean_conflicts=56.76 +ep100 solve_rate=0.060 mean_conflicts=115.03 +ep120 solve_rate=0.007 mean_conflicts=113.40 +ep140 solve_rate=0.003 mean_conflicts=102.39 +ep150 solve_rate=0.003 mean_conflicts=101.91 +[color_full_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.5033 mean_conflicts=19.497 @ep60 (153.7s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_n50_k3_p0.2_T3_ns3_s0.pt +===== train 1step ===== +ep20 solve_rate=0.000 mean_conflicts=43.71 +ep40 solve_rate=0.120 mean_conflicts=14.24 +ep60 solve_rate=0.250 mean_conflicts=12.98 +ep80 solve_rate=0.273 mean_conflicts=5.86 +ep100 solve_rate=0.237 mean_conflicts=6.15 +ep120 solve_rate=0.257 mean_conflicts=6.03 +ep140 solve_rate=0.223 mean_conflicts=5.50 +ep150 solve_rate=0.283 mean_conflicts=5.19 +[color_1step_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.2833 mean_conflicts=5.193 @ep150 (121.4s) + wrote /home/yurenh2/rrog/runs/ckpt_color_1step_n50_k3_p0.2_T3_ns3_s0.pt +===== LE diagnostic (lambda1: solved vs unsolved) ===== +[full] LE n=300 fail_rate=0.50 | lambda1 SOLVED mean -0.4828 (n=151) | UNSOLVED mean -0.1333 (n=149) | sep=+0.3495 | AUROC(fail|lambda1)=0.871 | mean_lambda1=-0.3092 +[1step] LE n=300 fail_rate=0.72 | lambda1 SOLVED mean +0.0215 (n=85) | UNSOLVED mean +0.2097 (n=215) | sep=+0.1882 | AUROC(fail|lambda1)=0.814 | mean_lambda1=+0.1564 +done=2026-06-16T10:52:55-05:00 diff --git a/runs/cyc_gcn_none_L5_s0.json b/runs/cyc_gcn_none_L5_s0.json new file mode 100644 index 0000000..8e3a5c2 --- /dev/null +++ b/runs/cyc_gcn_none_L5_s0.json @@ -0,0 +1,32 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "gcn_none_L5_s0", + "conv": "gcn", + "feat": "none", + "layers": 5, + "hidden": 128, + "rni_dim": 16, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "seed": 0, + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "sec": 127.8, + "dev": "cuda", + "ep": 200, + "train_mae": [ + 0.05943963676691055, + 0.08676010370254517 + ], + "val_mae": [ + 0.15079250931739807, + 0.20910263061523438 + ], + "test_mae": [ + 0.1485612541437149, + 0.21971328556537628 + ] +} \ No newline at end of file diff --git a/runs/cyc_gin_none_L5_s0.json b/runs/cyc_gin_none_L5_s0.json new file mode 100644 index 0000000..7b53fb3 --- /dev/null +++ b/runs/cyc_gin_none_L5_s0.json @@ -0,0 +1,32 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "gin_none_L5_s0", + "conv": "gin", + "feat": "none", + "layers": 5, + "hidden": 128, + "rni_dim": 16, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "seed": 0, + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "sec": 125.5, + "dev": "cuda", + "ep": 200, + "train_mae": [ + 0.00937615055590868, + 0.02337666228413582 + ], + "val_mae": [ + 0.05451786890625954, + 0.09657028317451477 + ], + "test_mae": [ + 0.052763670682907104, + 0.08840502053499222 + ] +} \ No newline at end of file diff --git a/runs/cyc_gin_rni_L5_s0.json b/runs/cyc_gin_rni_L5_s0.json new file mode 100644 index 0000000..3fb13b3 --- /dev/null +++ b/runs/cyc_gin_rni_L5_s0.json @@ -0,0 +1,32 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "gin_rni_L5_s0", + "conv": "gin", + "feat": "rni", + "layers": 5, + "hidden": 128, + "rni_dim": 16, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "seed": 0, + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "sec": 134.3, + "dev": "cuda", + "ep": 200, + "train_mae": [ + 0.012719802558422089, + 0.02454240433871746 + ], + "val_mae": [ + 0.06555940210819244, + 0.10593626648187637 + ], + "test_mae": [ + 0.052439868450164795, + 0.0945335254073143 + ] +} \ No newline at end of file diff --git a/runs/cyc_gin_rwse_L5_s0.json b/runs/cyc_gin_rwse_L5_s0.json new file mode 100644 index 0000000..59f13e7 --- /dev/null +++ b/runs/cyc_gin_rwse_L5_s0.json @@ -0,0 +1,32 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "gin_rwse_L5_s0", + "conv": "gin", + "feat": "rwse", + "layers": 5, + "hidden": 128, + "rni_dim": 16, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "seed": 0, + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "sec": 125.3, + "dev": "cuda", + "ep": 200, + "train_mae": [ + 0.005093096289783716, + 0.011449216865003109 + ], + "val_mae": [ + 0.009772364050149918, + 0.020356670022010803 + ], + "test_mae": [ + 0.008741355501115322, + 0.016079651191830635 + ] +} \ No newline at end of file diff --git a/runs/cycle_sweep.log b/runs/cycle_sweep.log new file mode 100644 index 0000000..04a3494 --- /dev/null +++ b/runs/cycle_sweep.log @@ -0,0 +1,54 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T08:59:16-05:00 +===== --conv gin --feat none ===== +ep20 val_mae(c5,c6)=[0.402, 0.44] +ep40 val_mae(c5,c6)=[0.225, 0.404] +ep60 val_mae(c5,c6)=[0.128, 0.188] +ep80 val_mae(c5,c6)=[0.09, 0.169] +ep100 val_mae(c5,c6)=[0.078, 0.124] +ep120 val_mae(c5,c6)=[0.062, 0.106] +ep140 val_mae(c5,c6)=[0.081, 0.136] +ep160 val_mae(c5,c6)=[0.056, 0.104] +ep180 val_mae(c5,c6)=[0.056, 0.097] +ep200 val_mae(c5,c6)=[0.055, 0.097] +[gin_none_L5_s0] train_mae(c5,c6)=[0.009, 0.023] test_mae=[0.053, 0.088] (raw rings; std=[0.78, 0.95]) @ep200 (125.5s) + wrote /home/yurenh2/rrog/runs/cyc_gin_none_L5_s0.json +===== --conv gcn --feat none ===== +ep20 val_mae(c5,c6)=[0.451, 0.691] +ep40 val_mae(c5,c6)=[0.352, 1.192] +ep60 val_mae(c5,c6)=[0.284, 0.438] +ep80 val_mae(c5,c6)=[0.234, 0.287] +ep100 val_mae(c5,c6)=[0.221, 0.333] +ep120 val_mae(c5,c6)=[0.201, 0.369] +ep140 val_mae(c5,c6)=[0.195, 0.264] +ep160 val_mae(c5,c6)=[0.153, 0.212] +ep180 val_mae(c5,c6)=[0.152, 0.212] +ep200 val_mae(c5,c6)=[0.151, 0.209] +[gcn_none_L5_s0] train_mae(c5,c6)=[0.059, 0.087] test_mae=[0.149, 0.22] (raw rings; std=[0.78, 0.95]) @ep200 (127.8s) + wrote /home/yurenh2/rrog/runs/cyc_gcn_none_L5_s0.json +===== --conv gin --feat rni ===== +ep20 val_mae(c5,c6)=[0.212, 0.288] +ep40 val_mae(c5,c6)=[0.161, 0.273] +ep60 val_mae(c5,c6)=[0.116, 0.226] +ep80 val_mae(c5,c6)=[0.14, 0.185] +ep100 val_mae(c5,c6)=[0.095, 0.139] +ep120 val_mae(c5,c6)=[0.08, 0.12] +ep140 val_mae(c5,c6)=[0.073, 0.117] +ep160 val_mae(c5,c6)=[0.069, 0.111] +ep180 val_mae(c5,c6)=[0.067, 0.107] +ep200 val_mae(c5,c6)=[0.066, 0.106] +[gin_rni_L5_s0] train_mae(c5,c6)=[0.013, 0.025] test_mae=[0.052, 0.095] (raw rings; std=[0.78, 0.95]) @ep200 (134.3s) + wrote /home/yurenh2/rrog/runs/cyc_gin_rni_L5_s0.json +===== --conv gin --feat rwse ===== +ep20 val_mae(c5,c6)=[0.09, 0.974] +ep40 val_mae(c5,c6)=[0.074, 0.268] +ep60 val_mae(c5,c6)=[0.069, 0.734] +ep80 val_mae(c5,c6)=[0.041, 0.347] +ep100 val_mae(c5,c6)=[0.054, 0.22] +ep120 val_mae(c5,c6)=[0.028, 0.092] +ep140 val_mae(c5,c6)=[0.017, 0.048] +ep160 val_mae(c5,c6)=[0.017, 0.053] +ep180 val_mae(c5,c6)=[0.01, 0.021] +ep200 val_mae(c5,c6)=[0.01, 0.02] +[gin_rwse_L5_s0] train_mae(c5,c6)=[0.005, 0.011] test_mae=[0.009, 0.016] (raw rings; std=[0.78, 0.95]) @ep200 (125.3s) + wrote /home/yurenh2/rrog/runs/cyc_gin_rwse_L5_s0.json +done=2026-06-16T09:08:37-05:00 diff --git a/runs/diag_csl_gcn_L4_s0.json b/runs/diag_csl_gcn_L4_s0.json new file mode 100644 index 0000000..a244c96 --- /dev/null +++ b/runs/diag_csl_gcn_L4_s0.json @@ -0,0 +1,24 @@ +{ + "task": "csl", + "model": "gcn", + "layers": 4, + "seed": 0, + "kind": null, + "n": 150, + "n_train": 100, + "n_test": 50, + "conv_round": 1, + "sec": 5.3, + "dev": "cuda", + "train_acc": 0.1, + "test_acc": 0.1, + "wl_ceiling_acc_converged": 0.1, + "wl_ceiling_acc_Ldepth": 0.1, + "test_bucket_counts": { + "H2": 50 + }, + "failure_bucket_counts": { + "H2": 45 + }, + "n_failures": 45 +} \ No newline at end of file diff --git a/runs/diag_csl_gin_L4_s0.json b/runs/diag_csl_gin_L4_s0.json new file mode 100644 index 0000000..d3a2432 --- /dev/null +++ b/runs/diag_csl_gin_L4_s0.json @@ -0,0 +1,24 @@ +{ + "task": "csl", + "model": "gin", + "layers": 4, + "seed": 0, + "kind": null, + "n": 150, + "n_train": 100, + "n_test": 50, + "conv_round": 1, + "sec": 4.9, + "dev": "cuda", + "train_acc": 0.1, + "test_acc": 0.1, + "wl_ceiling_acc_converged": 0.1, + "wl_ceiling_acc_Ldepth": 0.1, + "test_bucket_counts": { + "H2": 50 + }, + "failure_bucket_counts": { + "H2": 45 + }, + "n_failures": 45 +} \ No newline at end of file diff --git a/runs/diag_sweep_20260616_074509.log b/runs/diag_sweep_20260616_074509.log new file mode 100644 index 0000000..c90d558 --- /dev/null +++ b/runs/diag_sweep_20260616_074509.log @@ -0,0 +1,20 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T07:45:09-05:00 +===== --task csl --model gin ===== +[csl/gin] train_acc=0.100 test_acc=0.100 | 1-WL ceiling(conv)=0.100 L-depth=0.100 | failures=45 -> {'H2': 45} + wrote /home/yurenh2/rrog/runs/diag_csl_gin_L4_s0.json +===== --task tri --model gin --kind er ===== +[tri/gin/er] train_mse=3.474 test_mse=4.077 | 1-WL oracle floor(H2)=0.000 | unseen=1.00 singleton=1.00 | learn_gap=4.077 var_y=13.583 + wrote /home/yurenh2/rrog/runs/diag_tri_er_gin_L4_s0.json +===== --task tri --model gin --kind regular ===== +[tri/gin/regular] train_mse=1.582 test_mse=1.486 | 1-WL oracle floor(H2)=1.483 | unseen=0.00 singleton=0.00 | learn_gap=0.002 var_y=1.482 + wrote /home/yurenh2/rrog/runs/diag_tri_regular_gin_L4_s0.json +===== --task csl --model gcn ===== +[csl/gcn] train_acc=0.100 test_acc=0.100 | 1-WL ceiling(conv)=0.100 L-depth=0.100 | failures=45 -> {'H2': 45} + wrote /home/yurenh2/rrog/runs/diag_csl_gcn_L4_s0.json +===== --task tri --model gcn --kind er ===== +[tri/gcn/er] train_mse=15.246 test_mse=13.652 | 1-WL oracle floor(H2)=0.000 | unseen=1.00 singleton=1.00 | learn_gap=13.652 var_y=13.583 + wrote /home/yurenh2/rrog/runs/diag_tri_er_gcn_L4_s0.json +===== --task tri --model gcn --kind regular ===== +[tri/gcn/regular] train_mse=1.582 test_mse=1.485 | 1-WL oracle floor(H2)=1.483 | unseen=0.00 singleton=0.00 | learn_gap=0.001 var_y=1.482 + wrote /home/yurenh2/rrog/runs/diag_tri_regular_gcn_L4_s0.json +done=2026-06-16T07:47:46-05:00 diff --git a/runs/diag_tri_er_gcn_L4_s0.json b/runs/diag_tri_er_gcn_L4_s0.json new file mode 100644 index 0000000..b7ff68e --- /dev/null +++ b/runs/diag_tri_er_gcn_L4_s0.json @@ -0,0 +1,22 @@ +{ + "task": "tri", + "model": "gcn", + "layers": 4, + "seed": 0, + "kind": "er", + "n": 800, + "n_train": 560, + "n_test": 240, + "conv_round": 7, + "sec": 23.9, + "dev": "cuda", + "train_mse": 15.2464, + "test_mse_gin": 13.652, + "mse_floor_oracle_H2": 0.0, + "mse_floor_converged_train": 13.6509, + "mse_floor_Ldepth_train": 13.6509, + "var_target_test": 13.5833, + "frac_test_unseen_color": 1.0, + "frac_test_singleton_color": 1.0, + "learn_gap_test": 13.652 +} \ No newline at end of file diff --git a/runs/diag_tri_er_gin_L4_s0.json b/runs/diag_tri_er_gin_L4_s0.json new file mode 100644 index 0000000..9c246bf --- /dev/null +++ b/runs/diag_tri_er_gin_L4_s0.json @@ -0,0 +1,22 @@ +{ + "task": "tri", + "model": "gin", + "layers": 4, + "seed": 0, + "kind": "er", + "n": 800, + "n_train": 560, + "n_test": 240, + "conv_round": 7, + "sec": 26.0, + "dev": "cuda", + "train_mse": 3.4742, + "test_mse_gin": 4.0773, + "mse_floor_oracle_H2": 0.0, + "mse_floor_converged_train": 13.6509, + "mse_floor_Ldepth_train": 13.6509, + "var_target_test": 13.5833, + "frac_test_unseen_color": 1.0, + "frac_test_singleton_color": 1.0, + "learn_gap_test": 4.0773 +} \ No newline at end of file diff --git a/runs/diag_tri_gin_L4_s0.json b/runs/diag_tri_gin_L4_s0.json new file mode 100644 index 0000000..432c669 --- /dev/null +++ b/runs/diag_tri_gin_L4_s0.json @@ -0,0 +1,20 @@ +{ + "task": "tri", + "model": "gin", + "layers": 4, + "seed": 0, + "n": 800, + "n_train": 560, + "n_test": 240, + "conv_round": 1, + "sec": 4.9, + "dev": "cuda", + "test_mse_gin": 13820393400.4686, + "mse_floor_oracle_H2": 1.4835, + "mse_floor_converged_train": 1.4854, + "mse_floor_Ldepth_train": 1.4854, + "var_target_test": 1.4816, + "frac_test_unseen_color": 0.0, + "frac_test_singleton_color": 0.0, + "learn_gap": 13820393398.9851 +} \ No newline at end of file diff --git a/runs/diag_tri_regular_gcn_L4_s0.json b/runs/diag_tri_regular_gcn_L4_s0.json new file mode 100644 index 0000000..e9c70f5 --- /dev/null +++ b/runs/diag_tri_regular_gcn_L4_s0.json @@ -0,0 +1,22 @@ +{ + "task": "tri", + "model": "gcn", + "layers": 4, + "seed": 0, + "kind": "regular", + "n": 800, + "n_train": 560, + "n_test": 240, + "conv_round": 1, + "sec": 24.2, + "dev": "cuda", + "train_mse": 1.5822, + "test_mse_gin": 1.4847, + "mse_floor_oracle_H2": 1.4835, + "mse_floor_converged_train": 1.4854, + "mse_floor_Ldepth_train": 1.4854, + "var_target_test": 1.4816, + "frac_test_unseen_color": 0.0, + "frac_test_singleton_color": 0.0, + "learn_gap_test": 0.0012 +} \ No newline at end of file diff --git a/runs/diag_tri_regular_gin_L4_s0.json b/runs/diag_tri_regular_gin_L4_s0.json new file mode 100644 index 0000000..b4c06d7 --- /dev/null +++ b/runs/diag_tri_regular_gin_L4_s0.json @@ -0,0 +1,22 @@ +{ + "task": "tri", + "model": "gin", + "layers": 4, + "seed": 0, + "kind": "regular", + "n": 800, + "n_train": 560, + "n_test": 240, + "conv_round": 1, + "sec": 25.1, + "dev": "cuda", + "train_mse": 1.5821, + "test_mse_gin": 1.4857, + "mse_floor_oracle_H2": 1.4835, + "mse_floor_converged_train": 1.4854, + "mse_floor_Ldepth_train": 1.4854, + "var_target_test": 1.4816, + "frac_test_unseen_color": 0.0, + "frac_test_singleton_color": 0.0, + "learn_gap_test": 0.0022 +} \ No newline at end of file diff --git a/runs/esan_sweep.log b/runs/esan_sweep.log new file mode 100644 index 0000000..ffcdb42 --- /dev/null +++ b/runs/esan_sweep.log @@ -0,0 +1,58 @@ +PNA done -> ESAN +ESAN start gpu=0 2026-06-17T04:49:09-05:00 +== esan s0 == +ep20 solve=0.053 +ep40 solve=0.313 +ep60 solve=0.367 +ep80 solve=0.270 +ep100 solve=0.467 +ep120 solve=0.487 +ep140 solve=0.473 +ep150 solve=0.497 +[esan/full] solve=0.497 LE AUROC=0.790 mean_lam=+0.084 passK=0.513 lamsel=0.513 (486s) + wrote esan_full_none_n50_k3_p0.2_T3_ns3_s0 +== esan s1 == +ep20 solve=0.063 +ep40 solve=0.260 +ep60 solve=0.290 +ep80 solve=0.310 +ep100 solve=0.340 +ep120 solve=0.417 +ep140 solve=0.483 +ep150 solve=0.457 +[esan/full] solve=0.483 LE AUROC=0.791 mean_lam=+0.109 passK=0.453 lamsel=0.453 (487s) + wrote esan_full_none_n50_k3_p0.2_T3_ns3_s1 +== esan s2 == +ep20 solve=0.063 +ep40 solve=0.317 +ep60 solve=0.327 +ep80 solve=0.543 +ep100 solve=0.650 +ep120 solve=0.713 +ep140 solve=0.663 +ep150 solve=0.687 +[esan/full] solve=0.713 LE AUROC=0.887 mean_lam=+0.025 passK=0.773 lamsel=0.773 (486s) + wrote esan_full_none_n50_k3_p0.2_T3_ns3_s2 +== esan s3 == +ep20 solve=0.063 +ep40 solve=0.233 +ep60 solve=0.397 +ep80 solve=0.373 +ep100 solve=0.487 +ep120 solve=0.463 +ep140 solve=0.537 +ep150 solve=0.563 +[esan/full] solve=0.563 LE AUROC=0.651 mean_lam=+0.150 passK=0.613 lamsel=0.613 (487s) + wrote esan_full_none_n50_k3_p0.2_T3_ns3_s3 +== esan s4 == +ep20 solve=0.020 +ep40 solve=0.343 +ep60 solve=0.407 +ep80 solve=0.537 +ep100 solve=0.670 +ep120 solve=0.667 +ep140 solve=0.670 +ep150 solve=0.650 +[esan/full] solve=0.670 LE AUROC=0.826 mean_lam=+0.049 passK=0.720 lamsel=0.720 (488s) + wrote esan_full_none_n50_k3_p0.2_T3_ns3_s4 +doneESAN=2026-06-17T05:30:33-05:00 diff --git a/runs/ff_sweep.log b/runs/ff_sweep.log new file mode 100644 index 0000000..a91967f --- /dev/null +++ b/runs/ff_sweep.log @@ -0,0 +1,20 @@ +FF start gpu=0 2026-06-17T09:36:53-05:00 +[ff/gcn/L4/s0] solve=0.007 +[ff/gcn/L4/s1] solve=0.007 +[ff/gcn/L4/s2] solve=0.007 +[ff/gcn/L8/s0] solve=0.017 +[ff/gcn/L8/s1] solve=0.013 +[ff/gcn/L8/s2] solve=0.020 +[ff/gcn/L16/s0] solve=0.000 +[ff/gcn/L16/s1] solve=0.000 +[ff/gcn/L16/s2] solve=0.000 +[ff/gat/L4/s0] solve=0.000 +[ff/gat/L4/s1] solve=0.003 +[ff/gat/L4/s2] solve=0.000 +[ff/gat/L8/s0] solve=0.000 +[ff/gat/L8/s1] solve=0.000 +[ff/gat/L8/s2] solve=0.000 +[ff/gat/L16/s0] solve=0.000 +[ff/gat/L16/s1] solve=0.000 +[ff/gat/L16/s2] solve=0.000 +doneFF=2026-06-17T11:34:28-05:00 diff --git a/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..79bb648 --- /dev/null +++ b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,12 @@ +{ + "grad_mode": "1step", + "pe": "none", + "seed": 0, + "n": 300, + "fail_rate": 0.8, + "auroc": 0.7704861111111111, + "sep": 0.17692238994714662, + "lam_solved": -0.2978147272290058, + "lam_unsolved": -0.12089233728185919, + "mean_lam": -0.15627681527128853 +} \ No newline at end of file diff --git a/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..1f789af --- /dev/null +++ b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,12 @@ +{ + "grad_mode": "1step", + "pe": "none", + "seed": 1, + "n": 300, + "fail_rate": 0.6666666666666666, + "auroc": 0.8459000000000001, + "sep": 0.29627635299530486, + "lam_solved": -0.27734302583486875, + "lam_unsolved": 0.018933327160436116, + "mean_lam": -0.07982545717133217 +} \ No newline at end of file diff --git a/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..ab7d7fb --- /dev/null +++ b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,12 @@ +{ + "grad_mode": "1step", + "pe": "none", + "seed": 2, + "n": 300, + "fail_rate": 0.6433333333333333, + "auroc": 0.8665439930269722, + "sep": 0.30687106563423694, + "lam_solved": -0.21527756840739037, + "lam_unsolved": 0.09159349722684659, + "mean_lam": -0.01785718284936458 +} \ No newline at end of file diff --git a/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..ecbf3c4 --- /dev/null +++ b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,12 @@ +{ + "grad_mode": "1step", + "pe": "none", + "seed": 3, + "n": 300, + "fail_rate": 0.6633333333333333, + "auroc": 0.7862580227872034, + "sep": 0.18177656397526462, + "lam_solved": -0.01236024695468813, + "lam_unsolved": 0.1694163170205765, + "mean_lam": 0.10821820714890407 +} \ No newline at end of file diff --git a/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..50cddc9 --- /dev/null +++ b/runs/le_color_1step_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,12 @@ +{ + "grad_mode": "1step", + "pe": "none", + "seed": 4, + "n": 300, + "fail_rate": 0.7633333333333333, + "auroc": 0.8352912233224676, + "sep": 0.2472765305163136, + "lam_solved": -0.299572467096354, + "lam_unsolved": -0.0522959365800404, + "mean_lam": -0.11081804880223461 +} \ No newline at end of file diff --git a/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..28e195f --- /dev/null +++ b/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 0, "auroc": 0.7627027990729185, "mean_lam": 0.07398854013587206} \ No newline at end of file diff --git a/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..1592377 --- /dev/null +++ b/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 1, "auroc": 0.7631720913504765, "mean_lam": 0.13374968373699594} \ No newline at end of file diff --git a/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..8824de9 --- /dev/null +++ b/runs/le_color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": 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\ No newline at end of file diff --git a/runs/le_color_full_rwse_n50_k3_p0.2_T3_ns3_s3.json b/runs/le_color_full_rwse_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..8011dc0 --- /dev/null +++ b/runs/le_color_full_rwse_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,12 @@ +{ + "grad_mode": "full", + "pe": "rwse", + "seed": 3, + "n": 300, + "fail_rate": 0.51, + "auroc": 0.8299319727891156, + "sep": 0.20560663420246325, + "lam_solved": -0.04382999812552701, + "lam_unsolved": 0.16177663607693624, + "mean_lam": 0.061029385317729244 +} \ No newline at end of file diff --git a/runs/le_color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json b/runs/le_color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..081bb6b --- /dev/null +++ b/runs/le_color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,12 @@ +{ + "grad_mode": "full", + "pe": "rwse", + "seed": 4, + "n": 300, + "fail_rate": 0.4533333333333333, + "auroc": 0.8797973457675753, + "sep": 0.2826686345638501, + "lam_solved": 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a/runs/le_color_gin_full_all_n50_k3_p0.2_T3_ns3_s0.json b/runs/le_color_gin_full_all_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..6ce761a --- /dev/null +++ b/runs/le_color_gin_full_all_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,14 @@ +{ + "conv": "gin", + "grad_mode": "full", + "pe": "all", + "contract": false, + "seed": 0, + "n": 300, + "fail_rate": 0.33, + "auroc": 0.875119352731293, + "sep": 0.39282084404068157, + "lam_solved": -0.3723896080101707, + "lam_unsolved": 0.02043123603051091, + "mean_lam": -0.24275872947674576 +} \ No newline at end of file diff --git a/runs/le_color_gin_full_all_n50_k3_p0.2_T3_ns3_s1.json b/runs/le_color_gin_full_all_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..c50870c --- /dev/null +++ b/runs/le_color_gin_full_all_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,14 @@ +{ + "conv": "gin", + "grad_mode": "full", + "pe": "all", + "contract": false, + "seed": 1, + "n": 300, + "fail_rate": 0.29333333333333333, + "auroc": 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newline at end of file diff --git a/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0.json b/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..27ce86b --- /dev/null +++ b/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,14 @@ +{ + "conv": "gin", + "grad_mode": "full", + "pe": "lappe", + "contract": false, + "seed": 0, + "n": 300, + "fail_rate": 0.61, + "auroc": 0.8431180234458923, + "sep": 0.23954686694875665, + "lam_solved": -0.24919056584773336, + "lam_unsolved": -0.009643698898976713, + "mean_lam": -0.10306697700899181 +} \ No newline at end of file diff --git a/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.json b/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..d96a7ab --- /dev/null +++ b/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,14 @@ +{ + "conv": "gin", + "grad_mode": "full", + "pe": "lappe", + "contract": false, + "seed": 1, + "n": 300, + 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index 0000000..05dfcaa --- /dev/null +++ b/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,14 @@ +{ + "conv": "gin", + "grad_mode": "full", + "pe": "lappe", + "contract": false, + "seed": 3, + "n": 300, + "fail_rate": 0.4766666666666667, + "auroc": 0.8708743485813549, + "sep": 0.2660060151580407, + "lam_solved": -0.3108652821187193, + "lam_unsolved": -0.04485926696067862, + "mean_lam": -0.1840690815600532 +} \ No newline at end of file diff --git a/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4.json b/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..50172fd --- /dev/null +++ b/runs/le_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,14 @@ +{ + "conv": "gin", + "grad_mode": "full", + "pe": "lappe", + "contract": false, + "seed": 4, + "n": 300, + "fail_rate": 0.6666666666666666, + "auroc": 0.7764, + "sep": 0.15627152857246984, + "lam_solved": -0.21964845005493164, + "lam_unsolved": -0.06337692148246181, + 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b/runs/le_color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..c8934a3 --- /dev/null +++ b/runs/le_color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,14 @@ +{ + "conv": "gps", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 3, + "n": 300, + "fail_rate": 0.056666666666666664, + "auroc": 0.8559551028892123, + "sep": 0.34088548051302103, + "lam_solved": -0.39706455164588167, + "lam_unsolved": -0.056179071132860636, + "mean_lam": -0.37774770775014377 +} \ No newline at end of file diff --git a/runs/le_color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/le_color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..69cb51c --- /dev/null +++ b/runs/le_color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,14 @@ +{ + "conv": "gps", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 4, + "n": 300, + "fail_rate": 0.06333333333333334, + "auroc": 0.9361303614909159, + "sep": 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a/runs/le_color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/le_color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..ef3a99b --- /dev/null +++ b/runs/le_color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,14 @@ +{ + "conv": "pna", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 3, + "n": 300, + "fail_rate": 0.056666666666666664, + "auroc": 0.7563916025774267, + "sep": 0.20069597616913837, + "lam_solved": -0.16172555582132558, + "lam_unsolved": 0.03897042034781278, + "mean_lam": -0.15035278383840775 +} \ No newline at end of file diff --git a/runs/le_color_pna_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/le_color_pna_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..2591a8c --- /dev/null +++ b/runs/le_color_pna_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,14 @@ +{ + "conv": "pna", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 4, + "n": 300, + "fail_rate": 0.07666666666666666, + 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b/runs/le_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,11 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 3, + "auroc": 0.7696551724137932, + "mean_lam": 0.013861869268444363, + "lam_solved": 0.011020388753700146, + "lam_unsolved": 0.0962648041960266 +} \ No newline at end of file diff --git a/runs/le_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/le_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..0d1f945 --- /dev/null +++ b/runs/le_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,11 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 4, + "auroc": 0.7280092592592593, + "mean_lam": -0.03937435364091975, + "lam_solved": -0.04227734012992759, + "lam_unsolved": 0.030297322095268295 +} \ No newline at end of file diff --git a/runs/le_color_rrog_gin_full_none_n12_k3_p0.2_T2_ns2_s7.json b/runs/le_color_rrog_gin_full_none_n12_k3_p0.2_T2_ns2_s7.json new file mode 100644 index 0000000..81715aa --- /dev/null +++ b/runs/le_color_rrog_gin_full_none_n12_k3_p0.2_T2_ns2_s7.json @@ -0,0 +1,15 @@ +{ + "conv": "gin", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 7, + "arch": "rrog_once_agg_node_compute", + "n": 300, + "fail_rate": 1.0, + "auroc": NaN, + "sep": NaN, + "lam_solved": null, + "lam_unsolved": -6.027523296422051e-07, + "mean_lam": -6.027523296422051e-07 +} \ No newline at end of file diff --git a/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..bd2e44f --- /dev/null +++ b/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,14 @@ +{ + "conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 0, + "n": 300, + "fail_rate": 0.27, + "auroc": 0.7929421049664581, + "sep": 0.18276381259910376, + "lam_solved": 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"conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 2, + "n": 300, + "fail_rate": 0.17, + "auroc": 0.8143948342389165, + "sep": 0.20737819121386966, + "lam_solved": -0.10523268078443035, + "lam_unsolved": 0.10214551042943931, + "mean_lam": -0.06997838827807248 +} \ No newline at end of file diff --git a/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..b8352fc --- /dev/null +++ b/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,14 @@ +{ + "conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 3, + "n": 300, + "fail_rate": 0.19666666666666666, + "auroc": 0.6804979253112032, + "sep": 0.11776359703690804, + "lam_solved": 0.002266006156251741, + "lam_unsolved": 0.12002960319315978, + "mean_lam": 0.025426180240176986 +} \ No newline at end of file diff --git a/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..6287958 --- /dev/null +++ b/runs/le_color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,14 @@ +{ + "conv": "sage", + "grad_mode": "full", + "pe": "none", + "contract": false, + "seed": 4, + "n": 300, + "fail_rate": 0.18333333333333332, + "auroc": 0.8282745825602968, + "sep": 0.1934978023844479, + "lam_solved": -0.011430386611423616, + "lam_unsolved": 0.18206741577302427, + "mean_lam": 0.024044210492391832 +} \ No newline at end of file diff --git a/runs/le_sweep.log b/runs/le_sweep.log new file mode 100644 index 0000000..a34180d --- /dev/null +++ b/runs/le_sweep.log @@ -0,0 +1,29 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T10:23:58-05:00 +ep20 val_mae=[0.316, 0.393] +ep40 val_mae=[0.357, 0.365] +ep60 val_mae=[0.165, 0.247] +ep80 val_mae=[0.171, 0.226] +ep100 val_mae=[0.415, 0.502] +ep120 val_mae=[0.183, 0.27] +ep140 val_mae=[0.149, 0.203] +ep160 val_mae=[0.172, 0.243] +ep180 val_mae=[0.171, 0.205] +ep200 val_mae=[0.176, 0.212] +[rec_full_sig0.0_K1_bestq_T3_ns3_s0] test_mae=[0.145, 0.198] oracle@K=[0.145, 0.198] @ep140 (209.3s) + wrote /home/yurenh2/rrog/runs/ckpt_rec_full_sig0.0_K1_bestq_T3_ns3_s0.pt +ep20 val_mae=[0.353, 0.393] +ep40 val_mae=[0.281, 0.337] +ep60 val_mae=[0.217, 0.308] +ep80 val_mae=[0.194, 0.285] +ep100 val_mae=[0.185, 0.313] +ep120 val_mae=[0.21, 0.373] +ep140 val_mae=[0.531, 0.684] +ep160 val_mae=[0.471, 0.599] +ep180 val_mae=[0.56, 0.6] +ep200 val_mae=[0.595, 0.645] +[rec_1step_sig0.0_K1_bestq_T3_ns3_s0] test_mae=[0.211, 0.293] oracle@K=[0.211, 0.293] @ep80 (168.0s) + wrote /home/yurenh2/rrog/runs/ckpt_rec_1step_sig0.0_K1_bestq_T3_ns3_s0.pt +===== LE diagnostic (lambda1: success vs failure) ===== +[full] n=300 fail_rate=0.15 | lambda1 SUCC mean -0.0402 std 0.1253 (n=256) | FAIL mean +0.0156 std 0.1058 (n=44) | sep(fail-succ)=+0.0558 | AUROC(fail|lambda1)=0.633 | mean_lambda1=-0.0320 +[1step] n=300 fail_rate=0.29 | lambda1 SUCC mean -0.2247 std 0.1226 (n=213) | FAIL mean -0.1706 std 0.1229 (n=87) | sep(fail-succ)=+0.0542 | AUROC(fail|lambda1)=0.630 | mean_lambda1=-0.2090 +done=2026-06-16T10:31:15-05:00 diff --git a/runs/ogb_hiv_remaining_gpu1.log b/runs/ogb_hiv_remaining_gpu1.log new file mode 100644 index 0000000..97ed9bb --- /dev/null +++ b/runs/ogb_hiv_remaining_gpu1.log @@ -0,0 +1,79 @@ ++ [[ hB != hxB ]] ++ XTRACE_STATE=-x ++ [[ hxB != hxB ]] ++ VERBOSE_STATE=+v ++ set +xv ++ unset XTRACE_STATE VERBOSE_STATE ++ set -euo pipefail ++ cd /home/yurenh2/rrog ++ export PYTHONPATH=/home/yurenh2/rrog: ++ PYTHONPATH=/home/yurenh2/rrog: ++ DEVICE=cuda:1 ++ EPOCHS=100 ++ SEED=0 ++ run_if_missing sgc fixed-rrog 3 3 ++ local view=sgc ++ local compute=fixed-rrog ++ local t=3 ++ local ns=3 ++ local out=runs/ogbg-molhiv_sgc_fixed-rrog_T3_ns3_h128_e100_s0.json ++ [[ -f runs/ogbg-molhiv_sgc_fixed-rrog_T3_ns3_h128_e100_s0.json ]] ++ echo '[run] view=sgc compute=fixed-rrog T=3 ns=3 device=cuda:1' +[run] view=sgc compute=fixed-rrog T=3 ns=3 device=cuda:1 ++ python3 -m rrog.cli run --task ogbg-molhiv --view sgc --compute fixed-rrog --epochs 100 --T 3 --n_sup 3 --seed 0 --device cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view sgc --compute fixed-rrog --T 3 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1 +ep10 val_rocauc=0.71985 halt=0.00 train_steps=3.00 +ep20 val_rocauc=0.72847 halt=0.00 train_steps=3.00 +ep30 val_rocauc=0.72656 halt=0.00 train_steps=3.00 +ep40 val_rocauc=0.72385 halt=0.00 train_steps=3.00 +ep50 val_rocauc=0.73415 halt=0.00 train_steps=3.00 +ep60 val_rocauc=0.74863 halt=0.00 train_steps=3.00 +ep70 val_rocauc=0.73652 halt=0.00 train_steps=3.00 +ep80 val_rocauc=0.74310 halt=0.00 train_steps=3.00 +ep90 val_rocauc=0.74841 halt=0.00 train_steps=3.00 +ep100 val_rocauc=0.73595 halt=0.00 train_steps=3.00 +[ogbg-molhiv_sgc_fixed-rrog_T3_ns3_h128_e100_s0] best_ep=60 val={'rocauc': 0.7486343817362336} test={'rocauc': 0.7382220591359432} adaptive=None steps=None + wrote /home/yurenh2/rrog/runs/ogbg-molhiv_sgc_fixed-rrog_T3_ns3_h128_e100_s0.json ++ run_if_missing cheb classic 0 1 ++ local view=cheb ++ local compute=classic ++ local t=0 ++ local ns=1 ++ local out=runs/ogbg-molhiv_cheb_classic_T0_ns1_h128_e100_s0.json ++ [[ -f runs/ogbg-molhiv_cheb_classic_T0_ns1_h128_e100_s0.json ]] ++ echo '[run] view=cheb compute=classic T=0 ns=1 device=cuda:1' +[run] view=cheb compute=classic T=0 ns=1 device=cuda:1 ++ python3 -m rrog.cli run --task ogbg-molhiv --view cheb --compute classic --epochs 100 --T 0 --n_sup 1 --seed 0 --device cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view cheb --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1 +ep10 val_rocauc=0.72594 halt=0.00 train_steps=1.00 +ep20 val_rocauc=0.78152 halt=0.00 train_steps=1.00 +ep30 val_rocauc=0.75664 halt=0.00 train_steps=1.00 +ep40 val_rocauc=0.74200 halt=0.00 train_steps=1.00 +ep50 val_rocauc=0.79068 halt=0.00 train_steps=1.00 +ep60 val_rocauc=0.79676 halt=0.00 train_steps=1.00 +ep70 val_rocauc=0.76138 halt=0.00 train_steps=1.00 +ep80 val_rocauc=0.77612 halt=0.00 train_steps=1.00 +ep90 val_rocauc=0.77074 halt=0.00 train_steps=1.00 +ep100 val_rocauc=0.77029 halt=0.00 train_steps=1.00 +[ogbg-molhiv_cheb_classic_T0_ns1_h128_e100_s0] best_ep=60 val={'rocauc': 0.796764770723104} test={'rocauc': 0.7451302651654147} adaptive=None steps=None + wrote /home/yurenh2/rrog/runs/ogbg-molhiv_cheb_classic_T0_ns1_h128_e100_s0.json ++ run_if_missing cheb fixed-rrog 3 3 ++ local view=cheb ++ local compute=fixed-rrog ++ local t=3 ++ local ns=3 ++ local out=runs/ogbg-molhiv_cheb_fixed-rrog_T3_ns3_h128_e100_s0.json ++ [[ -f runs/ogbg-molhiv_cheb_fixed-rrog_T3_ns3_h128_e100_s0.json ]] ++ echo '[run] view=cheb compute=fixed-rrog T=3 ns=3 device=cuda:1' +[run] view=cheb compute=fixed-rrog T=3 ns=3 device=cuda:1 ++ python3 -m rrog.cli run --task ogbg-molhiv --view cheb --compute fixed-rrog --epochs 100 --T 3 --n_sup 3 --seed 0 --device cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view cheb --compute fixed-rrog --T 3 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1 +ep10 val_rocauc=0.72235 halt=0.00 train_steps=3.00 +ep20 val_rocauc=0.76443 halt=0.00 train_steps=3.00 +ep30 val_rocauc=0.77549 halt=0.00 train_steps=3.00 +ep40 val_rocauc=0.73576 halt=0.00 train_steps=3.00 +ep50 val_rocauc=0.77500 halt=0.00 train_steps=3.00 +ep60 val_rocauc=0.77257 halt=0.00 train_steps=3.00 +ep70 val_rocauc=0.76067 halt=0.00 train_steps=3.00 +ep80 val_rocauc=0.76616 halt=0.00 train_steps=3.00 +ep90 val_rocauc=0.76171 halt=0.00 train_steps=3.00 diff --git a/runs/ogbg-molbace_appnp_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molbace_appnp_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..e30e682 --- /dev/null +++ b/runs/ogbg-molbace_appnp_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_appnp_classic_T0_ns1_h128_e100_s0", + "view": "appnp", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 17.3, + "dev": "cuda:1", + "ep": 10, + "val": { + "rocauc": 0.6564102564102564 + }, + "test": { + "rocauc": 0.7423056859676577 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbace_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molbace_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..c30d31f --- /dev/null +++ b/runs/ogbg-molbace_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_appnp_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "appnp", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 20.1, + "dev": "cuda:1", + "ep": 30, + "val": { + "rocauc": 0.7168498168498169 + }, + "test": { + "rocauc": 0.7209181011997913 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..d061742 --- /dev/null +++ b/runs/ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "appnp", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:3", + "metric": "rocauc", + "sec": 34.5, + "dev": "cuda:3", + "ep": 10, + "val": { + "rocauc": 0.6802197802197802 + }, + "val_adaptive": { + "rocauc": 0.6714285714285715 + }, + "test": { + "rocauc": 0.6833594157537818 + }, + "test_adaptive": { + "rocauc": 0.7826464962615197 + }, + "fixed_val_steps": 8.0, + "adaptive_val_steps": 2.1059602649006623, + "fixed_steps": 8.0, + "adaptive_steps": 2.0921052631578947 +} \ No newline at end of file diff --git a/runs/ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..5dbddc8 --- /dev/null +++ b/runs/ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "appnp", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 38.3, + "dev": "cuda:0", + "ep": 20, + "val": { + "rocauc": 0.6835164835164835 + }, + "val_adaptive": { + "rocauc": 0.6549450549450551 + }, + "test": { + "rocauc": 0.7118761954442705 + }, + "test_adaptive": { + "rocauc": 0.7328290732046601 + }, + "fixed_val_steps": 8.0, + "adaptive_val_steps": 2.357615894039735, + "fixed_steps": 8.0, + "adaptive_steps": 2.1315789473684212 +} \ No newline at end of file diff --git a/runs/ogbg-molbace_arma_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molbace_arma_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..4d18ef2 --- /dev/null +++ b/runs/ogbg-molbace_arma_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_arma_classic_T0_ns1_h128_e100_s0", + "view": "arma", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 30.6, + "dev": "cuda:1", + "ep": 50, + "val": { + "rocauc": 0.6923076923076924 + }, + "test": { + "rocauc": 0.7838636758824552 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbace_arma_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molbace_arma_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..8090a35 --- /dev/null +++ b/runs/ogbg-molbace_arma_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_arma_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "arma", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 38.9, + "dev": "cuda:1", + "ep": 50, + "val": { + "rocauc": 0.717948717948718 + }, + "test": { + "rocauc": 0.7671709267953399 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbace_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molbace_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..ae5bc4f --- /dev/null +++ b/runs/ogbg-molbace_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "arma", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 36.3, + "dev": "cuda:0", + "ep": 50, + "val": { + "rocauc": 0.7355311355311356 + }, + "val_adaptive": { + "rocauc": 0.7347985347985347 + }, + "test": { + "rocauc": 0.7450878108155102 + }, + "test_adaptive": { + "rocauc": 0.7645626847504782 + }, + "fixed_val_steps": 8.0, + "adaptive_val_steps": 4.71523178807947, + "fixed_steps": 8.0, + "adaptive_steps": 4.375 +} \ No newline at end of file diff --git a/runs/ogbg-molbace_cheb_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molbace_cheb_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..ffd0717 --- /dev/null +++ b/runs/ogbg-molbace_cheb_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_cheb_classic_T0_ns1_h128_e100_s0", + "view": "cheb", + "compute": "classic", + "T": 0, 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b/runs/ogbg-molbace_gatv2_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_gatv2_classic_T0_ns1_h128_e100_s0", + "view": "gatv2", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 29.9, + "dev": "cuda:1", + "ep": 70, + "val": { + "rocauc": 0.702930402930403 + }, + "test": { + "rocauc": 0.7400452095287776 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbace_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molbace_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..4ed6321 --- /dev/null +++ b/runs/ogbg-molbace_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_gatv2_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gatv2", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 34.7, + "dev": "cuda:1", + "ep": 30, + "val": { + "rocauc": 0.7025641025641026 + }, + "test": { + "rocauc": 0.751869240132151 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbace_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molbace_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..9f3dced --- /dev/null +++ b/runs/ogbg-molbace_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "gatv2", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + 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100644 index 0000000..fbd4ded --- /dev/null +++ b/runs/ogbg-molbace_graphsage_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_graphsage_classic_T0_ns1_h128_e100_s0", + "view": "graphsage", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 11.0, + "dev": "cuda:1", + "ep": 50, + "val": { + "rocauc": 0.6758241758241759 + }, + "test": { + "rocauc": 0.7758650669448792 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbace_graphsage_fixed-rrog_T1_ns3_h128_e100_s0.json 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--git a/runs/ogbg-molbace_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molbace_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..b99cda3 --- /dev/null +++ b/runs/ogbg-molbace_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "graphsage", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + 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/dev/null +++ b/runs/ogbg-molbace_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbace", + "tag": "ogbg-molbace_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "sgc", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 33.9, + "dev": "cuda:0", + "ep": 60, + "val": { + "rocauc": 0.6615384615384615 + }, + "val_adaptive": { + "rocauc": 0.6641025641025642 + }, + "test": { + "rocauc": 0.7970787689097547 + }, + 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a/runs/ogbg-molbbbp_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molbbbp_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..03928c0 --- /dev/null +++ b/runs/ogbg-molbbbp_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbbbp", + "tag": "ogbg-molbbbp_appnp_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "appnp", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 26.7, + "dev": "cuda:1", + "ep": 10, + "val": { + "rocauc": 0.9359753061834113 + }, + "test": { + "rocauc": 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+} \ No newline at end of file diff --git a/runs/ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json b/runs/ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json new file mode 100644 index 0000000..9ae24fc --- /dev/null +++ b/runs/ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbbbp", + "tag": "ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0", + "view": "appnp", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 30, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + 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100644 index 0000000..f3e24ce --- /dev/null +++ b/runs/ogbg-molbbbp_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbbbp", + "tag": "ogbg-molbbbp_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "film", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 46.4, + "dev": "cuda:0", + "ep": 50, + "val": { + "rocauc": 0.9392611769391616 + }, + "val_adaptive": { + "rocauc": 0.9483222144777457 + }, + "test": { + 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/dev/null +++ b/runs/ogbg-molbbbp_gcn_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbbbp", + "tag": "ogbg-molbbbp_gcn_classic_T0_ns1_h128_e100_s0", + "view": "gcn", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 13.4, + "dev": "cuda:1", + "ep": 40, + "val": { + "rocauc": 0.9385641740515782 + }, + "test": { + "rocauc": 0.667920524691358 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbbbp_gcn_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molbbbp_gcn_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..ba2c88e --- /dev/null +++ b/runs/ogbg-molbbbp_gcn_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molbbbp", + "tag": "ogbg-molbbbp_gcn_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gcn", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 19.8, + "dev": "cuda:1", + "ep": 10, + "val": { + "rocauc": 0.9416509011251619 + }, + "test": { + "rocauc": 0.601658950617284 + } +} \ No newline at end of file diff --git a/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..9c600a3 --- /dev/null +++ b/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbbbp", + "tag": "ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "gcn", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + 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a/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json b/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json new file mode 100644 index 0000000..7070fb1 --- /dev/null +++ b/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbbbp", + "tag": "ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0", + "view": "gcn", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 30, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + 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a/runs/ogbg-molbbbp_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molbbbp_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..a0534f9 --- /dev/null +++ b/runs/ogbg-molbbbp_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molbbbp", + "tag": "ogbg-molbbbp_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "graphsage", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + 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b/runs/ogbg-molclintox_appnp_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..fa5411b --- /dev/null +++ b/runs/ogbg-molclintox_appnp_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molclintox", + "tag": "ogbg-molclintox_appnp_classic_T0_ns1_h128_e100_s0", + "view": "appnp", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 16.0, + "dev": "cuda:1", + "ep": 60, + "val": { + "rocauc": 0.8515931251846744 + }, + "test": { + "rocauc": 0.9184287352726515 + } +} \ No newline at end of file diff --git a/runs/ogbg-molclintox_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molclintox_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..e276b4d --- /dev/null +++ b/runs/ogbg-molclintox_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molclintox", + "tag": "ogbg-molclintox_appnp_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "appnp", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 30.3, + "dev": "cuda:1", + "ep": 40, + "val": { + "rocauc": 0.9029408385042188 + }, + "test": { + "rocauc": 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b/runs/ogbg-molclintox_gen_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molclintox", + "tag": "ogbg-molclintox_gen_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gen", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 31.7, + "dev": "cuda:1", + "ep": 30, + "val": { + "rocauc": 0.9398880462260745 + }, + "test": { + "rocauc": 0.8194027386786223 + } +} \ No newline at end of file diff --git a/runs/ogbg-molclintox_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json 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a/runs/ogbg-molclintox_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molclintox_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..f19044a --- /dev/null +++ b/runs/ogbg-molclintox_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molclintox", + "tag": "ogbg-molclintox_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "graphconv", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + 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b/runs/ogbg-molclintox_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..360e0bc --- /dev/null +++ b/runs/ogbg-molclintox_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molclintox", + "tag": "ogbg-molclintox_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "sgc", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 32.9, + "dev": "cuda:1", + "ep": 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a/runs/ogbg-molclintox_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molclintox_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..b488b39 --- /dev/null +++ b/runs/ogbg-molclintox_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molclintox", + "tag": "ogbg-molclintox_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "tag", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + 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b/runs/ogbg-molclintox_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molclintox", + "tag": "ogbg-molclintox_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "transformer", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 41.0, + "dev": "cuda:1", + "ep": 30, + "val": { + "rocauc": 0.8521414031977412 + }, + "val_adaptive": { + "rocauc": 0.8862561147772415 + }, + "test": { + "rocauc": 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b/runs/ogbg-molesol_arma_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_arma_classic_T0_ns1_h128_e100_s0", + "view": "arma", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 11.5, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 1.0194642543792725 + }, + "test": { + "rmse": 1.0665998458862305 + } +} \ No newline at end of file diff --git a/runs/ogbg-molesol_arma_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molesol_arma_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..5beccfd --- /dev/null +++ b/runs/ogbg-molesol_arma_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_arma_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "arma", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 17.6, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 1.003442406654358 + }, + "test": { + "rmse": 1.1272348165512085 + } +} \ No newline at end of file diff --git a/runs/ogbg-molesol_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json 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b/runs/ogbg-molesol_film_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..db08bfe --- /dev/null +++ b/runs/ogbg-molesol_film_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_film_classic_T0_ns1_h128_e100_s0", + "view": "film", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 9.3, + "dev": "cuda:1", + "ep": 90, + "val": { + "rmse": 1.0717737674713135 + }, + "test": { + "rmse": 1.2896088361740112 + } +} \ No newline at end of file diff --git a/runs/ogbg-molesol_film_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molesol_film_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..f4729c2 --- /dev/null +++ b/runs/ogbg-molesol_film_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_film_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "film", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 14.6, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 1.0196408033370972 + }, + "test": { + "rmse": 1.084921956062317 + } +} \ No newline at end of file diff --git a/runs/ogbg-molesol_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molesol_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..5af1876 --- /dev/null +++ b/runs/ogbg-molesol_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "film", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + 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b/runs/ogbg-molesol_gine_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_gine_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gine", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 13.6, + "dev": "cuda:1", + "ep": 100, + "val": { + "rmse": 1.0580767393112183 + }, + "test": { + "rmse": 1.0950747728347778 + } +} \ No newline at end of file diff --git a/runs/ogbg-molesol_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molesol_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..6ea7888 --- /dev/null +++ b/runs/ogbg-molesol_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "gine", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 23.3, + "dev": "cuda:1", + "ep": 90, + 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--- /dev/null +++ b/runs/ogbg-molesol_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "mf", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 39.1, + "dev": "cuda:1", + "ep": 60, + "val": { + "rmse": 1.0765037536621094 + }, + "val_adaptive": { + "rmse": 1.0629757642745972 + }, + "test": { + "rmse": 1.0843762159347534 + }, + 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b/runs/ogbg-molesol_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_resgated_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "resgated", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 24.6, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 0.9873355627059937 + }, + "test": { + "rmse": 0.8825017213821411 + } +} \ No newline at end of file diff --git a/runs/ogbg-molesol_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json 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b/runs/ogbg-molesol_tag_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..bdab4c4 --- /dev/null +++ b/runs/ogbg-molesol_tag_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_tag_classic_T0_ns1_h128_e100_s0", + "view": "tag", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 10.5, + "dev": "cuda:1", + "ep": 30, + "val": { + "rmse": 0.9323490858078003 + }, + "test": { + "rmse": 0.9677547216415405 + } +} \ No newline at end of file diff --git a/runs/ogbg-molesol_tag_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molesol_tag_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..317fb16 --- /dev/null +++ b/runs/ogbg-molesol_tag_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_tag_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "tag", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 16.3, + "dev": "cuda:1", + "ep": 50, + "val": { + "rmse": 0.9035957455635071 + }, + "test": { + "rmse": 0.9462130665779114 + } +} \ No newline at end of file diff --git a/runs/ogbg-molesol_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molesol_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..0e155a1 --- /dev/null +++ b/runs/ogbg-molesol_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "tag", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + 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b/runs/ogbg-molesol_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molesol", + "tag": "ogbg-molesol_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "transformer", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 28.3, + "dev": "cuda:1", + "ep": 40, + "val": { + "rmse": 1.066428780555725 + }, + "val_adaptive": { + "rmse": 1.0112154483795166 + }, + "test": { + "rmse": 0.9533939361572266 + }, + 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-0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_gatv2_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gatv2", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 13.0, + "dev": "cuda:1", + "ep": 100, + "val": { + "rmse": 3.9983770847320557 + }, + "test": { + "rmse": 2.5965566635131836 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_gcn_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molfreesolv_gcn_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..8553aee --- /dev/null +++ b/runs/ogbg-molfreesolv_gcn_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_gcn_classic_T0_ns1_h128_e100_s0", + "view": "gcn", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 4.7, + "dev": "cuda:1", + "ep": 90, + "val": { + "rmse": 3.7172489166259766 + }, + "test": { + "rmse": 2.4850735664367676 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_gcn_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molfreesolv_gcn_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..06a4ed7 --- /dev/null +++ b/runs/ogbg-molfreesolv_gcn_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_gcn_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gcn", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 7.1, + "dev": "cuda:1", + "ep": 70, + "val": { + "rmse": 3.5887632369995117 + }, + "test": { + "rmse": 2.4443516731262207 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_gen_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molfreesolv_gen_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..a0ef0ee --- /dev/null +++ b/runs/ogbg-molfreesolv_gen_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_gen_classic_T0_ns1_h128_e100_s0", + "view": "gen", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 5.8, + "dev": "cuda:1", + "ep": 40, + "val": { + "rmse": 3.9998085498809814 + }, + "test": { + "rmse": 2.558762788772583 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_gen_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molfreesolv_gen_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..9c5f0a0 --- /dev/null +++ b/runs/ogbg-molfreesolv_gen_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_gen_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gen", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 11.4, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 4.300873279571533 + }, + "test": { + "rmse": 2.9063339233398438 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_gin_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molfreesolv_gin_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..e1db15f --- /dev/null +++ b/runs/ogbg-molfreesolv_gin_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_gin_classic_T0_ns1_h128_e100_s0", + "view": "gin", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 4.9, + "dev": "cuda:1", + "ep": 40, + "val": { + "rmse": 4.018989086151123 + }, + "test": { + "rmse": 3.4898324012756348 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_gin_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molfreesolv_gin_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..1f527f0 --- /dev/null +++ b/runs/ogbg-molfreesolv_gin_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_gin_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gin", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 12.1, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 3.9742789268493652 + }, + "test": { + "rmse": 3.4291605949401855 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_gine_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molfreesolv_gine_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..21a7f6a --- /dev/null +++ b/runs/ogbg-molfreesolv_gine_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_gine_classic_T0_ns1_h128_e100_s0", + "view": "gine", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": 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"compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 24.8, + "dev": "cuda:1", + "ep": 40, + "val": { + "rmse": 2.5060386657714844 + }, + "test": { + "rmse": 3.1891541481018066 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_pna_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molfreesolv_pna_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..81ea6ec --- /dev/null +++ b/runs/ogbg-molfreesolv_pna_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_pna_classic_T0_ns1_h128_e100_s0", + "view": "pna", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 13.6, + "dev": "cuda:1", + "ep": 40, + "val": { + "rmse": 2.3625338077545166 + }, + "test": { + "rmse": 2.2610387802124023 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_pna_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molfreesolv_pna_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..de0fee4 --- /dev/null +++ b/runs/ogbg-molfreesolv_pna_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_pna_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "pna", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 16.4, + "dev": "cuda:1", + "ep": 40, + "val": { + "rmse": 3.3333704471588135 + }, + "test": { + "rmse": 2.4279491901397705 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_resgated_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molfreesolv_resgated_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..9187a7a --- /dev/null +++ b/runs/ogbg-molfreesolv_resgated_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_resgated_classic_T0_ns1_h128_e100_s0", + "view": "resgated", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 8.1, + "dev": "cuda:1", + "ep": 50, + "val": { + "rmse": 2.4772303104400635 + }, + "test": { + "rmse": 2.0041325092315674 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molfreesolv_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..7efe491 --- /dev/null +++ b/runs/ogbg-molfreesolv_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_resgated_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "resgated", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 14.0, + "dev": "cuda:1", + "ep": 70, + "val": { + "rmse": 3.0919928550720215 + }, + "test": { + "rmse": 2.0244016647338867 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_sgc_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molfreesolv_sgc_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..08ba938 --- /dev/null +++ b/runs/ogbg-molfreesolv_sgc_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_sgc_classic_T0_ns1_h128_e100_s0", + "view": "sgc", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 5.0, + "dev": "cuda:1", + "ep": 50, + "val": { + "rmse": 3.9146761894226074 + }, + "test": { + "rmse": 2.4146173000335693 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molfreesolv_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..d6ec5dc --- /dev/null +++ b/runs/ogbg-molfreesolv_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_sgc_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "sgc", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 7.4, + "dev": "cuda:1", + "ep": 50, + "val": { + "rmse": 3.9261200428009033 + }, + "test": { + "rmse": 2.4886999130249023 + } +} \ No newline at end of file diff --git a/runs/ogbg-molfreesolv_tag_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molfreesolv_tag_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..1d73b02 --- /dev/null +++ b/runs/ogbg-molfreesolv_tag_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molfreesolv", + "tag": "ogbg-molfreesolv_tag_classic_T0_ns1_h128_e100_s0", + "view": "tag", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 6.7, + 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+++ b/runs/ogbg-molhiv_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "appnp", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:3", + "metric": "rocauc", + "sec": 1000.9, + "dev": "cuda:3", + "ep": 50, + "val": { + "rocauc": 0.7323571918479326 + }, + "val_adaptive": { + "rocauc": 0.7404314863805603 + }, + "test": { + "rocauc": 0.7487070047702736 + }, + 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b/runs/ogbg-molhiv_film_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_film_classic_T0_ns1_h128_e100_s0", + "view": "film", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 684.6, + "dev": "cuda:1", + "ep": 20, + "val": { + "rocauc": 0.7921535126396236 + }, + "test": { + "rocauc": 0.7842136773595473 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_film_classic_T0_ns1_h128_e100_s1.json b/runs/ogbg-molhiv_film_classic_T0_ns1_h128_e100_s1.json new file mode 100644 index 0000000..8e0aa76 --- /dev/null +++ b/runs/ogbg-molhiv_film_classic_T0_ns1_h128_e100_s1.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_film_classic_T0_ns1_h128_e100_s1", + "view": "film", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 1, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 738.2, + "dev": "cuda:0", + "ep": 40, + "val": { + "rocauc": 0.7384259259259259 + }, + "test": { + "rocauc": 0.7277853956237085 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_film_classic_T0_ns1_h128_e100_s2.json b/runs/ogbg-molhiv_film_classic_T0_ns1_h128_e100_s2.json 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a/runs/ogbg-molhiv_film_fixed-rrog_T1_ns3_h128_e100_s1.json b/runs/ogbg-molhiv_film_fixed-rrog_T1_ns3_h128_e100_s1.json new file mode 100644 index 0000000..95b90c4 --- /dev/null +++ b/runs/ogbg-molhiv_film_fixed-rrog_T1_ns3_h128_e100_s1.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_film_fixed-rrog_T1_ns3_h128_e100_s1", + "view": "film", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 1, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 978.0, + "dev": "cuda:0", + "ep": 80, + "val": { + "rocauc": 0.7767214138741916 + }, + "test": { + "rocauc": 0.721711504664053 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_film_fixed-rrog_T1_ns3_h128_e100_s2.json b/runs/ogbg-molhiv_film_fixed-rrog_T1_ns3_h128_e100_s2.json new file mode 100644 index 0000000..2af945e --- /dev/null +++ b/runs/ogbg-molhiv_film_fixed-rrog_T1_ns3_h128_e100_s2.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_film_fixed-rrog_T1_ns3_h128_e100_s2", + "view": "film", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 2, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 990.1, + "dev": "cuda:0", + "ep": 60, + "val": { + "rocauc": 0.8191688712522045 + }, + "test": { + "rocauc": 0.7626895073292261 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_film_fixed-rrog_T3_ns3_h128_e100_s0.json b/runs/ogbg-molhiv_film_fixed-rrog_T3_ns3_h128_e100_s0.json new file mode 100644 index 0000000..be80ab8 --- /dev/null +++ b/runs/ogbg-molhiv_film_fixed-rrog_T3_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_film_fixed-rrog_T3_ns3_h128_e100_s0", + "view": "film", + "compute": "fixed-rrog", + "T": 3, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 1072.1, + "dev": "cuda:1", + "ep": 30, + "val": { + 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a/runs/ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..12d5541 --- /dev/null +++ b/runs/ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "gcn", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + 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end of file diff --git a/runs/ogbg-molhiv_gen_classic_T0_ns1_h128_e100_s2.json b/runs/ogbg-molhiv_gen_classic_T0_ns1_h128_e100_s2.json new file mode 100644 index 0000000..7b0261b --- /dev/null +++ b/runs/ogbg-molhiv_gen_classic_T0_ns1_h128_e100_s2.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_gen_classic_T0_ns1_h128_e100_s2", + "view": "gen", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 2, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 693.8, + "dev": "cuda:0", + "ep": 50, + "val": { + "rocauc": 0.7559125759357241 + }, + "test": { + "rocauc": 0.7565596091079395 + 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a/runs/ogbg-molhiv_gine_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molhiv_gine_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..1d75215 --- /dev/null +++ b/runs/ogbg-molhiv_gine_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_gine_classic_T0_ns1_h128_e100_s0", + "view": "gine", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 453.6, + "dev": "cuda:1", + "ep": 70, + "val": { + "rocauc": 0.7942448069762884 + }, + "test": { + "rocauc": 0.7445141852874717 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_gine_classic_T0_ns1_h128_e100_s1.json b/runs/ogbg-molhiv_gine_classic_T0_ns1_h128_e100_s1.json new file mode 100644 index 0000000..d88283d --- /dev/null +++ b/runs/ogbg-molhiv_gine_classic_T0_ns1_h128_e100_s1.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_gine_classic_T0_ns1_h128_e100_s1", + "view": "gine", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 1, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 658.5, + "dev": "cuda:0", + "ep": 40, + "val": { + "rocauc": 0.763098912404468 + }, + "test": { + "rocauc": 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a/runs/ogbg-molhiv_graphconv_fixed-rrog_T1_ns3_h128_e100_s1.json b/runs/ogbg-molhiv_graphconv_fixed-rrog_T1_ns3_h128_e100_s1.json new file mode 100644 index 0000000..ae03725 --- /dev/null +++ b/runs/ogbg-molhiv_graphconv_fixed-rrog_T1_ns3_h128_e100_s1.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_graphconv_fixed-rrog_T1_ns3_h128_e100_s1", + "view": "graphconv", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 1, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 813.7, + "dev": "cuda:0", + "ep": 80, + "val": { + "rocauc": 0.7784422153635117 + }, + "test": { + "rocauc": 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b/runs/ogbg-molhiv_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "graphconv", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 896.5, + "dev": "cuda:0", + "ep": 80, + "val": { + "rocauc": 0.7790944052518126 + }, + "val_adaptive": { + "rocauc": 0.7738033999608073 + }, + "test": { + "rocauc": 0.7510651036134339 + }, + 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b/runs/ogbg-molhiv_mf_fixed-rrog_T1_ns3_h128_e100_s2.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_mf_fixed-rrog_T1_ns3_h128_e100_s2", + "view": "mf", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 2, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 1742.8, + "dev": "cuda:0", + "ep": 20, + "val": { + "rocauc": 0.7763417352537723 + }, + "test": { + "rocauc": 0.7111811738349525 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_mf_fixed-rrog_T3_ns3_h128_e100_s0.json b/runs/ogbg-molhiv_mf_fixed-rrog_T3_ns3_h128_e100_s0.json new file mode 100644 index 0000000..6a5fba2 --- /dev/null +++ b/runs/ogbg-molhiv_mf_fixed-rrog_T3_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_mf_fixed-rrog_T3_ns3_h128_e100_s0", + "view": "mf", + "compute": "fixed-rrog", + "T": 3, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 1787.2, + "dev": "cuda:1", + "ep": 50, + "val": { + "rocauc": 0.7930782137958065 + }, + "test": { + "rocauc": 0.7216728789663763 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json 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a/runs/ogbg-molhiv_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molhiv_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..ef45220 --- /dev/null +++ b/runs/ogbg-molhiv_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "resgated", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + 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a/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..53f4e1d --- /dev/null +++ b/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s0", + "view": "sgc", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 349.7, + "dev": "cuda:1", + "ep": 80, + "val": { + "rocauc": 0.7478597148736037 + }, + "test": { + "rocauc": 0.7019100407501111 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s1.json b/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s1.json new file mode 100644 index 0000000..0375109 --- /dev/null +++ b/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s1.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s1", + "view": "sgc", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 1, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 367.1, + "dev": "cuda:0", + "ep": 30, + "val": { + "rocauc": 0.7691676464824613 + }, + "test": { + "rocauc": 0.7100407501110487 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s2.json b/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s2.json new file mode 100644 index 0000000..c8af7ef --- /dev/null +++ b/runs/ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s2.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_sgc_classic_T0_ns1_h128_e100_s2", + "view": "sgc", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 2, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 366.8, + "dev": "cuda:0", + "ep": 80, + "val": { + "rocauc": 0.7927750832843425 + }, + "test": { + "rocauc": 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b/runs/ogbg-molhiv_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "sgc", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 1011.3, + "dev": "cuda:0", + "ep": 50, + "val": { + "rocauc": 0.7352782676856752 + }, + "val_adaptive": { + "rocauc": 0.7147756221830296 + }, + "test": { + "rocauc": 0.6961702620753587 + }, + "test_adaptive": { 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b/runs/ogbg-molhiv_tag_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_tag_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "tag", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 646.4, + "dev": "cuda:0", + "ep": 90, + "val": { + "rocauc": 0.7717029198510681 + }, + "test": { + "rocauc": 0.7181154522103554 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_tag_fixed-rrog_T1_ns3_h128_e100_s1.json b/runs/ogbg-molhiv_tag_fixed-rrog_T1_ns3_h128_e100_s1.json new file mode 100644 index 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a/runs/ogbg-molhiv_tag_fixed-rrog_T3_ns3_h128_e100_s0.json b/runs/ogbg-molhiv_tag_fixed-rrog_T3_ns3_h128_e100_s0.json new file mode 100644 index 0000000..547c08d --- /dev/null +++ b/runs/ogbg-molhiv_tag_fixed-rrog_T3_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_tag_fixed-rrog_T3_ns3_h128_e100_s0", + "view": "tag", + "compute": "fixed-rrog", + "T": 3, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 1148.5, + "dev": "cuda:1", + "ep": 70, + "val": { + "rocauc": 0.7803834754066236 + }, + "test": { + "rocauc": 0.7351764228741382 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..15e4e59 --- /dev/null +++ b/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "tag", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 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a/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json b/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json new file mode 100644 index 0000000..7496c27 --- /dev/null +++ b/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0", + "view": "tag", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 30, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 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+{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "transformer", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 883.0, + "dev": "cuda:0", + "ep": 30, + "val": { + "rocauc": 0.7838158926121889 + }, + "test": { + "rocauc": 0.7647501883002762 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s1.json b/runs/ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s1.json new file mode 100644 index 0000000..4961b21 --- /dev/null +++ b/runs/ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s1.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s1", + "view": "transformer", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 1, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 1165.4, + "dev": "cuda:0", + "ep": 70, + "val": { + "rocauc": 0.7651320301783265 + }, + "test": { + "rocauc": 0.749757623747079 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s2.json b/runs/ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s2.json new file mode 100644 index 0000000..1bb42aa --- /dev/null +++ b/runs/ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s2.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_transformer_fixed-rrog_T1_ns3_h128_e100_s2", + "view": "transformer", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 2, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 1182.1, + "dev": "cuda:0", + "ep": 40, + "val": { + "rocauc": 0.8043399715853421 + }, + "test": { + "rocauc": 0.7765908959230575 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_transformer_fixed-rrog_T3_ns3_h128_e100_s0.json b/runs/ogbg-molhiv_transformer_fixed-rrog_T3_ns3_h128_e100_s0.json new file mode 100644 index 0000000..bf85cdc --- /dev/null +++ b/runs/ogbg-molhiv_transformer_fixed-rrog_T3_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_transformer_fixed-rrog_T3_ns3_h128_e100_s0", + "view": "transformer", + "compute": "fixed-rrog", + "T": 3, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 1246.4, + "dev": "cuda:1", + "ep": 40, + "val": { + "rocauc": 0.8088103811483441 + }, + "test": { + "rocauc": 0.7413024585256572 + } +} \ No newline at end of file diff --git a/runs/ogbg-molhiv_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molhiv_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..a054aac --- /dev/null +++ b/runs/ogbg-molhiv_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molhiv", + "tag": "ogbg-molhiv_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "transformer", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + 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b/runs/ogbg-mollipo_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "appnp", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 102.5, + "dev": "cuda:1", + "ep": 70, + "val": { + "rmse": 1.1389226913452148 + }, + "val_adaptive": { + "rmse": 0.8501057624816895 + }, + "test": { + "rmse": 1.0732718706130981 + }, + "test_adaptive": { 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-0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_cheb_classic_T0_ns1_h128_e100_s0", + "view": "cheb", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 41.9, + "dev": "cuda:1", + "ep": 90, + "val": { + "rmse": 0.7188113927841187 + }, + "test": { + "rmse": 0.7179734706878662 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_cheb_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-mollipo_cheb_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..5eba1b4 --- /dev/null +++ b/runs/ogbg-mollipo_cheb_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_cheb_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "cheb", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 66.9, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 0.6990480422973633 + }, + "test": { + "rmse": 0.7132058143615723 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-mollipo_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..45d681b --- /dev/null +++ b/runs/ogbg-mollipo_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "cheb", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 101.8, + "dev": "cuda:1", + "ep": 90, + 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b/runs/ogbg-mollipo_gatv2_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..a1373e9 --- /dev/null +++ b/runs/ogbg-mollipo_gatv2_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_gatv2_classic_T0_ns1_h128_e100_s0", + "view": "gatv2", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 70.6, + "dev": "cuda:1", + "ep": 40, + "val": { + "rmse": 0.6864758729934692 + }, + "test": { + "rmse": 0.7307590842247009 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-mollipo_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..14353de --- /dev/null +++ b/runs/ogbg-mollipo_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_gatv2_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gatv2", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 115.7, + "dev": "cuda:1", + "ep": 90, + "val": { + "rmse": 0.7079874277114868 + }, + "test": { + "rmse": 0.733400285243988 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-mollipo_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..a77b001 --- /dev/null +++ b/runs/ogbg-mollipo_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "gatv2", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + 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+} \ No newline at end of file diff --git a/runs/ogbg-mollipo_gen_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-mollipo_gen_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..8f45cbc --- /dev/null +++ b/runs/ogbg-mollipo_gen_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_gen_classic_T0_ns1_h128_e100_s0", + "view": "gen", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 60.8, + "dev": "cuda:1", + "ep": 70, + "val": { + "rmse": 0.7046297788619995 + }, + "test": { + "rmse": 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@@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "gin", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 90.2, + "dev": "cuda:1", + "ep": 100, + "val": { + "rmse": 0.8872742652893066 + }, + "val_adaptive": { + "rmse": 0.7704845070838928 + }, + "test": { + "rmse": 1.0246026515960693 + }, + "test_adaptive": { + "rmse": 0.8618570566177368 + }, + "fixed_val_steps": 8.0, + "adaptive_val_steps": 2.7214285714285715, + 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b/runs/ogbg-mollipo_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..a7f11fb --- /dev/null +++ b/runs/ogbg-mollipo_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "graphconv", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 87.3, + "dev": 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+1,49 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "pna", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 119.6, + "dev": "cuda:1", + "ep": 70, + "val": { + "rmse": 0.914740264415741 + }, + "val_adaptive": { + "rmse": 0.8654114603996277 + }, + "test": { + "rmse": 0.9266903400421143 + }, + "test_adaptive": { + "rmse": 0.8750127553939819 + }, + "fixed_val_steps": 8.0, + "adaptive_val_steps": 4.819047619047619, + 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+ "ep": 70, + "val": { + "rmse": 0.6720540523529053 + }, + "test": { + "rmse": 0.7270413041114807 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-mollipo_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..27e4416 --- /dev/null +++ b/runs/ogbg-mollipo_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_resgated_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "resgated", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": 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"ogbg-mollipo_sgc_classic_T0_ns1_h128_e100_s0", + "view": "sgc", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 34.6, + "dev": "cuda:1", + "ep": 70, + "val": { + "rmse": 0.750457763671875 + }, + "test": { + "rmse": 0.817555844783783 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-mollipo_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..1648b69 --- /dev/null +++ b/runs/ogbg-mollipo_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_sgc_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "sgc", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 72.1, + "dev": "cuda:1", + "ep": 90, + "val": { + "rmse": 0.7536844611167908 + }, + "test": { + "rmse": 0.7490182518959045 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-mollipo_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..3480ed6 --- /dev/null +++ b/runs/ogbg-mollipo_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "sgc", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 91.7, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 0.9196410775184631 + }, + "val_adaptive": { + "rmse": 0.754634439945221 + }, + "test": { + "rmse": 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b/runs/ogbg-mollipo_transformer_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_transformer_classic_T0_ns1_h128_e100_s0", + "view": "transformer", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 78.7, + "dev": "cuda:1", + "ep": 80, + "val": { + "rmse": 0.6809519529342651 + }, + "test": { + "rmse": 0.7346181273460388 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_transformer_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-mollipo_transformer_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..6d1cd1f --- /dev/null +++ b/runs/ogbg-mollipo_transformer_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_transformer_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "transformer", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rmse", + "sec": 74.7, + "dev": "cuda:1", + "ep": 90, + "val": { + "rmse": 0.6688172817230225 + }, + "test": { + "rmse": 0.7396050095558167 + } +} \ No newline at end of file diff --git a/runs/ogbg-mollipo_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-mollipo_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..68661c7 --- /dev/null +++ b/runs/ogbg-mollipo_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-mollipo", + "tag": "ogbg-mollipo_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "transformer", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + 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"ogbg-molsider_cheb_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "cheb", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 18.3, + "dev": "cuda:1", + "ep": 30, + "val": { + "rocauc": 0.626299014853098 + }, + "test": { + "rocauc": 0.609583177772403 + } +} \ No newline at end of file diff --git a/runs/ogbg-molsider_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molsider_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..c6089dd --- /dev/null +++ b/runs/ogbg-molsider_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "cheb", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:0", + "metric": "rocauc", + "sec": 30.5, + "dev": "cuda:0", + "ep": 90, + "val": { + "rocauc": 0.6409076943311921 + }, + "val_adaptive": { + "rocauc": 0.6415746496399081 + }, + "test": { + "rocauc": 0.6149744329414113 + }, 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b/runs/ogbg-molsider_gatv2_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_gatv2_classic_T0_ns1_h128_e100_s0", + "view": "gatv2", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 21.3, + "dev": "cuda:1", + "ep": 50, + "val": { + "rocauc": 0.6071193037623003 + }, + "test": { + "rocauc": 0.6013146804327355 + } +} \ No newline at end of file diff --git a/runs/ogbg-molsider_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molsider_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..260596d --- /dev/null +++ b/runs/ogbg-molsider_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_gatv2_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gatv2", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 35.6, + "dev": "cuda:1", + "ep": 70, + "val": { + "rocauc": 0.6462276348941932 + }, + "test": { + "rocauc": 0.6000090607166413 + } +} \ No newline at end of file diff --git a/runs/ogbg-molsider_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molsider_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..e6631f1 --- /dev/null +++ b/runs/ogbg-molsider_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "gatv2", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + 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b/runs/ogbg-molsider_graphconv_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_graphconv_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "graphconv", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 24.3, + "dev": "cuda:1", + "ep": 50, + "val": { + "rocauc": 0.6010260045148574 + }, + "test": { + "rocauc": 0.5962935439480032 + } +} \ No newline at end of file diff --git a/runs/ogbg-molsider_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json 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b/runs/ogbg-molsider_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "pna", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:3", + "metric": "rocauc", + "sec": 35.2, + "dev": "cuda:3", + "ep": 70, + "val": { + "rocauc": 0.5869831648034167 + }, + "val_adaptive": { + "rocauc": 0.5869831648034167 + }, + "test": { + "rocauc": 0.5961753244813196 + }, + "test_adaptive": 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b/runs/ogbg-molsider_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_resgated_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "resgated", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 28.0, + "dev": "cuda:1", + "ep": 70, + "val": { + "rocauc": 0.6204543981100222 + }, + "test": { + "rocauc": 0.5960257361986486 + } +} \ No newline at end of file diff --git a/runs/ogbg-molsider_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molsider_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..df6194b --- /dev/null +++ b/runs/ogbg-molsider_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "resgated", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:3", + "metric": "rocauc", + "sec": 29.0, + "dev": "cuda:3", + 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index 0000000..1ce0296 --- /dev/null +++ b/runs/ogbg-molsider_sgc_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_sgc_classic_T0_ns1_h128_e100_s0", + "view": "sgc", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 12.2, + "dev": "cuda:1", + "ep": 20, + "val": { + "rocauc": 0.6173711459877224 + }, + "test": { + "rocauc": 0.6042590538050838 + } +} \ No newline at end of file diff --git a/runs/ogbg-molsider_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-molsider_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..e656a13 --- /dev/null +++ b/runs/ogbg-molsider_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_sgc_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "sgc", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 15.3, + "dev": "cuda:1", + "ep": 20, + "val": { + "rocauc": 0.6151272572948054 + }, + "test": { + "rocauc": 0.6417135077812745 + } +} \ No newline at end of file diff --git a/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..168f5f7 --- /dev/null +++ b/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "sgc", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, 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a/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json b/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json new file mode 100644 index 0000000..d0a03a9 --- /dev/null +++ b/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0", + "view": "sgc", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 30, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + 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end of file diff --git a/runs/ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..49d5a4e --- /dev/null +++ b/runs/ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-molsider", + "tag": "ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "tag", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + 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+ "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_appnp_classic_T0_ns1_h128_e100_s0", + "view": "appnp", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 73.9, + "dev": "cuda:1", + "ep": 80, + "val": { + "rocauc": 0.7254553558600404 + }, + "test": { + "rocauc": 0.7158488769446065 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-moltox21_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..f86a36c --- /dev/null +++ b/runs/ogbg-moltox21_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_appnp_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "appnp", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 101.4, + "dev": "cuda:1", + "ep": 60, + "val": { + "rocauc": 0.7279951275996247 + }, + "test": { + "rocauc": 0.7153555287245948 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-moltox21_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..4034e03 --- /dev/null +++ b/runs/ogbg-moltox21_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "appnp", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:3", + "metric": "rocauc", + "sec": 173.4, + "dev": "cuda:3", + "ep": 70, 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file mode 100644 index 0000000..1ee54ec --- /dev/null +++ b/runs/ogbg-moltox21_arma_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_arma_classic_T0_ns1_h128_e100_s0", + "view": "arma", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 91.6, + "dev": "cuda:1", + "ep": 60, + "val": { + "rocauc": 0.7798972501326612 + }, + "test": { + "rocauc": 0.7222812510383411 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_arma_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-moltox21_arma_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..3f4c8e0 --- /dev/null +++ b/runs/ogbg-moltox21_arma_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_arma_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "arma", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 166.1, + "dev": "cuda:1", + "ep": 60, + "val": { + "rocauc": 0.7770957435163162 + }, + "test": { + "rocauc": 0.7208970968150412 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-moltox21_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..5724d7f --- /dev/null +++ b/runs/ogbg-moltox21_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "arma", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + 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+1,38 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_gatv2_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "gatv2", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 185.0, + "dev": "cuda:1", + "ep": 60, + "val": { + "rocauc": 0.7761905248713933 + }, + "test": { + "rocauc": 0.7302941629609098 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-moltox21_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..1cce6dc --- /dev/null +++ b/runs/ogbg-moltox21_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "gatv2", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 203.5, + "dev": "cuda:1", + "ep": 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a/runs/ogbg-moltox21_graphsage_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-moltox21_graphsage_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..0974e73 --- /dev/null +++ b/runs/ogbg-moltox21_graphsage_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_graphsage_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "graphsage", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 109.2, + "dev": "cuda:1", + "ep": 80, + "val": { + "rocauc": 0.7696559719157566 + }, + "test": { + 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0000000..617451b --- /dev/null +++ b/runs/ogbg-moltox21_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "pna", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 225.3, + "dev": "cuda:1", + "ep": 90, + "val": { + "rocauc": 0.7624732674125697 + }, + "val_adaptive": { + "rocauc": 0.7580383954116433 + }, + "test": { + "rocauc": 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b/runs/ogbg-moltox21_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..0b95cc6 --- /dev/null +++ b/runs/ogbg-moltox21_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "resgated", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 182.4, + "dev": 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a/runs/ogbg-moltox21_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-moltox21_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..1fbd5a4 --- /dev/null +++ b/runs/ogbg-moltox21_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "sgc", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + 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"lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 93.4, + "dev": "cuda:1", + "ep": 40, + "val": { + "rocauc": 0.7865543605336435 + }, + "test": { + "rocauc": 0.7415570498308578 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_tag_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-moltox21_tag_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..560afdf --- /dev/null +++ b/runs/ogbg-moltox21_tag_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_tag_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "tag", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 122.8, + "dev": "cuda:1", + "ep": 50, + "val": { + "rocauc": 0.7838617216718421 + }, + "test": { + "rocauc": 0.7341723374058734 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..3a2f6ea --- /dev/null +++ b/runs/ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "tag", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "exact", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:3", + "metric": "rocauc", + "sec": 168.4, + "dev": "cuda:3", + "ep": 100, + "val": { + "rocauc": 0.7700778158549199 + }, + "val_adaptive": { + "rocauc": 0.7732723159984056 + }, + "test": { + "rocauc": 0.7162575064186166 + }, + "test_adaptive": { + "rocauc": 0.7254468026027986 + }, + "fixed_val_steps": 8.0, + "adaptive_val_steps": 3.5019157088122603, + "fixed_steps": 8.0, + "adaptive_steps": 3.506377551020408 +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..7a13be9 --- /dev/null +++ b/runs/ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "tag", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 184.9, + "dev": "cuda:1", + "ep": 80, + "val": { + "rocauc": 0.7791811026208421 + }, + "val_adaptive": { + "rocauc": 0.783698445795415 + }, + "test": { + "rocauc": 0.7194750067722034 + }, + "test_adaptive": { + "rocauc": 0.7225403729796881 + }, + "fixed_val_steps": 8.0, + "adaptive_val_steps": 3.2835249042145596, + "fixed_steps": 8.0, + "adaptive_steps": 3.318877551020408 +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_transformer_classic_T0_ns1_h128_e100_s0.json b/runs/ogbg-moltox21_transformer_classic_T0_ns1_h128_e100_s0.json new file mode 100644 index 0000000..ec63ce7 --- /dev/null +++ b/runs/ogbg-moltox21_transformer_classic_T0_ns1_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_transformer_classic_T0_ns1_h128_e100_s0", + "view": "transformer", + "compute": "classic", + "T": 0, + "n_sup": 1, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 133.1, + "dev": "cuda:1", + "ep": 30, + "val": { + "rocauc": 0.7656017658932041 + }, + "test": { + "rocauc": 0.7309364489214464 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_transformer_fixed-rrog_T1_ns3_h128_e100_s0.json b/runs/ogbg-moltox21_transformer_fixed-rrog_T1_ns3_h128_e100_s0.json new file mode 100644 index 0000000..ff3555e --- /dev/null +++ b/runs/ogbg-moltox21_transformer_fixed-rrog_T1_ns3_h128_e100_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_transformer_fixed-rrog_T1_ns3_h128_e100_s0", + "view": "transformer", + "compute": "fixed-rrog", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "halt_max_steps": 8, + "halt_min_steps": 1, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 185.2, + "dev": "cuda:1", + "ep": 20, + "val": { + "rocauc": 0.7761466167802987 + }, + "test": { + "rocauc": 0.7291784660085319 + } +} \ No newline at end of file diff --git a/runs/ogbg-moltox21_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json b/runs/ogbg-moltox21_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json new file mode 100644 index 0000000..fd0a552 --- /dev/null +++ b/runs/ogbg-moltox21_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json @@ -0,0 +1,49 @@ +{ + "dataset": "ogbg-moltox21", + "tag": "ogbg-moltox21_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0", + "view": "transformer", + "compute": "rrog-act", + "T": 1, + "n_sup": 3, + "hidden": 128, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 100, + "eval_every": 10, + "lr": 0.001, + "bs": 128, + "lam_q": 0.1, + "halt_max_steps": 8, + "halt_min_steps": 2, + "halt_target": "loss", + "halt_loss_threshold": 0.2, + "halt_exploration_prob": 0.1, + "q_warmup_epochs": 0, + "act_train_mode": "stream", + "ema": 0.0, + "seed": 0, + "num_workers": 0, + "max_train_batches": 0, + "max_eval_batches": 0, + "device": "cuda:1", + "metric": "rocauc", + "sec": 191.2, + "dev": "cuda:1", + "ep": 40, + "val": { + "rocauc": 0.7839946999002233 + }, + "val_adaptive": { + "rocauc": 0.7907058937976815 + }, + "test": { + "rocauc": 0.723701343716436 + }, + "test_adaptive": { + "rocauc": 0.724166086603444 + }, + "fixed_val_steps": 8.0, + "adaptive_val_steps": 4.2005108556832695, + "fixed_steps": 8.0, + "adaptive_steps": 4.32780612244898 +} \ No newline at end of file diff --git a/runs/pe2_sweep.log b/runs/pe2_sweep.log new file mode 100644 index 0000000..9c83802 --- /dev/null +++ b/runs/pe2_sweep.log @@ -0,0 +1,97 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T12:46:37-05:00 +===== seed=0 full gsn ===== +ep20 solve_rate=0.000 mean_conflicts=89.71 +ep40 solve_rate=0.023 mean_conflicts=149.88 +ep60 solve_rate=0.113 mean_conflicts=86.64 +ep80 solve_rate=0.643 mean_conflicts=2.77 +ep100 solve_rate=0.587 mean_conflicts=8.41 +ep120 solve_rate=0.170 mean_conflicts=37.12 +ep140 solve_rate=0.053 mean_conflicts=54.13 +ep150 solve_rate=0.037 mean_conflicts=58.30 +[color_full_gsn_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.6433 mean_conflicts=2.77 @ep80 (153.5s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_gsn_n50_k3_p0.2_T3_ns3_s0.pt +[full] LE n=300 fail_rate=0.36 | lambda1 SOLVED mean -0.3404 (n=193) | UNSOLVED mean +0.0177 (n=107) | sep=+0.3580 | AUROC(fail|lambda1)=0.898 | mean_lambda1=-0.2127 +[pe=gsn s0] deterministic solve_rate = 0.627 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.853 0.733 0.613 0.623 0.888 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s0.json +===== seed=1 full gsn ===== +ep20 solve_rate=0.000 mean_conflicts=64.37 +ep40 solve_rate=0.130 mean_conflicts=24.72 +ep60 solve_rate=0.073 mean_conflicts=52.57 +ep80 solve_rate=0.533 mean_conflicts=19.95 +ep100 solve_rate=0.143 mean_conflicts=81.78 +ep120 solve_rate=0.080 mean_conflicts=67.85 +ep140 solve_rate=0.033 mean_conflicts=97.71 +ep150 solve_rate=0.010 mean_conflicts=121.37 +[color_full_gsn_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.5333 mean_conflicts=19.95 @ep80 (150.6s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_gsn_n50_k3_p0.2_T3_ns3_s1.pt +[full] LE n=300 fail_rate=0.47 | lambda1 SOLVED mean -0.2563 (n=160) | UNSOLVED mean +0.0329 (n=140) | sep=+0.2893 | AUROC(fail|lambda1)=0.854 | mean_lambda1=-0.1213 +[pe=gsn s1] deterministic solve_rate = 0.527 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.787 0.640 0.527 0.524 0.862 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s1.json +===== seed=2 full gsn ===== +ep20 solve_rate=0.000 mean_conflicts=73.69 +ep40 solve_rate=0.140 mean_conflicts=28.86 +ep60 solve_rate=0.350 mean_conflicts=19.34 +ep80 solve_rate=0.650 mean_conflicts=9.43 +ep100 solve_rate=0.460 mean_conflicts=16.59 +ep120 solve_rate=0.110 mean_conflicts=54.56 +ep140 solve_rate=0.030 mean_conflicts=77.26 +ep150 solve_rate=0.023 mean_conflicts=86.61 +[color_full_gsn_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.65 mean_conflicts=9.427 @ep80 (154.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_gsn_n50_k3_p0.2_T3_ns3_s2.pt +[full] LE n=300 fail_rate=0.35 | lambda1 SOLVED mean -0.3873 (n=195) | UNSOLVED mean -0.0600 (n=105) | sep=+0.3273 | AUROC(fail|lambda1)=0.839 | mean_lambda1=-0.2727 +[pe=gsn s2] deterministic solve_rate = 0.627 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.827 0.713 0.627 0.625 0.863 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s2.json +===== seed=3 full gsn ===== +ep20 solve_rate=0.000 mean_conflicts=105.31 +ep40 solve_rate=0.190 mean_conflicts=13.04 +ep60 solve_rate=0.097 mean_conflicts=53.37 +ep80 solve_rate=0.577 mean_conflicts=7.48 +ep100 solve_rate=0.417 mean_conflicts=31.46 +ep120 solve_rate=0.180 mean_conflicts=58.09 +ep140 solve_rate=0.110 mean_conflicts=83.96 +ep150 solve_rate=0.103 mean_conflicts=93.02 +[color_full_gsn_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.5767 mean_conflicts=7.477 @ep80 (150.0s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_gsn_n50_k3_p0.2_T3_ns3_s3.pt +[full] LE n=300 fail_rate=0.42 | lambda1 SOLVED mean -0.2939 (n=173) | UNSOLVED mean +0.0027 (n=127) | sep=+0.2966 | AUROC(fail|lambda1)=0.857 | mean_lambda1=-0.1684 +[pe=gsn s3] deterministic solve_rate = 0.573 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.807 0.660 0.573 0.565 0.865 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s3.json +===== seed=4 full gsn ===== +ep20 solve_rate=0.000 mean_conflicts=96.19 +ep40 solve_rate=0.140 mean_conflicts=21.32 +ep60 solve_rate=0.140 mean_conflicts=43.18 +ep80 solve_rate=0.367 mean_conflicts=17.62 +ep100 solve_rate=0.577 mean_conflicts=7.39 +ep120 solve_rate=0.163 mean_conflicts=76.12 +ep140 solve_rate=0.040 mean_conflicts=100.85 +ep150 solve_rate=0.040 mean_conflicts=104.33 +[color_full_gsn_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.5767 mean_conflicts=7.393 @ep100 (153.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_gsn_n50_k3_p0.2_T3_ns3_s4.pt +[full] LE n=300 fail_rate=0.42 | lambda1 SOLVED mean -0.3064 (n=173) | UNSOLVED mean +0.0036 (n=127) | sep=+0.3100 | AUROC(fail|lambda1)=0.890 | mean_lambda1=-0.1751 +[pe=gsn s4] deterministic solve_rate = 0.620 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.847 0.740 0.627 0.635 0.896 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s4.json +===== AGGREGATE (all pe: none/rwse/gsn) ===== +=== best solve_rate (deterministic, EMA) === + ('1step', 'none'): 0.293±0.062 (n=5) + ('full', 'gsn'): 0.596±0.044 (n=5) + ('full', 'none'): 0.457±0.087 (n=5) + ('full', 'rwse'): 0.503±0.064 (n=5) +=== LE AUROC(fail|lambda1) === + ('1step', 'none'): 0.821±0.036 (n=5) + ('full', 'gsn'): 0.868±0.023 (n=5) + ('full', 'none'): 0.868±0.032 (n=5) + ('full', 'rwse'): 0.837±0.041 (n=5) +=== PTRM sigma=0.2 === + ('full', 'gsn'): det 0.595±0.039 (n=5) | pass@K 0.824±0.025 (n=5) | lambda-sel 0.697±0.040 (n=5) | AUROC 0.875±0.014 (n=5) + ('full', 'none'): det 0.480±0.088 (n=5) | pass@K 0.739±0.113 (n=5) | lambda-sel 0.600±0.110 (n=5) | AUROC 0.853±0.023 (n=5) + ('full', 'rwse'): det 0.521±0.065 (n=5) | pass@K 0.883±0.075 (n=5) | lambda-sel 0.736±0.088 (n=5) | AUROC 0.837±0.028 (n=5) +done=2026-06-16T13:05:45-05:00 diff --git a/runs/pe3_sweep.log b/runs/pe3_sweep.log new file mode 100644 index 0000000..8092566 --- /dev/null +++ b/runs/pe3_sweep.log @@ -0,0 +1,220 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T13:42:05-05:00 +===== seed=0 #3 full sub ===== +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=56.87 +ep40 solve_rate=0.280 mean_conflicts=13.94 +ep60 solve_rate=0.207 mean_conflicts=44.20 +ep80 solve_rate=0.440 mean_conflicts=39.18 +ep100 solve_rate=0.710 mean_conflicts=1.94 +ep120 solve_rate=0.643 mean_conflicts=7.74 +ep140 solve_rate=0.530 mean_conflicts=26.79 +ep150 solve_rate=0.500 mean_conflicts=28.63 +[color_full_sub_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.71 mean_conflicts=1.94 @ep100 (155.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_sub_n50_k3_p0.2_T3_ns3_s0.pt +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[full] LE n=300 fail_rate=0.29 | lambda1 SOLVED mean -0.3371 (n=213) | UNSOLVED mean +0.0344 (n=87) | sep=+0.3714 | AUROC(fail|lambda1)=0.885 | mean_lambda1=-0.2293 +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=sub s0] deterministic solve_rate = 0.733 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.920 0.860 0.727 0.732 0.912 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s0.json +===== seed=0 #4 full none --contract ===== +ep20 solve_rate=0.000 mean_conflicts=163.48 +ep40 solve_rate=0.000 mean_conflicts=146.81 +ep60 solve_rate=0.000 mean_conflicts=135.64 +ep80 solve_rate=0.000 mean_conflicts=126.22 +ep100 solve_rate=0.000 mean_conflicts=113.24 +ep120 solve_rate=0.000 mean_conflicts=91.74 +ep140 solve_rate=0.000 mean_conflicts=88.39 +ep150 solve_rate=0.000 mean_conflicts=87.80 +[color_full_none_ctr_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.0 mean_conflicts=163.477 @ep20 (207.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s0.pt +[full] LE n=300 fail_rate=1.00 | lambda1 SOLVED mean +nan (n=0) | UNSOLVED mean -0.6308 (n=300) | sep=+nan | AUROC(fail|lambda1)=nan | mean_lambda1=-0.6308 +[pe=none s0] deterministic solve_rate = 0.000 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.000 0.000 0.000 0.000 nan + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s0.json +===== seed=1 #3 full sub ===== +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=99.67 +ep40 solve_rate=0.210 mean_conflicts=28.08 +ep60 solve_rate=0.233 mean_conflicts=59.81 +ep80 solve_rate=0.570 mean_conflicts=7.48 +ep100 solve_rate=0.303 mean_conflicts=60.79 +ep120 solve_rate=0.187 mean_conflicts=69.15 +ep140 solve_rate=0.107 mean_conflicts=63.47 +ep150 solve_rate=0.107 mean_conflicts=64.31 +[color_full_sub_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.57 mean_conflicts=7.483 @ep80 (148.6s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_sub_n50_k3_p0.2_T3_ns3_s1.pt +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[full] LE n=300 fail_rate=0.43 | lambda1 SOLVED mean -0.3139 (n=171) | UNSOLVED mean +0.0323 (n=129) | sep=+0.3462 | AUROC(fail|lambda1)=0.928 | mean_lambda1=-0.1650 +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=sub s1] deterministic solve_rate = 0.540 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.867 0.713 0.540 0.570 0.893 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s1.json +===== seed=1 #4 full none --contract ===== +ep20 solve_rate=0.000 mean_conflicts=107.59 +ep40 solve_rate=0.000 mean_conflicts=97.27 +ep60 solve_rate=0.000 mean_conflicts=84.15 +ep80 solve_rate=0.000 mean_conflicts=75.86 +ep100 solve_rate=0.000 mean_conflicts=99.62 +ep120 solve_rate=0.000 mean_conflicts=163.03 +ep140 solve_rate=0.000 mean_conflicts=162.94 +ep150 solve_rate=0.000 mean_conflicts=162.62 +[color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.0 mean_conflicts=107.593 @ep20 (206.4s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1.pt +[full] LE n=300 fail_rate=1.00 | lambda1 SOLVED mean +nan (n=0) | UNSOLVED mean -1.0479 (n=300) | sep=+nan | AUROC(fail|lambda1)=nan | mean_lambda1=-1.0479 +[pe=none s1] deterministic solve_rate = 0.000 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.000 0.000 0.000 0.000 nan + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1.json +===== seed=2 #3 full sub ===== +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=143.77 +ep40 solve_rate=0.280 mean_conflicts=19.26 +ep60 solve_rate=0.520 mean_conflicts=15.04 +ep80 solve_rate=0.670 mean_conflicts=3.32 +ep100 solve_rate=0.620 mean_conflicts=20.58 +ep120 solve_rate=0.403 mean_conflicts=60.92 +ep140 solve_rate=0.390 mean_conflicts=58.32 +ep150 solve_rate=0.377 mean_conflicts=55.34 +[color_full_sub_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.67 mean_conflicts=3.317 @ep80 (152.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_sub_n50_k3_p0.2_T3_ns3_s2.pt +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[full] LE n=300 fail_rate=0.33 | lambda1 SOLVED mean -0.3650 (n=201) | UNSOLVED mean +0.0472 (n=99) | sep=+0.4122 | AUROC(fail|lambda1)=0.937 | mean_lambda1=-0.2290 +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=sub s2] deterministic solve_rate = 0.707 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.893 0.800 0.700 0.688 0.919 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s2.json +===== seed=2 #4 full none --contract ===== +ep20 solve_rate=0.000 mean_conflicts=102.42 +ep40 solve_rate=0.000 mean_conflicts=89.46 +ep60 solve_rate=0.000 mean_conflicts=83.90 +ep80 solve_rate=0.000 mean_conflicts=90.79 +ep100 solve_rate=0.000 mean_conflicts=92.59 +ep120 solve_rate=0.000 mean_conflicts=84.45 +ep140 solve_rate=0.000 mean_conflicts=76.00 +ep150 solve_rate=0.000 mean_conflicts=69.42 +[color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.0 mean_conflicts=102.423 @ep20 (208.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2.pt +[full] LE n=300 fail_rate=1.00 | lambda1 SOLVED mean +nan (n=0) | UNSOLVED mean -0.9886 (n=300) | sep=+nan | AUROC(fail|lambda1)=nan | mean_lambda1=-0.9886 +[pe=none s2] deterministic solve_rate = 0.000 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.000 0.000 0.000 0.000 nan + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2.json +===== seed=3 #3 full sub ===== +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=109.49 +ep40 solve_rate=0.253 mean_conflicts=27.50 +ep60 solve_rate=0.203 mean_conflicts=33.37 +ep80 solve_rate=0.227 mean_conflicts=59.83 +ep100 solve_rate=0.043 mean_conflicts=81.74 +ep120 solve_rate=0.080 mean_conflicts=75.93 +ep140 solve_rate=0.170 mean_conflicts=56.67 +ep150 solve_rate=0.087 mean_conflicts=85.03 +[color_full_sub_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.2533 mean_conflicts=27.497 @ep40 (152.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_sub_n50_k3_p0.2_T3_ns3_s3.pt +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[full] LE n=300 fail_rate=0.75 | lambda1 SOLVED mean -0.3797 (n=76) | UNSOLVED mean -0.1929 (n=224) | sep=+0.1869 | AUROC(fail|lambda1)=0.805 | mean_lambda1=-0.2402 +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=sub s3] deterministic solve_rate = 0.280 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.380 0.260 0.260 0.247 0.831 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s3.json +===== seed=3 #4 full none --contract ===== +ep20 solve_rate=0.000 mean_conflicts=125.59 +ep40 solve_rate=0.000 mean_conflicts=118.58 +ep60 solve_rate=0.000 mean_conflicts=84.82 +ep80 solve_rate=0.000 mean_conflicts=65.44 +ep100 solve_rate=0.000 mean_conflicts=59.09 +ep120 solve_rate=0.000 mean_conflicts=61.66 +ep140 solve_rate=0.000 mean_conflicts=62.53 +ep150 solve_rate=0.000 mean_conflicts=63.31 +[color_full_none_ctr_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.0 mean_conflicts=125.593 @ep20 (206.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s3.pt +[full] LE n=300 fail_rate=1.00 | lambda1 SOLVED mean +nan (n=0) | UNSOLVED mean -0.5765 (n=300) | sep=+nan | AUROC(fail|lambda1)=nan | mean_lambda1=-0.5765 +[pe=none s3] deterministic solve_rate = 0.000 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.000 0.000 0.000 0.000 nan + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s3.json +===== seed=4 #3 full sub ===== +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +ep20 solve_rate=0.000 mean_conflicts=157.73 +ep40 solve_rate=0.140 mean_conflicts=24.79 +ep60 solve_rate=0.120 mean_conflicts=98.35 +ep80 solve_rate=0.623 mean_conflicts=4.32 +ep100 solve_rate=0.540 mean_conflicts=16.64 +ep120 solve_rate=0.380 mean_conflicts=41.04 +ep140 solve_rate=0.390 mean_conflicts=44.34 +ep150 solve_rate=0.387 mean_conflicts=43.48 +[color_full_sub_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.6233 mean_conflicts=4.323 @ep80 (152.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_sub_n50_k3_p0.2_T3_ns3_s4.pt +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[full] LE n=300 fail_rate=0.38 | lambda1 SOLVED mean -0.3913 (n=187) | UNSOLVED mean +0.0144 (n=113) | sep=+0.4057 | AUROC(fail|lambda1)=0.940 | mean_lambda1=-0.2385 +/home/yurenh2/rrog/diag/train_color.py:86: RuntimeWarning: invalid value encountered in divide + clus = np.where(deg > 1, tri / (deg * (deg - 1) / 2.0), 0.0) +[pe=sub s4] deterministic solve_rate = 0.647 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.907 0.793 0.647 0.645 0.914 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s4.json +===== seed=4 #4 full none --contract ===== +ep20 solve_rate=0.000 mean_conflicts=156.35 +ep40 solve_rate=0.000 mean_conflicts=121.15 +ep60 solve_rate=0.000 mean_conflicts=82.09 +ep80 solve_rate=0.000 mean_conflicts=80.90 +ep100 solve_rate=0.000 mean_conflicts=81.51 +ep120 solve_rate=0.000 mean_conflicts=80.79 +ep140 solve_rate=0.000 mean_conflicts=74.61 +ep150 solve_rate=0.000 mean_conflicts=73.39 +[color_full_none_ctr_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.0 mean_conflicts=156.353 @ep20 (208.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s4.pt +[full] LE n=300 fail_rate=1.00 | lambda1 SOLVED mean +nan (n=0) | UNSOLVED mean -0.7751 (n=300) | sep=+nan | AUROC(fail|lambda1)=nan | mean_lambda1=-0.7751 +[pe=none s4] deterministic solve_rate = 0.000 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.000 0.000 0.000 0.000 nan + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s4.json +===== AGGREGATE ===== +=== best solve_rate (deterministic, EMA) === + ('1step', 'none', '-'): 0.293±0.062 (n=5) + ('full', 'gsn', '-'): 0.596±0.044 (n=5) + ('full', 'none', '-'): 0.457±0.087 (n=5) + ('full', 'none', 'ctr'): 0.000±0.000 (n=5) + ('full', 'rwse', '-'): 0.503±0.064 (n=5) + ('full', 'sub', '-'): 0.565±0.163 (n=5) +=== LE AUROC(fail|lambda1) === + ('1step', 'none', '-'): 0.821±0.036 (n=5) + ('full', 'gsn', '-'): 0.868±0.023 (n=5) + ('full', 'none', '-'): 0.868±0.032 (n=5) + ('full', 'none', 'ctr'): nan±nan (n=5) + ('full', 'rwse', '-'): 0.837±0.041 (n=5) + ('full', 'sub', '-'): 0.899±0.051 (n=5) +=== LE mean_lambda1 (forced-contraction dose) === + ('1step', 'none', '-'): -0.051±0.092 (n=5) + ('full', 'gsn', '-'): -0.190±0.051 (n=5) + ('full', 'none', '-'): -0.197±0.032 (n=5) + ('full', 'none', 'ctr'): -0.804±0.188 (n=5) + ('full', 'rwse', '-'): -0.011±0.075 (n=5) + ('full', 'sub', '-'): -0.220±0.028 (n=5) +=== PTRM sigma=0.2 === + ('full', 'gsn', '-'): det 0.595±0.039 (n=5) | pass@K 0.824±0.025 (n=5) | lambda-sel 0.697±0.040 (n=5) | AUROC 0.875±0.014 (n=5) + ('full', 'none', '-'): det 0.480±0.088 (n=5) | pass@K 0.739±0.113 (n=5) | lambda-sel 0.600±0.110 (n=5) | AUROC 0.853±0.023 (n=5) + ('full', 'none', 'ctr'): det 0.000±0.000 (n=5) | pass@K 0.000±0.000 (n=5) | lambda-sel 0.000±0.000 (n=5) | AUROC nan±nan (n=5) + ('full', 'rwse', '-'): det 0.521±0.065 (n=5) | pass@K 0.883±0.075 (n=5) | lambda-sel 0.736±0.088 (n=5) | AUROC 0.837±0.028 (n=5) + ('full', 'sub', '-'): det 0.581±0.165 (n=5) | pass@K 0.793±0.207 (n=5) | lambda-sel 0.685±0.218 (n=5) | AUROC 0.894±0.033 (n=5) +done=2026-06-16T14:24:48-05:00 diff --git a/runs/pe_sweep.log b/runs/pe_sweep.log new file mode 100644 index 0000000..d147d94 --- /dev/null +++ b/runs/pe_sweep.log @@ -0,0 +1,66 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T11:31:39-05:00 +===== train full pe=none ===== +ep20 solve_rate=0.000 mean_conflicts=122.82 +ep40 solve_rate=0.167 mean_conflicts=60.87 +ep60 solve_rate=0.187 mean_conflicts=64.07 +ep80 solve_rate=0.313 mean_conflicts=23.74 +ep100 solve_rate=0.093 mean_conflicts=77.11 +ep120 solve_rate=0.060 mean_conflicts=69.50 +ep140 solve_rate=0.113 mean_conflicts=38.00 +ep150 solve_rate=0.103 mean_conflicts=39.66 +[color_full_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.3133 mean_conflicts=23.737 @ep80 (152.8s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_n50_k3_p0.2_T3_ns3_s0.pt +===== train full pe=rwse ===== +ep20 solve_rate=0.000 mean_conflicts=71.30 +ep40 solve_rate=0.193 mean_conflicts=29.00 +ep60 solve_rate=0.177 mean_conflicts=37.01 +ep80 solve_rate=0.483 mean_conflicts=6.12 +ep100 solve_rate=0.543 mean_conflicts=7.36 +ep120 solve_rate=0.497 mean_conflicts=13.22 +ep140 solve_rate=0.373 mean_conflicts=49.20 +ep150 solve_rate=0.363 mean_conflicts=50.49 +[color_full_rwse_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.5433 mean_conflicts=7.357 @ep100 (152.9s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_rwse_n50_k3_p0.2_T3_ns3_s0.pt +===== LE (full, both pe) ===== +[full] LE n=300 fail_rate=0.69 | lambda1 SOLVED mean -0.2724 (n=94) | UNSOLVED mean -0.0750 (n=206) | sep=+0.1974 | AUROC(fail|lambda1)=0.823 | mean_lambda1=-0.1369 +Traceback (most recent call last): + File "/home/yurenh2/rrog/diag/train_color.py", line 254, in + main() + ~~~~^^ + File "/home/yurenh2/rrog/diag/train_color.py", line 202, in main + run_le(model, te, dev, c['n_sup'] * c['T']) + ~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/yurenh2/rrog/diag/train_color.py", line 159, in run_le + col = model(xin, ei)[-1].argmax(-1) + ~~~~~^^^^^^^^^ + File "/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1776, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1787, in _call_impl + return forward_call(*args, **kwargs) + File "/home/yurenh2/rrog/diag/train_color.py", line 106, in forward + h0 = self.lin_in(xin) + File "/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1776, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1787, in _call_impl + return forward_call(*args, **kwargs) + File "/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch/nn/modules/linear.py", line 134, in forward + return F.linear(input, self.weight, self.bias) + ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +RuntimeError: mat1 and mat2 shapes cannot be multiplied (50x8 and 24x128) +!! le rwse failed +===== PTRM noise + lambda-select (both pe) ===== +--- pe=none --- +[pe=none] deterministic solve_rate = 0.327 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.1 0.560 0.440 0.353 0.323 0.820 + 0.2 0.747 0.520 0.307 0.313 0.817 + 0.4 0.860 0.620 0.300 0.292 0.777 +--- pe=rwse --- +[pe=rwse] deterministic solve_rate = 0.593 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.1 0.840 0.720 0.593 0.595 0.850 + 0.2 0.927 0.767 0.540 0.579 0.838 + 0.4 0.973 0.860 0.540 0.509 0.831 +done=2026-06-16T11:41:49-05:00 diff --git a/runs/pna_sweep.log b/runs/pna_sweep.log new file mode 100644 index 0000000..21ecfa1 --- /dev/null +++ b/runs/pna_sweep.log @@ -0,0 +1,142 @@ +PNA start gpu=0 2026-06-17T03:30:41-05:00 +== pna s0 == +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep20 solve_rate=0.027 mean_conflicts=13.04 +ep40 solve_rate=0.693 mean_conflicts=1.50 +ep60 solve_rate=0.867 mean_conflicts=0.58 +ep80 solve_rate=0.877 mean_conflicts=0.49 +ep100 solve_rate=0.913 mean_conflicts=0.26 +ep120 solve_rate=0.913 mean_conflicts=0.33 +ep140 solve_rate=0.920 mean_conflicts=0.32 +ep150 solve_rate=0.920 mean_conflicts=0.35 +[color_pna_full_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.92 @ep140 (718.5s) + wrote /home/yurenh2/rrog/runs/ckpt_color_pna_full_none_n50_k3_p0.2_T3_ns3_s0.pt +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pna/full] LE n=300 fail=0.08 | SOLVED -0.150 UNSOLVED +0.171 sep=+0.321 AUROC=0.867 mean_lam=-0.124 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pe=none s0] deterministic solve_rate = 0.920 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.980 0.913 0.920 0.910 0.819 + wrote /home/yurenh2/rrog/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s0.json +== pna s1 == +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep20 solve_rate=0.020 mean_conflicts=17.71 +ep40 solve_rate=0.687 mean_conflicts=1.50 +ep60 solve_rate=0.817 mean_conflicts=0.69 +ep80 solve_rate=0.893 mean_conflicts=0.43 +ep100 solve_rate=0.917 mean_conflicts=0.27 +ep120 solve_rate=0.917 mean_conflicts=0.31 +ep140 solve_rate=0.927 mean_conflicts=0.24 +ep150 solve_rate=0.943 mean_conflicts=0.15 +[color_pna_full_none_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.9433 @ep150 (718.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_pna_full_none_n50_k3_p0.2_T3_ns3_s1.pt +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pna/full] LE n=300 fail=0.06 | SOLVED -0.164 UNSOLVED -0.019 sep=+0.145 AUROC=0.727 mean_lam=-0.155 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pe=none s1] deterministic solve_rate = 0.940 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.987 0.967 0.953 0.933 0.794 + wrote /home/yurenh2/rrog/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s1.json +== pna s2 == +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep20 solve_rate=0.017 mean_conflicts=13.94 +ep40 solve_rate=0.737 mean_conflicts=1.15 +ep60 solve_rate=0.820 mean_conflicts=0.68 +ep80 solve_rate=0.883 mean_conflicts=0.41 +ep100 solve_rate=0.913 mean_conflicts=0.30 +ep120 solve_rate=0.907 mean_conflicts=0.30 +ep140 solve_rate=0.903 mean_conflicts=0.29 +ep150 solve_rate=0.917 mean_conflicts=0.20 +[color_pna_full_none_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.9167 @ep150 (714.9s) + wrote /home/yurenh2/rrog/runs/ckpt_color_pna_full_none_n50_k3_p0.2_T3_ns3_s2.pt +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pna/full] LE n=300 fail=0.08 | SOLVED -0.204 UNSOLVED +0.008 sep=+0.212 AUROC=0.773 mean_lam=-0.186 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pe=none s2] deterministic solve_rate = 0.940 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 1.000 0.947 0.953 0.934 0.800 + wrote /home/yurenh2/rrog/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s2.json +== pna s3 == +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep20 solve_rate=0.003 mean_conflicts=34.24 +ep40 solve_rate=0.747 mean_conflicts=1.30 +ep60 solve_rate=0.827 mean_conflicts=0.66 +ep80 solve_rate=0.893 mean_conflicts=0.47 +ep100 solve_rate=0.897 mean_conflicts=0.47 +ep120 solve_rate=0.913 mean_conflicts=0.28 +ep140 solve_rate=0.943 mean_conflicts=0.20 +ep150 solve_rate=0.933 mean_conflicts=0.19 +[color_pna_full_none_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.9433 @ep140 (614.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.pt +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pna/full] LE n=300 fail=0.06 | SOLVED -0.162 UNSOLVED +0.039 sep=+0.201 AUROC=0.756 mean_lam=-0.150 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pe=none s3] deterministic solve_rate = 0.960 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.993 0.987 0.933 0.945 0.885 + wrote /home/yurenh2/rrog/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json +== pna s4 == +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep20 solve_rate=0.007 mean_conflicts=24.65 +ep40 solve_rate=0.717 mean_conflicts=1.45 +ep60 solve_rate=0.827 mean_conflicts=0.60 +ep80 solve_rate=0.913 mean_conflicts=0.37 +ep100 solve_rate=0.920 mean_conflicts=0.28 +ep120 solve_rate=0.897 mean_conflicts=0.31 +ep140 solve_rate=0.897 mean_conflicts=0.36 +ep150 solve_rate=0.923 mean_conflicts=0.29 +[color_pna_full_none_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.9233 @ep150 (702.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_pna_full_none_n50_k3_p0.2_T3_ns3_s4.pt +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pna/full] LE n=300 fail=0.08 | SOLVED -0.137 UNSOLVED +0.070 sep=+0.207 AUROC=0.778 mean_lam=-0.121 +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/home/yurenh2/miniconda3/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +[pe=none s4] deterministic solve_rate = 0.947 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.993 0.973 0.920 0.935 0.844 + wrote /home/yurenh2/rrog/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s4.json +donePNA=2026-06-17T04:49:08-05:00 diff --git a/runs/ppgn_sweep.log b/runs/ppgn_sweep.log new file mode 100644 index 0000000..dd5e672 --- /dev/null +++ b/runs/ppgn_sweep.log @@ -0,0 +1,57 @@ +PPGN start gpu=1 2026-06-17T03:36:55-05:00 +== ppgn s0 == +ep20 solve=0.727 +ep40 solve=0.867 +ep60 solve=0.887 +ep80 solve=0.913 +ep100 solve=0.923 +ep120 solve=0.907 +ep140 solve=0.897 +ep150 solve=0.897 +[ppgn/full] solve=0.923 | LE AUROC=0.857 mean_lam=-0.025 | PTRM det=0.953 passK=0.987 lamsel=0.967 (645s) + wrote color_/le_color_/ptrm_color_ ppgn_full_none_n50_k3_p0.2_T3_ns3_s0 +== ppgn s1 == +ep20 solve=0.700 +ep40 solve=0.880 +ep60 solve=0.903 +ep80 solve=0.903 +ep100 solve=0.930 +ep120 solve=0.920 +ep140 solve=0.917 +ep150 solve=0.917 +[ppgn/full] solve=0.930 | LE AUROC=0.753 mean_lam=-0.010 | PTRM det=0.967 passK=0.987 lamsel=0.953 (639s) + wrote color_/le_color_/ptrm_color_ ppgn_full_none_n50_k3_p0.2_T3_ns3_s1 +== ppgn s2 == +ep20 solve=0.723 +ep40 solve=0.877 +ep60 solve=0.907 +ep80 solve=0.920 +ep100 solve=0.933 +ep120 solve=0.910 +ep140 solve=0.917 +ep150 solve=0.927 +[ppgn/full] solve=0.933 | LE AUROC=0.779 mean_lam=-0.011 | PTRM det=0.967 passK=0.973 lamsel=0.967 (639s) + wrote color_/le_color_/ptrm_color_ ppgn_full_none_n50_k3_p0.2_T3_ns3_s2 +== ppgn s3 == +ep20 solve=0.667 +ep40 solve=0.847 +ep60 solve=0.900 +ep80 solve=0.913 +ep100 solve=0.930 +ep120 solve=0.937 +ep140 solve=0.937 +ep150 solve=0.947 +[ppgn/full] solve=0.947 | LE AUROC=0.770 mean_lam=+0.014 | PTRM det=0.967 passK=0.987 lamsel=0.973 (640s) + wrote color_/le_color_/ptrm_color_ ppgn_full_none_n50_k3_p0.2_T3_ns3_s3 +== ppgn s4 == +ep20 solve=0.647 +ep40 solve=0.823 +ep60 solve=0.880 +ep80 solve=0.897 +ep100 solve=0.923 +ep120 solve=0.917 +ep140 solve=0.893 +ep150 solve=0.893 +[ppgn/full] solve=0.923 | LE AUROC=0.728 mean_lam=-0.039 | PTRM det=0.960 passK=0.980 lamsel=0.960 (639s) + wrote color_/le_color_/ptrm_color_ ppgn_full_none_n50_k3_p0.2_T3_ns3_s4 +donePPGN=2026-06-17T04:31:04-05:00 diff --git a/runs/ptrm_color.log b/runs/ptrm_color.log new file mode 100644 index 0000000..67dac38 --- /dev/null +++ b/runs/ptrm_color.log @@ -0,0 +1,7 @@ +deterministic solve_rate = 0.540 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.05 0.600 0.567 0.527 0.537 0.871 + 0.1 0.627 0.573 0.507 0.521 0.872 + 0.2 0.720 0.593 0.493 0.505 0.870 + 0.4 0.820 0.647 0.467 0.472 0.845 +done=2026-06-16T11:01:53-05:00 diff --git a/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..871294d --- /dev/null +++ b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 0, "det": 0.4733333333333334, "sigmas": {"0.2": {"passk": 0.47333333333333333, "lamsel": 0.47333333333333333, "random": 0.47333333333333333}}} \ No newline at end of file diff --git a/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..7acd118 --- /dev/null +++ b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 1, "det": 0.5533333333333333, "sigmas": {"0.2": {"passk": 0.5533333333333333, "lamsel": 0.5533333333333333, "random": 0.5533333333333333}}} \ No newline at end of file diff --git a/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..8c7783b --- /dev/null +++ b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 2, "det": 0.5666666666666667, "sigmas": {"0.2": {"passk": 0.5666666666666667, "lamsel": 0.5666666666666667, "random": 0.5666666666666667}}} \ No newline at end of file diff --git a/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..c64955d --- /dev/null +++ b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 3, "det": 0.5866666666666667, "sigmas": {"0.2": {"passk": 0.5866666666666667, "lamsel": 0.5866666666666667, "random": 0.5866666666666667}}} \ No newline at end of file diff --git a/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..8457967 --- /dev/null +++ b/runs/ptrm_color_cin_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1 @@ +{"conv": "cin", "pe": "none", "grad_mode": "full", "contract": false, "seed": 4, "det": 0.5266666666666666, "sigmas": {"0.2": {"passk": 0.5266666666666666, "lamsel": 0.5266666666666666, "random": 0.5266666666666666}}} \ No newline at end of file diff --git a/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..0a4625a --- /dev/null +++ b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 0, "det": 0.5133333333333333, "sigmas": {"0.2": {"passk": 0.5133333333333333, "lamsel": 0.5133333333333333, "random": 0.5133333333333333}}} \ No newline at end of file diff --git a/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..01e2418 --- /dev/null +++ b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 1, "det": 0.45333333333333337, "sigmas": {"0.2": {"passk": 0.4533333333333333, "lamsel": 0.4533333333333333, "random": 0.4533333333333333}}} \ No newline at end of file diff --git a/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..e72c48a --- /dev/null +++ b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 2, "det": 0.7733333333333333, "sigmas": {"0.2": {"passk": 0.7733333333333333, "lamsel": 0.7733333333333333, "random": 0.7733333333333333}}} \ No newline at end of file diff --git a/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..7cad929 --- /dev/null +++ b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 3, "det": 0.6133333333333333, "sigmas": {"0.2": {"passk": 0.6133333333333333, "lamsel": 0.6133333333333333, "random": 0.6133333333333333}}} \ No newline at end of file diff --git a/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..5741e75 --- /dev/null +++ b/runs/ptrm_color_esan_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1 @@ +{"conv": "esan", "pe": "none", "grad_mode": "full", "contract": false, "seed": 4, "det": 0.72, "sigmas": {"0.2": {"passk": 0.72, "lamsel": 0.72, "random": 0.72}}} \ No newline at end of file diff --git a/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..e7ccd9f --- /dev/null +++ b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,15 @@ +{ + "pe": "gsn", + "seed": 0, + "grad_mode": "full", + "det": 0.6266666666666667, + "sigmas": { + "0.2": { + "passk": 0.8533333333333334, + "lamsel": 0.7333333333333333, + "random": 0.6133333333333333, + "perRoll": 0.6233333333333333, + "auroc": 0.8884251810136766 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..41fae0b --- /dev/null +++ b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,15 @@ +{ + "pe": "gsn", + "seed": 1, + "grad_mode": "full", + "det": 0.5266666666666666, + "sigmas": { + "0.2": { + "passk": 0.7866666666666666, + "lamsel": 0.64, + "random": 0.5266666666666666, + "perRoll": 0.5241666666666667, + "auroc": 0.862321423102303 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..5db7789 --- /dev/null +++ b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,15 @@ +{ + "pe": "gsn", + "seed": 2, + "grad_mode": "full", + "det": 0.6266666666666667, + "sigmas": { + "0.2": { + "passk": 0.8266666666666667, + "lamsel": 0.7133333333333334, + "random": 0.6266666666666667, + "perRoll": 0.6245833333333334, + "auroc": 0.8630370672568245 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..fa8268e --- /dev/null +++ b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,15 @@ +{ + "pe": "gsn", + "seed": 3, + "grad_mode": "full", + "det": 0.5733333333333334, + "sigmas": { + "0.2": { + "passk": 0.8066666666666666, + "lamsel": 0.66, + "random": 0.5733333333333334, + "perRoll": 0.5645833333333333, + "auroc": 0.8653351930648494 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..f9b9749 --- /dev/null +++ b/runs/ptrm_color_full_gsn_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,15 @@ +{ + "pe": "gsn", + "seed": 4, + "grad_mode": "full", + "det": 0.62, + "sigmas": { + "0.2": { + "passk": 0.8466666666666667, + "lamsel": 0.74, + "random": 0.6266666666666667, + "perRoll": 0.6354166666666666, + "auroc": 0.8955960655737706 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..b2d510c --- /dev/null +++ b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,16 @@ +{ + "pe": "none", + "seed": 0, + "grad_mode": "full", + "contract": true, + "det": 0.0, + "sigmas": { + "0.2": { + "passk": 0.0, + "lamsel": 0.0, + "random": 0.0, + "perRoll": 0.0, + "auroc": NaN + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..fd60315 --- /dev/null +++ b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,16 @@ +{ + "pe": "none", + "seed": 1, + "grad_mode": "full", + "contract": true, + "det": 0.0, + "sigmas": { + "0.2": { + "passk": 0.0, + "lamsel": 0.0, + "random": 0.0, + "perRoll": 0.0, + "auroc": NaN + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..8fd27b1 --- /dev/null +++ b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,16 @@ +{ + "pe": "none", + "seed": 2, + "grad_mode": "full", + "contract": true, + "det": 0.0, + "sigmas": { + "0.2": { + "passk": 0.0, + "lamsel": 0.0, + "random": 0.0, + "perRoll": 0.0, + "auroc": NaN + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..f957227 --- /dev/null +++ b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,16 @@ +{ + "pe": "none", + "seed": 3, + "grad_mode": "full", + "contract": true, + "det": 0.0, + "sigmas": { + "0.2": { + "passk": 0.0, + "lamsel": 0.0, + "random": 0.0, + "perRoll": 0.0, + "auroc": NaN + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..b073283 --- /dev/null +++ b/runs/ptrm_color_full_none_ctr_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,16 @@ +{ + "pe": "none", + "seed": 4, + "grad_mode": "full", + "contract": true, + "det": 0.0, + "sigmas": { + "0.2": { + "passk": 0.0, + "lamsel": 0.0, + "random": 0.0, + "perRoll": 0.0, + "auroc": NaN + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..6aba919 --- /dev/null +++ b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,15 @@ +{ + "pe": "none", + "seed": 0, + "grad_mode": "full", + "det": 0.6266666666666667, + "sigmas": { + "0.2": { + "passk": 0.9, + "lamsel": 0.7733333333333333, + "random": 0.64, + "perRoll": 0.5954166666666667, + "auroc": 0.8829923628472736 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..704aa9b --- /dev/null +++ b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,15 @@ +{ + "pe": "none", + "seed": 1, + "grad_mode": "full", + "det": 0.48, + "sigmas": { + "0.2": { + "passk": 0.74, + "lamsel": 0.5933333333333334, + "random": 0.44, + "perRoll": 0.4558333333333333, + "auroc": 0.8691883334126559 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..8b223e1 --- /dev/null +++ b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,15 @@ +{ + "pe": "none", + "seed": 2, + "grad_mode": "full", + "det": 0.44666666666666666, + "sigmas": { + "0.2": { + "passk": 0.7733333333333333, + "lamsel": 0.62, + "random": 0.4666666666666667, + "perRoll": 0.4345833333333333, + "auroc": 0.8206013914569601 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..1dec48a --- /dev/null +++ b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,15 @@ +{ + "pe": "none", + "seed": 3, + "grad_mode": "full", + "det": 0.49333333333333335, + "sigmas": { + "0.2": { + "passk": 0.7333333333333333, + "lamsel": 0.5866666666666667, + "random": 0.49333333333333335, + "perRoll": 0.4716666666666667, + "auroc": 0.8563686448707517 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..4b91166 --- /dev/null +++ b/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,15 @@ +{ + "pe": "none", + "seed": 4, + "grad_mode": "full", + "det": 0.35333333333333333, + "sigmas": { + "0.2": { + "passk": 0.5466666666666666, + "lamsel": 0.4266666666666667, + "random": 0.37333333333333335, + "perRoll": 0.35791666666666666, + "auroc": 0.834668838325959 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..1cb1224 --- /dev/null +++ b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,15 @@ +{ + "pe": "rwse", + "seed": 0, + "grad_mode": "full", + "det": 0.4066666666666667, + "sigmas": { + "0.2": { + "passk": 0.74, + "lamsel": 0.5866666666666667, + "random": 0.49333333333333335, + "perRoll": 0.42625, + "auroc": 0.8078394458322773 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..1918714 --- /dev/null +++ b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,15 @@ +{ + "pe": "rwse", + "seed": 1, + "grad_mode": "full", + "det": 0.5466666666666666, + "sigmas": { + "0.2": { + "passk": 0.9466666666666667, + "lamsel": 0.7266666666666667, + "random": 0.5533333333333333, + "perRoll": 0.5070833333333333, + "auroc": 0.8140779642581045 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..59d1b2a --- /dev/null +++ b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,15 @@ +{ + "pe": "rwse", + "seed": 2, + "grad_mode": "full", + "det": 0.6, + "sigmas": { + "0.2": { + "passk": 0.8933333333333333, + "lamsel": 0.7866666666666666, + "random": 0.5733333333333334, + "perRoll": 0.55625, + "auroc": 0.8734314501239648 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..f3c83d4 --- /dev/null +++ b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,15 @@ +{ + "pe": "rwse", + "seed": 3, + "grad_mode": "full", + "det": 0.5066666666666667, + "sigmas": { + "0.2": { + "passk": 0.8933333333333333, + "lamsel": 0.7266666666666667, + "random": 0.47333333333333333, + "perRoll": 0.4970833333333333, + "auroc": 0.8230412007075241 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..d41321f --- /dev/null +++ b/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,15 @@ +{ + "pe": "rwse", + "seed": 4, + "grad_mode": "full", + "det": 0.5466666666666666, + "sigmas": { + "0.2": { + "passk": 0.94, + "lamsel": 0.8533333333333334, + "random": 0.49333333333333335, + "perRoll": 0.5575, + "auroc": 0.8680135063999166 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..31cc229 --- /dev/null +++ b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,16 @@ +{ + "pe": "sub", + "seed": 0, + "grad_mode": "full", + "contract": false, + "det": 0.7333333333333333, + "sigmas": { + "0.2": { + "passk": 0.92, + "lamsel": 0.86, + "random": 0.7266666666666667, + "perRoll": 0.7316666666666667, + "auroc": 0.9117701155930333 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..ab49809 --- /dev/null +++ b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,16 @@ +{ + "pe": "sub", + "seed": 1, + "grad_mode": "full", + "contract": false, + "det": 0.54, + "sigmas": { + "0.2": { + "passk": 0.8666666666666667, + "lamsel": 0.7133333333333334, + "random": 0.54, + "perRoll": 0.5695833333333333, + "auroc": 0.8928419932993937 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..58177d5 --- /dev/null +++ b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,16 @@ +{ + "pe": "sub", + "seed": 2, + "grad_mode": "full", + "contract": false, + "det": 0.7066666666666667, + "sigmas": { + "0.2": { + "passk": 0.8933333333333333, + "lamsel": 0.8, + "random": 0.7, + "perRoll": 0.6879166666666666, + "auroc": 0.9192786020367153 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..dfe302e --- /dev/null +++ b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,16 @@ +{ + "pe": "sub", + "seed": 3, + "grad_mode": "full", + "contract": false, + "det": 0.28, + "sigmas": { + "0.2": { + "passk": 0.38, + "lamsel": 0.26, + "random": 0.26, + "perRoll": 0.24666666666666667, + "auroc": 0.8310353010643388 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..ed96dea --- /dev/null +++ b/runs/ptrm_color_full_sub_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,16 @@ +{ + "pe": "sub", + "seed": 4, + "grad_mode": "full", + "contract": false, + "det": 0.6466666666666666, + "sigmas": { + "0.2": { + "passk": 0.9066666666666666, + "lamsel": 0.7933333333333333, + "random": 0.6466666666666666, + "perRoll": 0.6445833333333333, + "auroc": 0.9136490018498156 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..654be97 --- /dev/null +++ b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,17 @@ +{ + "conv": "gat", + "pe": "none", + "seed": 0, + "grad_mode": "full", + "contract": false, + "det": 0.006666666666666667, + "sigmas": { + "0.2": { + "passk": 0.04666666666666667, + "lamsel": 0.02, + "random": 0.02666666666666667, + "perRoll": 0.02, + "auroc": 0.20287698412698413 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..4bf9cab --- /dev/null +++ b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,17 @@ +{ + "conv": "gat", + "pe": "none", + "seed": 1, + "grad_mode": "full", + "contract": false, + "det": 0.013333333333333334, + "sigmas": { + "0.2": { + "passk": 0.03333333333333333, + "lamsel": 0.02, + "random": 0.013333333333333334, + "perRoll": 0.014166666666666666, + "auroc": 0.17698025955944507 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..8a6bd7b --- /dev/null +++ b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,17 @@ +{ + "conv": "gat", + "pe": "none", + "seed": 2, + "grad_mode": "full", + "contract": false, + "det": 0.006666666666666667, + "sigmas": { + "0.2": { + "passk": 0.03333333333333333, + "lamsel": 0.013333333333333334, + "random": 0.02, + "perRoll": 0.0125, + "auroc": 0.2478621659634318 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..1ec43f4 --- /dev/null +++ b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,17 @@ +{ + "conv": "gat", + "pe": "none", + "seed": 3, + "grad_mode": "full", + "contract": false, + "det": 0.11333333333333333, + "sigmas": { + "0.2": { + "passk": 0.22, + "lamsel": 0.11333333333333333, + "random": 0.11333333333333333, + "perRoll": 0.10541666666666667, + "auroc": 0.6144615798126258 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..0cc60ce --- /dev/null +++ b/runs/ptrm_color_gat_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,17 @@ +{ + "conv": "gat", + "pe": "none", + "seed": 4, + "grad_mode": "full", + "contract": false, + "det": 0.13333333333333333, + "sigmas": { + "0.2": { + "passk": 0.22666666666666666, + "lamsel": 0.14666666666666667, + "random": 0.12, + "perRoll": 0.11333333333333333, + "auroc": 0.4537676912870411 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..a48eef3 --- /dev/null +++ b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,17 @@ +{ + "conv": "gcn", + "pe": "none", + "seed": 0, + "grad_mode": "full", + "contract": false, + "det": 0.0, + "sigmas": { + "0.2": { + "passk": 0.0, + "lamsel": 0.0, + "random": 0.0, + "perRoll": 0.0, + "auroc": NaN + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..b14d8f5 --- /dev/null +++ b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,17 @@ +{ + "conv": "gcn", + "pe": "none", + "seed": 1, + "grad_mode": "full", + "contract": false, + "det": 0.0, + "sigmas": { + "0.2": { + "passk": 0.006666666666666667, + "lamsel": 0.0, + "random": 0.0, + "perRoll": 0.0004166666666666667, + "auroc": 0.940808670279283 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..fe87e26 --- /dev/null +++ b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,17 @@ +{ + "conv": "gcn", + "pe": "none", + "seed": 2, + "grad_mode": "full", + "contract": false, + "det": 0.006666666666666667, + "sigmas": { + "0.2": { + "passk": 0.006666666666666667, + "lamsel": 0.006666666666666667, + "random": 0.0, + "perRoll": 0.0025, + "auroc": 0.5626566416040101 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..af2a103 --- /dev/null +++ b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,17 @@ +{ + "conv": "gcn", + "pe": "none", + "seed": 3, + "grad_mode": "full", + "contract": false, + "det": 0.006666666666666667, + "sigmas": { + "0.2": { + "passk": 0.013333333333333334, + "lamsel": 0.0, + "random": 0.006666666666666667, + "perRoll": 0.00375, + "auroc": 0.6968725312514522 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..419d757 --- /dev/null +++ b/runs/ptrm_color_gcn_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,17 @@ +{ + "conv": "gcn", + "pe": "none", + "seed": 4, + "grad_mode": "full", + "contract": false, + "det": 0.0, + "sigmas": { + "0.2": { + "passk": 0.006666666666666667, + "lamsel": 0.0, + "random": 0.0, + "perRoll": 0.0008333333333333334, + "auroc": 0.06234361968306923 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..99119c2 --- /dev/null +++ b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "all", + "seed": 0, + "grad_mode": "full", + "contract": false, + "det": 0.6933333333333334, + "sigmas": { + "0.2": { + "passk": 0.8866666666666667, + "lamsel": 0.8333333333333334, + "random": 0.6933333333333334, + "perRoll": 0.6941666666666667, + "auroc": 0.8982764768032554 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..a703c1d --- /dev/null +++ b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "all", + "seed": 1, + "grad_mode": "full", + "contract": false, + "det": 0.76, + "sigmas": { + "0.2": { + "passk": 0.94, + "lamsel": 0.82, + "random": 0.7733333333333333, + "perRoll": 0.7354166666666667, + "auroc": 0.8783663090272357 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..ea4f20a --- /dev/null +++ b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "all", + "seed": 2, + "grad_mode": "full", + "contract": false, + "det": 0.32666666666666666, + "sigmas": { + "0.2": { + "passk": 0.46, + "lamsel": 0.32666666666666666, + "random": 0.28, + "perRoll": 0.30291666666666667, + "auroc": 0.6564342979484012 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..21b9d62 --- /dev/null +++ b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "all", + "seed": 3, + "grad_mode": "full", + "contract": false, + "det": 0.4666666666666667, + "sigmas": { + "0.2": { + "passk": 0.76, + "lamsel": 0.6266666666666667, + "random": 0.4266666666666667, + "perRoll": 0.45625, + "auroc": 0.8906062037474413 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..631b63f --- /dev/null +++ b/runs/ptrm_color_gin_full_all_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "all", + "seed": 4, + "grad_mode": "full", + "contract": false, + "det": 0.5933333333333334, + "sigmas": { + "0.2": { + "passk": 0.7866666666666666, + "lamsel": 0.7066666666666667, + "random": 0.5666666666666667, + "perRoll": 0.575, + "auroc": 0.9012666950838306 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..e8b66bb --- /dev/null +++ b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "lappe", + "seed": 0, + "grad_mode": "full", + "contract": false, + "det": 0.42, + "sigmas": { + "0.2": { + "passk": 0.76, + "lamsel": 0.6, + "random": 0.38666666666666666, + "perRoll": 0.3779166666666667, + "auroc": 0.8389898910830477 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..a054d9e --- /dev/null +++ b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "lappe", + "seed": 1, + "grad_mode": "full", + "contract": false, + "det": 0.62, + "sigmas": { + "0.2": { + "passk": 0.9266666666666666, + "lamsel": 0.7866666666666666, + "random": 0.5733333333333334, + "perRoll": 0.5829166666666666, + "auroc": 0.8634389199078263 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..a92273c --- /dev/null +++ b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "lappe", + "seed": 2, + "grad_mode": "full", + "contract": false, + "det": 0.41333333333333333, + "sigmas": { + "0.2": { + "passk": 0.76, + "lamsel": 0.54, + "random": 0.3933333333333333, + "perRoll": 0.40041666666666664, + "auroc": 0.8344894961887482 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..f4e112d --- /dev/null +++ b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "lappe", + "seed": 3, + "grad_mode": "full", + "contract": false, + "det": 0.5666666666666667, + "sigmas": { + "0.2": { + "passk": 0.8533333333333334, + "lamsel": 0.7266666666666667, + "random": 0.52, + "perRoll": 0.5191666666666667, + "auroc": 0.8635606210236708 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..1412f8a --- /dev/null +++ b/runs/ptrm_color_gin_full_lappe_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,17 @@ +{ + "conv": "gin", + "pe": "lappe", + "seed": 4, + "grad_mode": "full", + "contract": false, + "det": 0.34, + "sigmas": { + "0.2": { + "passk": 0.7533333333333333, + "lamsel": 0.5066666666666667, + "random": 0.30666666666666664, + "perRoll": 0.3333333333333333, + "auroc": 0.78412109375 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..5e7e845 --- /dev/null +++ b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,17 @@ +{ + "conv": "gps", + "pe": "none", + "seed": 0, + "grad_mode": "full", + "contract": false, + "det": 0.94, + "sigmas": { + "0.2": { + "passk": 0.9866666666666667, + "lamsel": 0.96, + "random": 0.92, + "perRoll": 0.9245833333333333, + "auroc": 0.8191261306795405 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..f6d82a8 --- /dev/null +++ b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,17 @@ +{ + "conv": "gps", + "pe": "none", + "seed": 1, + "grad_mode": "full", + "contract": false, + "det": 0.94, + "sigmas": { + "0.2": { + "passk": 0.9866666666666667, + "lamsel": 0.9533333333333334, + "random": 0.96, + "perRoll": 0.9383333333333334, + "auroc": 0.8573040180500215 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..763a720 --- /dev/null +++ b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,17 @@ +{ + "conv": "gps", + "pe": "none", + "seed": 2, + "grad_mode": "full", + "contract": false, + "det": 0.9533333333333334, + "sigmas": { + "0.2": { + "passk": 0.98, + "lamsel": 0.9533333333333334, + "random": 0.9266666666666666, + "perRoll": 0.9345833333333333, + "auroc": 0.8720889618373937 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..15a4af2 --- /dev/null +++ b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,17 @@ +{ + "conv": "gps", + "pe": "none", + "seed": 3, + "grad_mode": "full", + "contract": false, + "det": 0.9333333333333333, + "sigmas": { + "0.2": { + "passk": 0.9866666666666667, + "lamsel": 0.9733333333333334, + "random": 0.9533333333333334, + "perRoll": 0.9395833333333333, + "auroc": 0.8657756709228535 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..37d6217 --- /dev/null +++ b/runs/ptrm_color_gps_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,17 @@ +{ + "conv": "gps", + "pe": "none", + "seed": 4, + "grad_mode": "full", + "contract": false, + "det": 0.96, + "sigmas": { + "0.2": { + "passk": 0.9933333333333333, + "lamsel": 0.9666666666666667, + "random": 0.9466666666666667, + "perRoll": 0.9520833333333333, + "auroc": 0.9001503187137284 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..cb7503a --- /dev/null +++ b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,17 @@ +{ + "conv": "pna", + "pe": "none", + "seed": 0, + "grad_mode": "full", + "contract": false, + "det": 0.92, + "sigmas": { + "0.2": { + "passk": 0.98, + "lamsel": 0.9133333333333333, + "random": 0.92, + "perRoll": 0.9095833333333333, + "auroc": 0.8190162356373399 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..43eab37 --- /dev/null +++ b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,17 @@ +{ + "conv": "pna", + "pe": "none", + "seed": 1, + "grad_mode": "full", + "contract": false, + "det": 0.94, + "sigmas": { + "0.2": { + "passk": 0.9866666666666667, + "lamsel": 0.9666666666666667, + "random": 0.9533333333333334, + "perRoll": 0.9329166666666666, + "auroc": 0.7938964544397871 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..a7ea67f --- /dev/null +++ b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,17 @@ +{ + "conv": "pna", + "pe": "none", + "seed": 2, + "grad_mode": "full", + "contract": false, + "det": 0.94, + "sigmas": { + "0.2": { + "passk": 1.0, + "lamsel": 0.9466666666666667, + "random": 0.9533333333333334, + "perRoll": 0.93375, + "auroc": 0.7995644352392097 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..a6a2b71 --- /dev/null +++ b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,17 @@ +{ + "conv": "pna", + "pe": "none", + "seed": 3, + "grad_mode": "full", + "contract": false, + "det": 0.96, + "sigmas": { + "0.2": { + "passk": 0.9933333333333333, + "lamsel": 0.9866666666666667, + "random": 0.9333333333333333, + "perRoll": 0.945, + "auroc": 0.8850709475709475 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..a162925 --- /dev/null +++ b/runs/ptrm_color_pna_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,17 @@ +{ + "conv": "pna", + "pe": "none", + "seed": 4, + "grad_mode": "full", + "contract": false, + "det": 0.9466666666666667, + "sigmas": { + "0.2": { + "passk": 0.9933333333333333, + "lamsel": 0.9733333333333334, + "random": 0.92, + "perRoll": 0.935, + "auroc": 0.8440056675350792 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..fd253fa --- /dev/null +++ b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,17 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 0, + "det": 0.9533333333333334, + "sigmas": { + "0.2": { + "passk": 0.9866666666666667, + "lamsel": 0.9666666666666667, + "random": 0.9466666666666667, + "perRoll": 0.9445833333333333, + "auroc": 0.8244442159655867 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..1cb63f5 --- /dev/null +++ b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,17 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 1, + "det": 0.9666666666666667, + "sigmas": { + "0.2": { + "passk": 0.9866666666666667, + "lamsel": 0.9533333333333334, + "random": 0.9333333333333333, + "perRoll": 0.9533333333333334, + "auroc": 0.8222792832167831 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..b8ec6f3 --- /dev/null +++ b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,17 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 2, + "det": 0.9666666666666667, + "sigmas": { + "0.2": { + "passk": 0.9733333333333334, + "lamsel": 0.9666666666666667, + "random": 0.96, + "perRoll": 0.95625, + "auroc": 0.79279593318809 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..0c0cbd5 --- /dev/null +++ b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,17 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 3, + "det": 0.9666666666666667, + "sigmas": { + "0.2": { + "passk": 0.9866666666666667, + "lamsel": 0.9733333333333334, + "random": 0.9533333333333334, + "perRoll": 0.9595833333333333, + "auroc": 0.7407639519944851 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..f03ea8a --- /dev/null +++ b/runs/ptrm_color_ppgn_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,17 @@ +{ + "conv": "ppgn", + "pe": "none", + "grad_mode": "full", + "contract": false, + "seed": 4, + "det": 0.96, + "sigmas": { + "0.2": { + "passk": 0.98, + "lamsel": 0.96, + "random": 0.9533333333333334, + "perRoll": 0.9570833333333333, + "auroc": 0.7987074740797411 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json new file mode 100644 index 0000000..3149f14 --- /dev/null +++ b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s0.json @@ -0,0 +1,17 @@ +{ + "conv": "sage", + "pe": "none", + "seed": 0, + "grad_mode": "full", + "contract": false, + "det": 0.7466666666666667, + "sigmas": { + "0.2": { + "passk": 0.9533333333333334, + "lamsel": 0.8133333333333334, + "random": 0.7666666666666667, + "perRoll": 0.7625, + "auroc": 0.7712002684306394 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s1.json b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s1.json new file mode 100644 index 0000000..afb5102 --- /dev/null +++ b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s1.json @@ -0,0 +1,17 @@ +{ + "conv": "sage", + "pe": "none", + "seed": 1, + "grad_mode": "full", + "contract": false, + "det": 0.8266666666666667, + "sigmas": { + "0.2": { + "passk": 0.9733333333333334, + "lamsel": 0.8733333333333333, + "random": 0.7933333333333333, + "perRoll": 0.7808333333333334, + "auroc": 0.7023538028900586 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s2.json b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s2.json new file mode 100644 index 0000000..4f2366a --- /dev/null +++ b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s2.json @@ -0,0 +1,17 @@ +{ + "conv": "sage", + "pe": "none", + "seed": 2, + "grad_mode": "full", + "contract": false, + "det": 0.8466666666666667, + "sigmas": { + "0.2": { + "passk": 0.98, + "lamsel": 0.9066666666666666, + "random": 0.8333333333333334, + "perRoll": 0.8204166666666667, + "auroc": 0.7895241675199938 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json new file mode 100644 index 0000000..b978b19 --- /dev/null +++ b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s3.json @@ -0,0 +1,17 @@ +{ + "conv": "sage", + "pe": "none", + "seed": 3, + "grad_mode": "full", + "contract": false, + "det": 0.8133333333333334, + "sigmas": { + "0.2": { + "passk": 0.9533333333333334, + "lamsel": 0.88, + "random": 0.78, + "perRoll": 0.8016666666666666, + "auroc": 0.750294816471287 + } + } +} \ No newline at end of file diff --git a/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json new file mode 100644 index 0000000..b4daa33 --- /dev/null +++ b/runs/ptrm_color_sage_full_none_n50_k3_p0.2_T3_ns3_s4.json @@ -0,0 +1,17 @@ +{ + "conv": "sage", + "pe": "none", + "seed": 4, + "grad_mode": "full", + "contract": false, + "det": 0.84, + "sigmas": { + "0.2": { + "passk": 0.9866666666666667, + "lamsel": 0.8933333333333333, + "random": 0.8466666666666667, + "perRoll": 0.8345833333333333, + "auroc": 0.7519149487355867 + } + } +} \ No newline at end of file diff --git a/runs/real_gcn_L5_rni0_s0.json b/runs/real_gcn_L5_rni0_s0.json new file mode 100644 index 0000000..b9ec4df --- /dev/null +++ b/runs/real_gcn_L5_rni0_s0.json @@ -0,0 +1,18 @@ +{ + "dataset": "Peptides-struct", + "tag": "gcn_L5_rni0_s0", + "conv": "gcn", + "layers": 5, + "hidden": 128, + "rni": 0, + "epochs": 150, + "lr": 0.001, + "bs": 128, + "seed": 0, + "sec": 161.5, + "dev": "cuda", + "ep": 150, + "train_mae": 0.244050630256077, + "val_mae": 0.25049042685914025, + "test_mae": 0.2555193755450103 +} \ No newline at end of file diff --git a/runs/real_gin_L10_rni0_s0.json b/runs/real_gin_L10_rni0_s0.json new file mode 100644 index 0000000..3b028b8 --- /dev/null +++ b/runs/real_gin_L10_rni0_s0.json @@ -0,0 +1,18 @@ +{ + "dataset": "Peptides-struct", + "tag": "gin_L10_rni0_s0", + "conv": "gin", + "layers": 10, + "hidden": 128, + "rni": 0, + "epochs": 150, + "lr": 0.001, + "bs": 128, + "seed": 0, + "sec": 243.5, + "dev": "cuda", + "ep": 135, + "train_mae": 0.2384826198831858, + "val_mae": 0.24895160110156447, + "test_mae": 0.2550770111042328 +} \ No newline at end of file diff --git a/runs/real_gin_L3_rni0_s0.json b/runs/real_gin_L3_rni0_s0.json new file mode 100644 index 0000000..8ec6c07 --- /dev/null +++ b/runs/real_gin_L3_rni0_s0.json @@ -0,0 +1,18 @@ +{ + "dataset": "Peptides-struct", + "tag": "gin_L3_rni0_s0", + "conv": "gin", + "layers": 3, + "hidden": 128, + "rni": 0, + "epochs": 3, + "lr": 0.001, + "bs": 128, + "seed": 0, + "sec": 3.9, + "dev": "cuda", + "ep": 3, + "train_mae": 0.347590095878069, + "val_mae": 0.33667740190109574, + "test_mae": 0.3489650007594344 +} \ No newline at end of file diff --git a/runs/real_gin_L3_rni16_s0.json b/runs/real_gin_L3_rni16_s0.json new file mode 100644 index 0000000..357741b --- /dev/null +++ b/runs/real_gin_L3_rni16_s0.json @@ -0,0 +1,18 @@ +{ + "dataset": "Peptides-struct", + "tag": "gin_L3_rni16_s0", + "conv": "gin", + "layers": 3, + "hidden": 128, + "rni": 16, + "epochs": 3, + "lr": 0.001, + "bs": 128, + "seed": 0, + "sec": 3.7, + "dev": "cuda", + "ep": 3, + "train_mae": 0.40587605805157545, + "val_mae": 0.39079357209850374, + "test_mae": 0.40458849098375466 +} \ No newline at end of file diff --git a/runs/real_gin_L5_rni0_s0.json b/runs/real_gin_L5_rni0_s0.json new file mode 100644 index 0000000..08391be --- /dev/null +++ b/runs/real_gin_L5_rni0_s0.json @@ -0,0 +1,18 @@ +{ + "dataset": "Peptides-struct", + "tag": "gin_L5_rni0_s0", + "conv": "gin", + "layers": 5, + "hidden": 128, + "rni": 0, + "epochs": 150, + "lr": 0.001, + "bs": 128, + "seed": 0, + "sec": 161.1, + "dev": "cuda", + "ep": 135, + "train_mae": 0.23827263818608818, + "val_mae": 0.24697842829861874, + "test_mae": 0.25350159751862633 +} \ No newline at end of file diff --git a/runs/real_gin_L5_rni16_s0.json b/runs/real_gin_L5_rni16_s0.json new file mode 100644 index 0000000..db6b7fc --- /dev/null +++ b/runs/real_gin_L5_rni16_s0.json @@ -0,0 +1,18 @@ +{ + "dataset": "Peptides-struct", + "tag": "gin_L5_rni16_s0", + "conv": "gin", + "layers": 5, + "hidden": 128, + "rni": 16, + "epochs": 150, + "lr": 0.001, + "bs": 128, + "seed": 0, + "sec": 167.8, + "dev": "cuda", + "ep": 150, + "train_mae": 0.236489369612221, + "val_mae": 0.24831518891272308, + "test_mae": 0.25482755748563857 +} \ No newline at end of file diff --git a/runs/real_sweep_20260616_081956.log b/runs/real_sweep_20260616_081956.log new file mode 100644 index 0000000..bbf5d41 --- /dev/null +++ b/runs/real_sweep_20260616_081956.log @@ -0,0 +1,54 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T08:19:56-05:00 +===== --conv gin --layers 5 --rni 0 ===== +ep15 val_mae=0.4472 +ep30 val_mae=0.2721 +ep45 val_mae=0.2886 +ep60 val_mae=0.2730 +ep75 val_mae=0.2963 +ep90 val_mae=0.2586 +ep105 val_mae=0.2562 +ep120 val_mae=0.2491 +ep135 val_mae=0.2470 +ep150 val_mae=0.2474 +[gin_L5_rni0_s0] train_mae=0.2383 val_mae=0.2470 test_mae=0.2535 @ep135 (161.1s) + wrote /home/yurenh2/rrog/runs/real_gin_L5_rni0_s0.json +===== --conv gin --layers 10 --rni 0 ===== +ep15 val_mae=0.3038 +ep30 val_mae=0.6204 +ep45 val_mae=0.2929 +ep60 val_mae=0.2667 +ep75 val_mae=0.2624 +ep90 val_mae=0.2608 +ep105 val_mae=0.2526 +ep120 val_mae=0.2511 +ep135 val_mae=0.2490 +ep150 val_mae=0.2492 +[gin_L10_rni0_s0] train_mae=0.2385 val_mae=0.2490 test_mae=0.2551 @ep135 (243.5s) + wrote /home/yurenh2/rrog/runs/real_gin_L10_rni0_s0.json +===== --conv gin --layers 5 --rni 16 ===== +ep15 val_mae=0.4952 +ep30 val_mae=0.2769 +ep45 val_mae=0.2618 +ep60 val_mae=0.2594 +ep75 val_mae=0.2753 +ep90 val_mae=0.2532 +ep105 val_mae=0.2523 +ep120 val_mae=0.2506 +ep135 val_mae=0.2488 +ep150 val_mae=0.2483 +[gin_L5_rni16_s0] train_mae=0.2365 val_mae=0.2483 test_mae=0.2548 @ep150 (167.8s) + wrote /home/yurenh2/rrog/runs/real_gin_L5_rni16_s0.json +===== --conv gcn --layers 5 --rni 0 ===== +ep15 val_mae=0.2776 +ep30 val_mae=0.2730 +ep45 val_mae=0.2642 +ep60 val_mae=0.2619 +ep75 val_mae=0.2570 +ep90 val_mae=0.2570 +ep105 val_mae=0.2533 +ep120 val_mae=0.2520 +ep135 val_mae=0.2513 +ep150 val_mae=0.2505 +[gcn_L5_rni0_s0] train_mae=0.2441 val_mae=0.2505 test_mae=0.2555 @ep150 (161.5s) + wrote /home/yurenh2/rrog/runs/real_gcn_L5_rni0_s0.json +done=2026-06-16T08:33:03-05:00 diff --git a/runs/rec_1step_sig0.0_K1_bestq_T3_ns3_s0.json b/runs/rec_1step_sig0.0_K1_bestq_T3_ns3_s0.json new file mode 100644 index 0000000..dc1db82 --- /dev/null +++ b/runs/rec_1step_sig0.0_K1_bestq_T3_ns3_s0.json @@ -0,0 +1,35 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_1step_sig0.0_K1_bestq_T3_ns3_s0", + "grad_mode": "1step", + "sigma": 0.0, + "K": 1, + "select": "bestq", + "T": 3, + "n_sup": 3, + "hidden": 128, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "seed": 0, + "sec": 168.0, + "dev": "cuda", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 80, + "val_mae": [ + 0.19435928761959076, + 0.2852666974067688 + ], + "test_mae": [ + 0.2114018052816391, + 0.29347068071365356 + ], + "test_mae_oracle": [ + 0.2114018052816391, + 0.29347068071365356 + ] +} \ No newline at end of file diff --git a/runs/rec_full_sig0.0_K1_bestq_T3_ns3_s0.json b/runs/rec_full_sig0.0_K1_bestq_T3_ns3_s0.json new file mode 100644 index 0000000..ea7b4fa --- /dev/null +++ b/runs/rec_full_sig0.0_K1_bestq_T3_ns3_s0.json @@ -0,0 +1,35 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_full_sig0.0_K1_bestq_T3_ns3_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "bestq", + "T": 3, + "n_sup": 3, + "hidden": 128, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "seed": 0, + "sec": 209.3, + "dev": "cuda", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 140, + "val_mae": [ + 0.1493159532546997, + 0.20290319621562958 + ], + "test_mae": [ + 0.14498460292816162, + 0.197983056306839 + ], + "test_mae_oracle": [ + 0.14498460292816162, + 0.197983056306839 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_appnp_full_sig0.0_K1_none_T0_ns1_trace_s0.json b/runs/rec_rrog_appnp_full_sig0.0_K1_none_T0_ns1_trace_s0.json new file mode 100644 index 0000000..1672f92 --- /dev/null +++ b/runs/rec_rrog_appnp_full_sig0.0_K1_none_T0_ns1_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_appnp_full_sig0.0_K1_none_T0_ns1_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 0, + "n_sup": 1, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "appnp", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 149.8, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 140, + "val_mae": [ + 0.516572117805481, + 0.487392783164978 + ], + "test_mae": [ + 0.5241897702217102, + 0.49413174390792847 + ], + "test_mae_oracle": [ + 0.5241897702217102, + 0.49413174390792847 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_appnp_full_sig0.0_K1_none_T1_ns3_trace_s0.json b/runs/rec_rrog_appnp_full_sig0.0_K1_none_T1_ns3_trace_s0.json new file mode 100644 index 0000000..96373c9 --- /dev/null +++ b/runs/rec_rrog_appnp_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_appnp_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "appnp", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 175.6, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 120, + "val_mae": [ + 0.48746374249458313, + 0.4855128228664398 + ], + "test_mae": [ + 0.4944251477718353, + 0.4900885820388794 + ], + "test_mae_oracle": [ + 0.4944251477718353, + 0.4900885820388794 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_arma_full_sig0.0_K1_none_T0_ns1_trace_s0.json b/runs/rec_rrog_arma_full_sig0.0_K1_none_T0_ns1_trace_s0.json new file mode 100644 index 0000000..045ccf9 --- /dev/null +++ b/runs/rec_rrog_arma_full_sig0.0_K1_none_T0_ns1_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_arma_full_sig0.0_K1_none_T0_ns1_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 0, + "n_sup": 1, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "arma", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 136.4, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.14000031352043152, + 0.2056213617324829 + ], + "test_mae": [ + 0.13872109353542328, + 0.201865091919899 + ], + "test_mae_oracle": [ + 0.13872109353542328, + 0.201865091919899 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_arma_full_sig0.0_K1_none_T1_ns3_trace_s0.json b/runs/rec_rrog_arma_full_sig0.0_K1_none_T1_ns3_trace_s0.json new file mode 100644 index 0000000..65b4a32 --- /dev/null +++ b/runs/rec_rrog_arma_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_arma_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "arma", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 213.2, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.0940091535449028, + 0.14743280410766602 + ], + "test_mae": [ + 0.10224228352308273, + 0.13551878929138184 + ], + "test_mae_oracle": [ + 0.10224228352308273, + 0.13551878929138184 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_cheb_full_sig0.0_K1_none_T0_ns1_trace_s0.json b/runs/rec_rrog_cheb_full_sig0.0_K1_none_T0_ns1_trace_s0.json new file mode 100644 index 0000000..81e7113 --- /dev/null +++ b/runs/rec_rrog_cheb_full_sig0.0_K1_none_T0_ns1_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_cheb_full_sig0.0_K1_none_T0_ns1_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 0, + "n_sup": 1, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "cheb", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 112.8, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.16218321025371552, + 0.24164889752864838 + ], + "test_mae": [ + 0.14866158366203308, + 0.23999349772930145 + ], + "test_mae_oracle": [ + 0.14866158366203308, + 0.23999349772930145 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_cheb_full_sig0.0_K1_none_T1_ns3_trace_s0.json b/runs/rec_rrog_cheb_full_sig0.0_K1_none_T1_ns3_trace_s0.json new file mode 100644 index 0000000..477b677 --- /dev/null +++ b/runs/rec_rrog_cheb_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_cheb_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "cheb", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 149.4, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.08989150822162628, + 0.19968892633914948 + ], + "test_mae": [ + 0.08699783682823181, + 0.1959630250930786 + ], + "test_mae_oracle": [ + 0.08699783682823181, + 0.1959630250930786 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_film_full_sig0.0_K1_none_T0_ns1_trace_s0.json b/runs/rec_rrog_film_full_sig0.0_K1_none_T0_ns1_trace_s0.json new file mode 100644 index 0000000..da32094 --- /dev/null +++ b/runs/rec_rrog_film_full_sig0.0_K1_none_T0_ns1_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_film_full_sig0.0_K1_none_T0_ns1_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 0, + "n_sup": 1, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "film", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 102.7, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.18675006926059723, + 0.30383461713790894 + ], + "test_mae": [ + 0.1926984190940857, + 0.3070546090602875 + ], + "test_mae_oracle": [ + 0.1926984190940857, + 0.3070546090602875 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_film_full_sig0.0_K1_none_T1_ns3_trace_s0.json b/runs/rec_rrog_film_full_sig0.0_K1_none_T1_ns3_trace_s0.json new file mode 100644 index 0000000..d5647b0 --- /dev/null +++ b/runs/rec_rrog_film_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_film_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "film", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 216.1, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.287736177444458, + 0.4021036922931671 + ], + "test_mae": [ + 0.25880178809165955, + 0.40551459789276123 + ], + "test_mae_oracle": [ + 0.25880178809165955, + 0.40551459789276123 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0.json b/runs/rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0.json new file mode 100644 index 0000000..288f622 --- /dev/null +++ b/runs/rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "bestq", + "T": 0, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 40, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "seed": 0, + "sec": 12.6, + "dev": "cuda", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 40, + "val_mae": [ + 0.5319395661354065, + 0.5700212717056274 + ], + "test_mae": [ + 0.5142009854316711, + 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0.21319814026355743, + 0.30013495683670044 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_full_sig0.0_K1_bestq_T2_ns2_s7.json b/runs/rec_rrog_full_sig0.0_K1_bestq_T2_ns2_s7.json new file mode 100644 index 0000000..11083e9 --- /dev/null +++ b/runs/rec_rrog_full_sig0.0_K1_bestq_T2_ns2_s7.json @@ -0,0 +1,38 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_full_sig0.0_K1_bestq_T2_ns2_s7", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "bestq", + "T": 2, + "n_sup": 2, + "hidden": 16, + "agg_layers": 1, + "compute_layers": 2, + "epochs": 1, + "lr": 0.001, + "bs": 4096, + "lam_q": 1.0, + "seed": 7, + "sec": 0.9, + "dev": "cuda", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 1, + "val_mae": [ + 1.9260238409042358, + 1.1891183853149414 + ], + "test_mae": [ + 1.9688374996185303, + 1.1753125190734863 + ], + "test_mae_oracle": [ + 1.9688374996185303, + 1.1753125190734863 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0.json b/runs/rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0.json new file mode 100644 index 0000000..6cb172d --- /dev/null +++ b/runs/rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0.json @@ -0,0 +1,38 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "bestq", + "T": 3, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "epochs": 40, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "seed": 0, + "sec": 22.6, + "dev": "cuda", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 40, + "val_mae": [ + 0.21103313565254211, + 0.2831687033176422 + ], + "test_mae": [ + 0.20590344071388245, + 0.28427624702453613 + ], + "test_mae_oracle": [ + 0.20590344071388245, + 0.28427624702453613 + ] +} \ No newline at end of file diff --git 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b/runs/rec_rrog_gatv2_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_gatv2_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "gatv2", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 160.3, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.10159114748239517, + 0.21391241252422333 + ], + "test_mae": [ + 0.1038370430469513, + 0.20821833610534668 + ], + "test_mae_oracle": [ + 0.1038370430469513, + 0.20821833610534668 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_gcn_full_sig0.0_K1_none_T0_ns1_trace_s0.json b/runs/rec_rrog_gcn_full_sig0.0_K1_none_T0_ns1_trace_s0.json new file mode 100644 index 0000000..4ce1d1f --- /dev/null +++ b/runs/rec_rrog_gcn_full_sig0.0_K1_none_T0_ns1_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_gcn_full_sig0.0_K1_none_T0_ns1_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 0, + "n_sup": 1, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "gcn", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 86.5, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.2706347703933716, + 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--git a/runs/rec_rrog_gine_full_sig0.0_K1_none_T1_ns3_trace_s0.json b/runs/rec_rrog_gine_full_sig0.0_K1_none_T1_ns3_trace_s0.json new file mode 100644 index 0000000..5ecc8f1 --- /dev/null +++ b/runs/rec_rrog_gine_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_gine_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "gine", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 159.6, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.0580325685441494, + 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"soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 137.8, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 180, + "val_mae": [ + 0.07244974374771118, + 0.11092057079076767 + ], + "test_mae": [ + 0.06887289136648178, + 0.10761728137731552 + ], + "test_mae_oracle": [ + 0.06887289136648178, + 0.10761728137731552 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_sgc_full_sig0.0_K1_none_T0_ns1_trace_s0.json b/runs/rec_rrog_sgc_full_sig0.0_K1_none_T0_ns1_trace_s0.json new file mode 100644 index 0000000..11dab34 --- /dev/null +++ b/runs/rec_rrog_sgc_full_sig0.0_K1_none_T0_ns1_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_sgc_full_sig0.0_K1_none_T0_ns1_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 0, + "n_sup": 1, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "sgc", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 91.8, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.29122766852378845, + 0.33744269609451294 + ], + "test_mae": [ + 0.2915189266204834, + 0.3516658842563629 + ], + "test_mae_oracle": [ + 0.2915189266204834, + 0.3516658842563629 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_sgc_full_sig0.0_K1_none_T1_ns3_trace_s0.json b/runs/rec_rrog_sgc_full_sig0.0_K1_none_T1_ns3_trace_s0.json new file mode 100644 index 0000000..d9f7863 --- /dev/null +++ b/runs/rec_rrog_sgc_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_sgc_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "sgc", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 124.9, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.19793416559696198, + 0.3029009997844696 + ], + "test_mae": [ + 0.1908223181962967, + 0.3157658874988556 + ], + "test_mae_oracle": [ + 0.1908223181962967, + 0.3157658874988556 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_tag_full_sig0.0_K1_none_T0_ns1_trace_s0.json b/runs/rec_rrog_tag_full_sig0.0_K1_none_T0_ns1_trace_s0.json new file mode 100644 index 0000000..bccb853 --- /dev/null +++ b/runs/rec_rrog_tag_full_sig0.0_K1_none_T0_ns1_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_tag_full_sig0.0_K1_none_T0_ns1_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 0, + "n_sup": 1, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "tag", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 109.9, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.11659888178110123, + 0.17228826880455017 + ], + "test_mae": [ + 0.11192158609628677, + 0.17113320529460907 + ], + "test_mae_oracle": [ + 0.11192158609628677, + 0.17113320529460907 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_tag_full_sig0.0_K1_none_T1_ns3_trace_s0.json b/runs/rec_rrog_tag_full_sig0.0_K1_none_T1_ns3_trace_s0.json new file mode 100644 index 0000000..b4a8256 --- /dev/null +++ b/runs/rec_rrog_tag_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_tag_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "tag", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 147.1, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.051080916076898575, + 0.08987285196781158 + ], + "test_mae": [ + 0.05129510164260864, + 0.08730053156614304 + ], + "test_mae_oracle": [ + 0.05129510164260864, + 0.08730053156614304 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_transformer_full_sig0.0_K1_none_T0_ns1_trace_s0.json b/runs/rec_rrog_transformer_full_sig0.0_K1_none_T0_ns1_trace_s0.json new file mode 100644 index 0000000..7fad586 --- /dev/null +++ b/runs/rec_rrog_transformer_full_sig0.0_K1_none_T0_ns1_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_transformer_full_sig0.0_K1_none_T0_ns1_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 0, + "n_sup": 1, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "transformer", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 129.3, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 200, + "val_mae": [ + 0.15405215322971344, + 0.2296278476715088 + ], + "test_mae": [ + 0.14875350892543793, + 0.22720274329185486 + ], + "test_mae_oracle": [ + 0.14875350892543793, + 0.22720274329185486 + ] +} \ No newline at end of file diff --git a/runs/rec_rrog_transformer_full_sig0.0_K1_none_T1_ns3_trace_s0.json b/runs/rec_rrog_transformer_full_sig0.0_K1_none_T1_ns3_trace_s0.json new file mode 100644 index 0000000..629be7d --- /dev/null +++ b/runs/rec_rrog_transformer_full_sig0.0_K1_none_T1_ns3_trace_s0.json @@ -0,0 +1,47 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_rrog_transformer_full_sig0.0_K1_none_T1_ns3_trace_s0", + "grad_mode": "full", + "sigma": 0.0, + "K": 1, + "select": "none", + "T": 1, + "n_sup": 3, + "hidden": 64, + "agg_layers": 5, + "compute_layers": 2, + "view": "transformer", + "epochs": 200, + "lr": 0.001, + "bs": 256, + "lam_q": 1.0, + "act": false, + "halt_max_steps": 8, + "halt_norm_threshold": 0.3, + "halt_temp": 0.1, + "halt_target": "soft", + "halt_exploration_prob": 0.1, + "loss_mode": "trace", + "seed": 0, + "device": "cuda:0", + "sec": 210.2, + "dev": "cuda:0", + "arch": "rrog_once_agg_node_compute", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 180, + "val_mae": [ + 0.09927801787853241, + 0.20996834337711334 + ], + "test_mae": [ + 0.1036745011806488, + 0.2231702208518982 + ], + "test_mae_oracle": [ + 0.1036745011806488, + 0.2231702208518982 + ] +} \ No newline at end of file diff --git a/runs/rec_sig0.0_K1_bestq_T3_ns3_s0.json b/runs/rec_sig0.0_K1_bestq_T3_ns3_s0.json new file mode 100644 index 0000000..d983501 --- /dev/null +++ b/runs/rec_sig0.0_K1_bestq_T3_ns3_s0.json @@ -0,0 +1,34 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_sig0.0_K1_bestq_T3_ns3_s0", + "sigma": 0.0, + "K": 1, + "select": "bestq", + "T": 3, + "n_sup": 3, + "hidden": 128, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "seed": 0, + "sec": 210.1, + "dev": "cuda", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 140, + "val_mae": [ + 0.14077112078666687, + 0.18784108757972717 + ], + "test_mae": [ + 0.1506122499704361, + 0.19844625890254974 + ], + "test_mae_oracle": [ + 0.1506122499704361, + 0.19844625890254974 + ] +} \ No newline at end of file diff --git a/runs/rec_sig0.1_K8_bestq_T3_ns3_s0.json b/runs/rec_sig0.1_K8_bestq_T3_ns3_s0.json new file mode 100644 index 0000000..bb6420e --- /dev/null +++ b/runs/rec_sig0.1_K8_bestq_T3_ns3_s0.json @@ -0,0 +1,34 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_sig0.1_K8_bestq_T3_ns3_s0", + "sigma": 0.1, + "K": 8, + "select": "bestq", + "T": 3, + "n_sup": 3, + "hidden": 128, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "seed": 0, + "sec": 211.1, + "dev": "cuda", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 180, + "val_mae": [ + 0.1527794450521469, + 0.26431822776794434 + ], + "test_mae": [ + 0.15733911097049713, + 0.2645413875579834 + ], + "test_mae_oracle": [ + 0.08885522931814194, + 0.1291976273059845 + ] +} \ No newline at end of file diff --git a/runs/rec_sig0.1_K8_none_T3_ns3_s0.json b/runs/rec_sig0.1_K8_none_T3_ns3_s0.json new file mode 100644 index 0000000..76ceee5 --- /dev/null +++ b/runs/rec_sig0.1_K8_none_T3_ns3_s0.json @@ -0,0 +1,34 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_sig0.1_K8_none_T3_ns3_s0", + "sigma": 0.1, + "K": 8, + "select": "none", + "T": 3, + "n_sup": 3, + "hidden": 128, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "seed": 0, + "sec": 212.0, + "dev": "cuda", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 140, + "val_mae": [ + 0.1645255982875824, + 0.22213539481163025 + ], + "test_mae": [ + 0.16389606893062592, + 0.23174288868904114 + ], + "test_mae_oracle": [ + 0.09854131191968918, + 0.120295949280262 + ] +} \ No newline at end of file diff --git a/runs/rec_sig0.2_K16_bestq_T3_ns3_s0.json b/runs/rec_sig0.2_K16_bestq_T3_ns3_s0.json new file mode 100644 index 0000000..b59684f --- /dev/null +++ b/runs/rec_sig0.2_K16_bestq_T3_ns3_s0.json @@ -0,0 +1,34 @@ +{ + "dataset": "ZINC-cycle56", + "tag": "rec_sig0.2_K16_bestq_T3_ns3_s0", + "sigma": 0.2, + "K": 16, + "select": "bestq", + "T": 3, + "n_sup": 3, + "hidden": 128, + "epochs": 200, + "lr": 0.001, + "bs": 128, + "lam_q": 1.0, + "seed": 0, + "sec": 207.9, + "dev": "cuda", + "y_std_raw": [ + 0.7805301547050476, + 0.9526597261428833 + ], + "ep": 60, + "val_mae": [ + 0.19973090291023254, + 0.3134014308452606 + ], + "test_mae": [ + 0.20950639247894287, + 0.30515405535697937 + ], + "test_mae_oracle": [ + 0.1255389302968979, + 0.1383717805147171 + ] +} \ No newline at end of file diff --git a/runs/rec_sweep.log b/runs/rec_sweep.log new file mode 100644 index 0000000..850f373 --- /dev/null +++ b/runs/rec_sweep.log @@ -0,0 +1,54 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T09:56:20-05:00 +===== --sigma 0 --K 1 --select bestq ===== +ep20 val_mae=[0.343, 0.416] +ep40 val_mae=[0.271, 0.321] +ep60 val_mae=[0.192, 0.234] +ep80 val_mae=[0.203, 0.245] +ep100 val_mae=[0.289, 0.382] +ep120 val_mae=[0.189, 0.235] +ep140 val_mae=[0.141, 0.188] +ep160 val_mae=[0.131, 0.286] +ep180 val_mae=[0.178, 0.295] +ep200 val_mae=[0.132, 0.244] +[rec_sig0.0_K1_bestq_T3_ns3_s0] test_mae=[0.151, 0.198] oracle@K=[0.151, 0.198] @ep140 (210.1s) + wrote /home/yurenh2/rrog/runs/rec_sig0.0_K1_bestq_T3_ns3_s0.json +===== --sigma 0.1 --K 8 --select none ===== +ep20 val_mae=[0.343, 0.401] +ep40 val_mae=[0.273, 0.304] +ep60 val_mae=[0.324, 0.339] +ep80 val_mae=[0.207, 0.409] +ep100 val_mae=[0.172, 0.261] +ep120 val_mae=[0.199, 0.271] +ep140 val_mae=[0.165, 0.222] +ep160 val_mae=[0.173, 0.258] +ep180 val_mae=[0.204, 0.33] +ep200 val_mae=[0.206, 0.333] +[rec_sig0.1_K8_none_T3_ns3_s0] test_mae=[0.164, 0.232] oracle@K=[0.099, 0.12] @ep140 (212.0s) + wrote /home/yurenh2/rrog/runs/rec_sig0.1_K8_none_T3_ns3_s0.json +===== --sigma 0.1 --K 8 --select bestq ===== +ep20 val_mae=[0.342, 0.419] +ep40 val_mae=[0.276, 0.34] +ep60 val_mae=[0.205, 0.282] +ep80 val_mae=[0.181, 0.507] +ep100 val_mae=[0.198, 0.588] +ep120 val_mae=[0.235, 0.542] +ep140 val_mae=[0.219, 0.428] +ep160 val_mae=[0.16, 0.283] +ep180 val_mae=[0.153, 0.264] +ep200 val_mae=[0.147, 0.291] +[rec_sig0.1_K8_bestq_T3_ns3_s0] test_mae=[0.157, 0.265] oracle@K=[0.089, 0.129] @ep180 (211.1s) + wrote /home/yurenh2/rrog/runs/rec_sig0.1_K8_bestq_T3_ns3_s0.json +===== --sigma 0.2 --K 16 --select bestq ===== +ep20 val_mae=[0.32, 0.384] +ep40 val_mae=[0.295, 0.322] +ep60 val_mae=[0.2, 0.313] +ep80 val_mae=[0.2, 0.331] +ep100 val_mae=[0.332, 0.522] +ep120 val_mae=[0.202, 0.374] +ep140 val_mae=[0.261, 0.339] +ep160 val_mae=[0.261, 0.404] +ep180 val_mae=[0.177, 0.339] +ep200 val_mae=[0.24, 0.356] +[rec_sig0.2_K16_bestq_T3_ns3_s0] test_mae=[0.21, 0.305] oracle@K=[0.126, 0.138] @ep60 (207.9s) + wrote /home/yurenh2/rrog/runs/rec_sig0.2_K16_bestq_T3_ns3_s0.json +done=2026-06-16T10:11:08-05:00 diff --git a/runs/rrog_attn_T1_T3_e80_seed0_20260617_113532.log b/runs/rrog_attn_T1_T3_e80_seed0_20260617_113532.log new file mode 100644 index 0000000..bf7e5c4 --- /dev/null +++ b/runs/rrog_attn_T1_T3_e80_seed0_20260617_113532.log @@ -0,0 +1,8 @@ +===== attn T=1 ===== +ep20 solve_rate=0.000 mean_conflicts=50.67 +ep40 solve_rate=0.000 mean_conflicts=45.77 +ep60 solve_rate=0.000 mean_conflicts=34.93 +ep80 solve_rate=0.000 mean_conflicts=32.84 +[color_rrog_attn_gin_full_none_n50_k3_p0.2_T1_ns3_s0] best solve_rate=0.0 @ep20 (96.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_rrog_attn_gin_full_none_n50_k3_p0.2_T1_ns3_s0.pt +===== attn T=3 ===== diff --git a/runs/rrog_color_T1_seed0_20260617_113041.log b/runs/rrog_color_T1_seed0_20260617_113041.log new file mode 100644 index 0000000..e275e3e --- /dev/null +++ b/runs/rrog_color_T1_seed0_20260617_113041.log @@ -0,0 +1,10 @@ +ep20 solve_rate=0.000 mean_conflicts=61.33 +ep40 solve_rate=0.000 mean_conflicts=50.18 +ep60 solve_rate=0.000 mean_conflicts=38.73 +ep80 solve_rate=0.000 mean_conflicts=36.58 +ep100 solve_rate=0.000 mean_conflicts=36.11 +ep120 solve_rate=0.000 mean_conflicts=35.95 +ep140 solve_rate=0.000 mean_conflicts=35.86 +ep150 solve_rate=0.000 mean_conflicts=35.80 +[color_rrog_gin_full_none_n50_k3_p0.2_T1_ns3_s0] best solve_rate=0.0 @ep20 (127.8s) + wrote /home/yurenh2/rrog/runs/ckpt_color_rrog_gin_full_none_n50_k3_p0.2_T1_ns3_s0.pt diff --git a/runs/rrog_color_sweep_20260617_112632.log b/runs/rrog_color_sweep_20260617_112632.log new file mode 100644 index 0000000..b3cf032 --- /dev/null +++ b/runs/rrog_color_sweep_20260617_112632.log @@ -0,0 +1,2 @@ +host=timan1.cs.illinois.edu gpu=? start=2026-06-17T11:26:32-05:00 +===== train full ===== diff --git a/runs/rrog_gcn_node_agg4_T3_e150_seed0_20260617_114425.log b/runs/rrog_gcn_node_agg4_T3_e150_seed0_20260617_114425.log new file mode 100644 index 0000000..4bc2865 --- /dev/null +++ b/runs/rrog_gcn_node_agg4_T3_e150_seed0_20260617_114425.log @@ -0,0 +1,5 @@ +ep20 solve_rate=0.000 mean_conflicts=59.14 +ep40 solve_rate=0.000 mean_conflicts=93.71 +ep60 solve_rate=0.000 mean_conflicts=41.06 +ep80 solve_rate=0.000 mean_conflicts=29.80 +ep100 solve_rate=0.000 mean_conflicts=31.36 diff --git a/runs/rrog_node_agg4_T1_e80_seed0_20260617_113927.log b/runs/rrog_node_agg4_T1_e80_seed0_20260617_113927.log new file mode 100644 index 0000000..0dda954 --- /dev/null +++ b/runs/rrog_node_agg4_T1_e80_seed0_20260617_113927.log @@ -0,0 +1,6 @@ +ep20 solve_rate=0.000 mean_conflicts=58.17 +ep40 solve_rate=0.000 mean_conflicts=21.81 +ep60 solve_rate=0.000 mean_conflicts=17.77 +ep80 solve_rate=0.000 mean_conflicts=16.47 +[color_rrog_node_gin_full_none_n50_k3_p0.2_T1_ns3_s0] best solve_rate=0.0 @ep20 (54.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_rrog_node_gin_full_none_n50_k3_p0.2_T1_ns3_s0.pt diff --git a/runs/rrog_rec_T0_T3_e40_seed0_20260617_114919.log b/runs/rrog_rec_T0_T3_e40_seed0_20260617_114919.log new file mode 100644 index 0000000..c763eae --- /dev/null +++ b/runs/rrog_rec_T0_T3_e40_seed0_20260617_114919.log @@ -0,0 +1,10 @@ +===== rec T=0 ===== +ep20 val_mae=[0.537, 0.59] +ep40 val_mae=[0.532, 0.57] +[rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0] test_mae=[0.514, 0.561] oracle@K=[0.514, 0.561] @ep40 (12.6s) + wrote /home/yurenh2/rrog/runs/ckpt_rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0.pt +===== rec T=3 ===== +ep20 val_mae=[0.34, 0.365] +ep40 val_mae=[0.211, 0.283] +[rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0] test_mae=[0.206, 0.284] oracle@K=[0.206, 0.284] @ep40 (22.6s) + wrote /home/yurenh2/rrog/runs/ckpt_rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0.pt diff --git a/runs/rrog_rec_T1_e40_seed0_20260617_115020.log b/runs/rrog_rec_T1_e40_seed0_20260617_115020.log new file mode 100644 index 0000000..26fdead --- /dev/null +++ b/runs/rrog_rec_T1_e40_seed0_20260617_115020.log @@ -0,0 +1,4 @@ +ep20 val_mae=[0.339, 0.445] +ep40 val_mae=[0.209, 0.279] +[rec_rrog_full_sig0.0_K1_bestq_T1_ns3_s0] test_mae=[0.213, 0.3] oracle@K=[0.213, 0.3] @ep40 (21.2s) + wrote /home/yurenh2/rrog/runs/ckpt_rec_rrog_full_sig0.0_K1_bestq_T1_ns3_s0.pt diff --git a/runs/rrog_trm_gnn_perf_20260617_112714.log b/runs/rrog_trm_gnn_perf_20260617_112714.log new file mode 100644 index 0000000..ecbdbf4 --- /dev/null +++ b/runs/rrog_trm_gnn_perf_20260617_112714.log @@ -0,0 +1,13 @@ +host=timan1.cs.illinois.edu gpu=? start=2026-06-17T11:27:14-05:00 +===== train full ===== +ep20 solve_rate=0.000 mean_conflicts=66.64 +ep40 solve_rate=0.000 mean_conflicts=50.38 +ep60 solve_rate=0.000 mean_conflicts=39.63 +ep80 solve_rate=0.000 mean_conflicts=37.37 +ep100 solve_rate=0.000 mean_conflicts=36.56 +ep120 solve_rate=0.000 mean_conflicts=36.30 +ep140 solve_rate=0.000 mean_conflicts=36.23 +ep150 solve_rate=0.000 mean_conflicts=36.25 +[color_rrog_gin_full_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.0 @ep20 (141.4s) + wrote /home/yurenh2/rrog/runs/ckpt_color_rrog_gin_full_none_n50_k3_p0.2_T3_ns3_s0.pt +===== train 1step ===== diff --git a/runs/rrog_viewonly_agg4_T0_e150_seed0_20260617_114134.log b/runs/rrog_viewonly_agg4_T0_e150_seed0_20260617_114134.log new file mode 100644 index 0000000..333c591 --- /dev/null +++ b/runs/rrog_viewonly_agg4_T0_e150_seed0_20260617_114134.log @@ -0,0 +1,10 @@ +ep20 solve_rate=0.000 mean_conflicts=81.17 +ep40 solve_rate=0.000 mean_conflicts=18.96 +ep60 solve_rate=0.000 mean_conflicts=16.98 +ep80 solve_rate=0.000 mean_conflicts=15.84 +ep100 solve_rate=0.000 mean_conflicts=15.50 +ep120 solve_rate=0.000 mean_conflicts=15.44 +ep140 solve_rate=0.000 mean_conflicts=15.69 +ep150 solve_rate=0.000 mean_conflicts=15.68 +[color_rrog_node_gin_full_none_n50_k3_p0.2_T0_ns3_s0] best solve_rate=0.0 @ep20 (69.4s) + wrote /home/yurenh2/rrog/runs/ckpt_color_rrog_node_gin_full_none_n50_k3_p0.2_T0_ns3_s0.pt diff --git a/runs/rrog_viewonly_gcn_agg4_T0_e150_seed0_20260617_114257.log b/runs/rrog_viewonly_gcn_agg4_T0_e150_seed0_20260617_114257.log new file mode 100644 index 0000000..b28b107 --- /dev/null +++ b/runs/rrog_viewonly_gcn_agg4_T0_e150_seed0_20260617_114257.log @@ -0,0 +1,10 @@ +ep20 solve_rate=0.000 mean_conflicts=67.89 +ep40 solve_rate=0.000 mean_conflicts=46.29 +ep60 solve_rate=0.000 mean_conflicts=58.42 +ep80 solve_rate=0.000 mean_conflicts=51.36 +ep100 solve_rate=0.000 mean_conflicts=32.18 +ep120 solve_rate=0.007 mean_conflicts=20.98 +ep140 solve_rate=0.003 mean_conflicts=18.32 +ep150 solve_rate=0.003 mean_conflicts=18.08 +[color_rrog_node_gcn_full_none_n50_k3_p0.2_T0_ns3_s0] best solve_rate=0.0067 @ep120 (72.9s) + wrote /home/yurenh2/rrog/runs/ckpt_color_rrog_node_gcn_full_none_n50_k3_p0.2_T0_ns3_s0.pt diff --git a/runs/seeds_sweep.log b/runs/seeds_sweep.log new file mode 100644 index 0000000..7e1b08f --- /dev/null +++ b/runs/seeds_sweep.log @@ -0,0 +1,234 @@ +host=timan1.cs.illinois.edu gpu=0 start=2026-06-16T11:50:28-05:00 +===== seed=0 full none ===== +ep20 solve_rate=0.000 mean_conflicts=114.06 +ep40 solve_rate=0.163 mean_conflicts=61.27 +ep60 solve_rate=0.410 mean_conflicts=17.81 +ep80 solve_rate=0.610 mean_conflicts=4.32 +ep100 solve_rate=0.440 mean_conflicts=16.00 +ep120 solve_rate=0.287 mean_conflicts=19.54 +ep140 solve_rate=0.090 mean_conflicts=59.83 +ep150 solve_rate=0.063 mean_conflicts=70.46 +[color_full_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.61 mean_conflicts=4.323 @ep80 (155.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_n50_k3_p0.2_T3_ns3_s0.pt +[full] LE n=300 fail_rate=0.39 | lambda1 SOLVED mean -0.3206 (n=183) | UNSOLVED mean +0.0485 (n=117) | sep=+0.3692 | AUROC(fail|lambda1)=0.919 | mean_lambda1=-0.1767 +[pe=none s0] deterministic solve_rate = 0.627 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.900 0.773 0.640 0.595 0.883 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s0.json +===== seed=0 full rwse ===== +ep20 solve_rate=0.000 mean_conflicts=51.22 +ep40 solve_rate=0.083 mean_conflicts=55.16 +ep60 solve_rate=0.203 mean_conflicts=58.38 +ep80 solve_rate=0.350 mean_conflicts=37.23 +ep100 solve_rate=0.383 mean_conflicts=31.48 +ep120 solve_rate=0.203 mean_conflicts=53.56 +ep140 solve_rate=0.273 mean_conflicts=37.79 +ep150 solve_rate=0.280 mean_conflicts=36.98 +[color_full_rwse_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.3833 mean_conflicts=31.483 @ep100 (153.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_rwse_n50_k3_p0.2_T3_ns3_s0.pt +[full] LE n=300 fail_rate=0.62 | lambda1 SOLVED mean -0.1834 (n=115) | UNSOLVED mean +0.0100 (n=185) | sep=+0.1934 | AUROC(fail|lambda1)=0.817 | mean_lambda1=-0.0641 +[pe=rwse s0] deterministic solve_rate = 0.407 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.740 0.587 0.493 0.426 0.808 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s0.json +===== seed=0 1step none ===== +ep20 solve_rate=0.000 mean_conflicts=44.63 +ep40 solve_rate=0.123 mean_conflicts=19.01 +ep60 solve_rate=0.200 mean_conflicts=18.33 +ep80 solve_rate=0.067 mean_conflicts=42.81 +ep100 solve_rate=0.027 mean_conflicts=42.48 +ep120 solve_rate=0.087 mean_conflicts=23.53 +ep140 solve_rate=0.100 mean_conflicts=10.46 +ep150 solve_rate=0.127 mean_conflicts=18.32 +[color_1step_none_n50_k3_p0.2_T3_ns3_s0] best solve_rate=0.2 mean_conflicts=18.333 @ep60 (127.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_1step_none_n50_k3_p0.2_T3_ns3_s0.pt +[1step] LE n=300 fail_rate=0.80 | lambda1 SOLVED mean -0.2978 (n=60) | UNSOLVED mean -0.1209 (n=240) | sep=+0.1769 | AUROC(fail|lambda1)=0.770 | mean_lambda1=-0.1563 +===== seed=1 full none ===== +ep20 solve_rate=0.000 mean_conflicts=76.94 +ep40 solve_rate=0.070 mean_conflicts=41.69 +ep60 solve_rate=0.207 mean_conflicts=33.02 +ep80 solve_rate=0.453 mean_conflicts=11.75 +ep100 solve_rate=0.203 mean_conflicts=21.24 +ep120 solve_rate=0.163 mean_conflicts=19.60 +ep140 solve_rate=0.067 mean_conflicts=41.63 +ep150 solve_rate=0.027 mean_conflicts=50.77 +[color_full_none_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.4533 mean_conflicts=11.753 @ep80 (151.0s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_n50_k3_p0.2_T3_ns3_s1.pt +[full] LE n=300 fail_rate=0.55 | lambda1 SOLVED mean -0.3182 (n=136) | UNSOLVED mean -0.0426 (n=164) | sep=+0.2757 | AUROC(fail|lambda1)=0.864 | mean_lambda1=-0.1675 +[pe=none s1] deterministic solve_rate = 0.480 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.740 0.593 0.440 0.456 0.869 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s1.json +===== seed=1 full rwse ===== +ep20 solve_rate=0.000 mean_conflicts=115.59 +ep40 solve_rate=0.100 mean_conflicts=91.86 +ep60 solve_rate=0.327 mean_conflicts=34.60 +ep80 solve_rate=0.097 mean_conflicts=88.34 +ep100 solve_rate=0.140 mean_conflicts=56.41 +ep120 solve_rate=0.500 mean_conflicts=16.20 +ep140 solve_rate=0.537 mean_conflicts=13.68 +ep150 solve_rate=0.500 mean_conflicts=16.04 +[color_full_rwse_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.5367 mean_conflicts=13.68 @ep140 (152.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_rwse_n50_k3_p0.2_T3_ns3_s1.pt +[full] LE n=300 fail_rate=0.46 | lambda1 SOLVED mean +0.0219 (n=161) | UNSOLVED mean +0.1773 (n=139) | sep=+0.1554 | AUROC(fail|lambda1)=0.774 | mean_lambda1=+0.0939 +[pe=rwse s1] deterministic solve_rate = 0.547 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.947 0.727 0.553 0.507 0.814 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s1.json +===== seed=1 1step none ===== +ep20 solve_rate=0.000 mean_conflicts=47.30 +ep40 solve_rate=0.157 mean_conflicts=34.06 +ep60 solve_rate=0.297 mean_conflicts=7.36 +ep80 solve_rate=0.333 mean_conflicts=8.70 +ep100 solve_rate=0.193 mean_conflicts=13.99 +ep120 solve_rate=0.233 mean_conflicts=6.94 +ep140 solve_rate=0.227 mean_conflicts=6.85 +ep150 solve_rate=0.320 mean_conflicts=5.31 +[color_1step_none_n50_k3_p0.2_T3_ns3_s1] best solve_rate=0.3333 mean_conflicts=8.7 @ep80 (123.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_1step_none_n50_k3_p0.2_T3_ns3_s1.pt +[1step] LE n=300 fail_rate=0.67 | lambda1 SOLVED mean -0.2773 (n=100) | UNSOLVED mean +0.0189 (n=200) | sep=+0.2963 | AUROC(fail|lambda1)=0.846 | mean_lambda1=-0.0798 +===== seed=2 full none ===== +ep20 solve_rate=0.000 mean_conflicts=137.74 +ep40 solve_rate=0.087 mean_conflicts=44.48 +ep60 solve_rate=0.140 mean_conflicts=42.89 +ep80 solve_rate=0.413 mean_conflicts=16.23 +ep100 solve_rate=0.123 mean_conflicts=60.71 +ep120 solve_rate=0.027 mean_conflicts=58.64 +ep140 solve_rate=0.017 mean_conflicts=79.05 +ep150 solve_rate=0.013 mean_conflicts=83.54 +[color_full_none_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.4133 mean_conflicts=16.23 @ep80 (154.4s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_n50_k3_p0.2_T3_ns3_s2.pt +[full] LE n=300 fail_rate=0.59 | lambda1 SOLVED mean -0.2913 (n=124) | UNSOLVED mean -0.0796 (n=176) | sep=+0.2117 | AUROC(fail|lambda1)=0.830 | mean_lambda1=-0.1671 +[pe=none s2] deterministic solve_rate = 0.447 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.773 0.620 0.467 0.435 0.821 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s2.json +===== seed=2 full rwse ===== +ep20 solve_rate=0.000 mean_conflicts=89.84 +ep40 solve_rate=0.110 mean_conflicts=36.78 +ep60 solve_rate=0.400 mean_conflicts=9.39 +ep80 solve_rate=0.560 mean_conflicts=3.40 +ep100 solve_rate=0.463 mean_conflicts=23.90 +ep120 solve_rate=0.550 mean_conflicts=16.37 +ep140 solve_rate=0.557 mean_conflicts=23.72 +ep150 solve_rate=0.510 mean_conflicts=34.19 +[color_full_rwse_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.56 mean_conflicts=3.4 @ep80 (151.8s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_rwse_n50_k3_p0.2_T3_ns3_s2.pt +[full] LE n=300 fail_rate=0.44 | lambda1 SOLVED mean -0.2328 (n=168) | UNSOLVED mean +0.0707 (n=132) | sep=+0.3034 | AUROC(fail|lambda1)=0.883 | mean_lambda1=-0.0993 +[pe=rwse s2] deterministic solve_rate = 0.600 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.893 0.787 0.573 0.556 0.873 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s2.json +===== seed=2 1step none ===== +ep20 solve_rate=0.000 mean_conflicts=38.00 +ep40 solve_rate=0.153 mean_conflicts=18.17 +ep60 solve_rate=0.327 mean_conflicts=7.32 +ep80 solve_rate=0.320 mean_conflicts=5.31 +ep100 solve_rate=0.357 mean_conflicts=4.67 +ep120 solve_rate=0.293 mean_conflicts=7.30 +ep140 solve_rate=0.273 mean_conflicts=7.96 +ep150 solve_rate=0.227 mean_conflicts=10.33 +[color_1step_none_n50_k3_p0.2_T3_ns3_s2] best solve_rate=0.3567 mean_conflicts=4.67 @ep100 (131.6s) + wrote /home/yurenh2/rrog/runs/ckpt_color_1step_none_n50_k3_p0.2_T3_ns3_s2.pt +[1step] LE n=300 fail_rate=0.64 | lambda1 SOLVED mean -0.2153 (n=107) | UNSOLVED mean +0.0916 (n=193) | sep=+0.3069 | AUROC(fail|lambda1)=0.867 | mean_lambda1=-0.0179 +===== seed=3 full none ===== +ep20 solve_rate=0.000 mean_conflicts=62.81 +ep40 solve_rate=0.207 mean_conflicts=33.51 +ep60 solve_rate=0.460 mean_conflicts=15.68 +ep80 solve_rate=0.033 mean_conflicts=114.30 +ep100 solve_rate=0.000 mean_conflicts=82.87 +ep120 solve_rate=0.000 mean_conflicts=85.01 +ep140 solve_rate=0.000 mean_conflicts=77.61 +ep150 solve_rate=0.000 mean_conflicts=79.58 +[color_full_none_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.46 mean_conflicts=15.68 @ep60 (151.6s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_n50_k3_p0.2_T3_ns3_s3.pt +[full] LE n=300 fail_rate=0.54 | lambda1 SOLVED mean -0.4216 (n=138) | UNSOLVED mean -0.0826 (n=162) | sep=+0.3390 | AUROC(fail|lambda1)=0.886 | mean_lambda1=-0.2385 +[pe=none s3] deterministic solve_rate = 0.493 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.733 0.587 0.493 0.472 0.856 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s3.json +===== seed=3 full rwse ===== +ep20 solve_rate=0.000 mean_conflicts=139.52 +ep40 solve_rate=0.043 mean_conflicts=135.26 +ep60 solve_rate=0.313 mean_conflicts=32.37 +ep80 solve_rate=0.370 mean_conflicts=14.78 +ep100 solve_rate=0.490 mean_conflicts=12.46 +ep120 solve_rate=0.067 mean_conflicts=89.87 +ep140 solve_rate=0.137 mean_conflicts=53.29 +ep150 solve_rate=0.127 mean_conflicts=46.23 +[color_full_rwse_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.49 mean_conflicts=12.46 @ep100 (152.1s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_rwse_n50_k3_p0.2_T3_ns3_s3.pt +[full] LE n=300 fail_rate=0.51 | lambda1 SOLVED mean -0.0438 (n=147) | UNSOLVED mean +0.1618 (n=153) | sep=+0.2056 | AUROC(fail|lambda1)=0.830 | mean_lambda1=+0.0610 +[pe=rwse s3] deterministic solve_rate = 0.507 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.893 0.727 0.473 0.497 0.823 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s3.json +===== seed=3 1step none ===== +ep20 solve_rate=0.000 mean_conflicts=54.09 +ep40 solve_rate=0.103 mean_conflicts=17.25 +ep60 solve_rate=0.187 mean_conflicts=28.48 +ep80 solve_rate=0.120 mean_conflicts=29.85 +ep100 solve_rate=0.200 mean_conflicts=16.34 +ep120 solve_rate=0.337 mean_conflicts=7.23 +ep140 solve_rate=0.157 mean_conflicts=16.67 +ep150 solve_rate=0.087 mean_conflicts=19.67 +[color_1step_none_n50_k3_p0.2_T3_ns3_s3] best solve_rate=0.3367 mean_conflicts=7.227 @ep120 (124.3s) + wrote /home/yurenh2/rrog/runs/ckpt_color_1step_none_n50_k3_p0.2_T3_ns3_s3.pt +[1step] LE n=300 fail_rate=0.66 | lambda1 SOLVED mean -0.0124 (n=101) | UNSOLVED mean +0.1694 (n=199) | sep=+0.1818 | AUROC(fail|lambda1)=0.786 | mean_lambda1=+0.1082 +===== seed=4 full none ===== +ep20 solve_rate=0.000 mean_conflicts=67.14 +ep40 solve_rate=0.200 mean_conflicts=24.37 +ep60 solve_rate=0.347 mean_conflicts=27.20 +ep80 solve_rate=0.127 mean_conflicts=41.29 +ep100 solve_rate=0.180 mean_conflicts=35.82 +ep120 solve_rate=0.073 mean_conflicts=66.69 +ep140 solve_rate=0.070 mean_conflicts=74.02 +ep150 solve_rate=0.073 mean_conflicts=81.13 +[color_full_none_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.3467 mean_conflicts=27.197 @ep60 (149.8s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_none_n50_k3_p0.2_T3_ns3_s4.pt +[full] LE n=300 fail_rate=0.65 | lambda1 SOLVED mean -0.4008 (n=104) | UNSOLVED mean -0.1440 (n=196) | sep=+0.2567 | AUROC(fail|lambda1)=0.842 | mean_lambda1=-0.2330 +[pe=none s4] deterministic solve_rate = 0.353 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.547 0.427 0.373 0.358 0.835 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_none_n50_k3_p0.2_T3_ns3_s4.json +===== seed=4 full rwse ===== +ep20 solve_rate=0.000 mean_conflicts=56.06 +ep40 solve_rate=0.050 mean_conflicts=55.24 +ep60 solve_rate=0.303 mean_conflicts=39.93 +ep80 solve_rate=0.357 mean_conflicts=15.34 +ep100 solve_rate=0.547 mean_conflicts=6.19 +ep120 solve_rate=0.440 mean_conflicts=18.82 +ep140 solve_rate=0.240 mean_conflicts=41.55 +ep150 solve_rate=0.233 mean_conflicts=46.02 +[color_full_rwse_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.5467 mean_conflicts=6.193 @ep100 (154.2s) + wrote /home/yurenh2/rrog/runs/ckpt_color_full_rwse_n50_k3_p0.2_T3_ns3_s4.pt +[full] LE n=300 fail_rate=0.45 | lambda1 SOLVED mean -0.1742 (n=164) | UNSOLVED mean +0.1084 (n=136) | sep=+0.2827 | AUROC(fail|lambda1)=0.880 | mean_lambda1=-0.0461 +[pe=rwse s4] deterministic solve_rate = 0.547 (n=150, K=16) + sigma pass@K lam-sel random perRoll AUROC(s|-lam) + 0.2 0.940 0.853 0.493 0.557 0.868 + wrote /home/yurenh2/rrog/runs/ptrm_color_full_rwse_n50_k3_p0.2_T3_ns3_s4.json +===== seed=4 1step none ===== +ep20 solve_rate=0.000 mean_conflicts=63.11 +ep40 solve_rate=0.187 mean_conflicts=11.62 +ep60 solve_rate=0.237 mean_conflicts=22.39 +ep80 solve_rate=0.200 mean_conflicts=24.78 +ep100 solve_rate=0.183 mean_conflicts=15.49 +ep120 solve_rate=0.207 mean_conflicts=12.25 +ep140 solve_rate=0.093 mean_conflicts=21.66 +ep150 solve_rate=0.067 mean_conflicts=30.98 +[color_1step_none_n50_k3_p0.2_T3_ns3_s4] best solve_rate=0.2367 mean_conflicts=22.393 @ep60 (120.8s) + wrote /home/yurenh2/rrog/runs/ckpt_color_1step_none_n50_k3_p0.2_T3_ns3_s4.pt +[1step] LE n=300 fail_rate=0.76 | lambda1 SOLVED mean -0.2996 (n=71) | UNSOLVED mean -0.0523 (n=229) | sep=+0.2473 | AUROC(fail|lambda1)=0.835 | mean_lambda1=-0.1108 +===== AGGREGATE ===== +=== best solve_rate (deterministic, EMA) === + ('1step', 'none'): 0.293±0.062 (n=5) + ('full', 'none'): 0.457±0.087 (n=5) + ('full', 'rwse'): 0.503±0.064 (n=5) +=== LE AUROC(fail|lambda1) === + ('1step', 'none'): 0.821±0.036 (n=5) + ('full', 'none'): 0.868±0.032 (n=5) + ('full', 'rwse'): 0.837±0.041 (n=5) +=== PTRM sigma=0.2 === + ('full', 'none'): det 0.480±0.088 (n=5) | pass@K 0.739±0.113 (n=5) | lambda-sel 0.600±0.110 (n=5) | AUROC 0.853±0.023 (n=5) + ('full', 'rwse'): det 0.521±0.065 (n=5) | pass@K 0.883±0.075 (n=5) | lambda-sel 0.736±0.088 (n=5) | AUROC 0.837±0.028 (n=5) +done=2026-06-16T12:41:20-05:00 diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0_test.json b/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0_test.json new file mode 100644 index 0000000..e5bc803 --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0_test.json @@ -0,0 +1,63 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_bestq_T0_ns3_s0.pt", + "split": "test", + "train_T": 0, + "train_n_sup": 3, + "eval_n_sup": 3, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 3, + "mae": [ + 0.5142010450363159, + 0.5612384080886841 + ], + "mae_sum": 1.075439453125 + }, + { + "T_eval": 1, + "n_sup_eval": 3, + "mae": [ + 0.5142010450363159, + 0.5612384080886841 + ], + "mae_sum": 1.075439453125 + }, + { + "T_eval": 2, + "n_sup_eval": 3, + "mae": [ + 0.5142010450363159, + 0.5612384080886841 + ], + "mae_sum": 1.075439453125 + }, + { + "T_eval": 3, + "n_sup_eval": 3, + "mae": [ + 0.5142010450363159, + 0.5612384080886841 + ], + "mae_sum": 1.075439453125 + }, + { + "T_eval": 5, + "n_sup_eval": 3, + "mae": [ + 0.5142010450363159, + 0.5612384080886841 + ], + "mae_sum": 1.075439453125 + }, + { + "T_eval": 8, + "n_sup_eval": 3, + "mae": [ + 0.5142010450363159, + 0.5612384080886841 + ], + "mae_sum": 1.075439453125 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T1_ns3_s0_test.json b/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T1_ns3_s0_test.json new file mode 100644 index 0000000..fd6aa76 --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T1_ns3_s0_test.json @@ -0,0 +1,18 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_bestq_T1_ns3_s0.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 3, + "eval_n_sup": 8, + "rows": [ + { + "T_eval": 1, + "n_sup_eval": 8, + "mae": [ + 0.660330057144165, + 0.6151341795921326 + ], + "mae_sum": 1.2754642367362976 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0_test.json b/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0_test.json new file mode 100644 index 0000000..ae00620 --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0_test.json @@ -0,0 +1,18 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_bestq_T3_ns3_s0.pt", + "split": "test", + "train_T": 3, + "train_n_sup": 3, + "eval_n_sup": 8, + "rows": [ + { + "T_eval": 3, + "n_sup_eval": 8, + "mae": [ + 0.41426005959510803, + 0.6339796185493469 + ], + "mae_sum": 1.048239678144455 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s123_ns2_test.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s123_ns2_test.json new file mode 100644 index 0000000..4e954e1 --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s123_ns2_test.json @@ -0,0 +1,43 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s123.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 2, + "eval_n_sup": 2, + "adaptive": false, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 2, + "adaptive": false, + "avg_steps": 2.0, + "mae": [ + 0.6409543752670288, + 0.6232001185417175 + ], + "mae_sum": 1.2641544938087463 + }, + { + "T_eval": 1, + "n_sup_eval": 2, + "adaptive": false, + "avg_steps": 2.0, + "mae": [ + 0.5365709662437439, + 0.6183863282203674 + ], + "mae_sum": 1.1549572944641113 + }, + { + "T_eval": 2, + "n_sup_eval": 2, + "adaptive": false, + "avg_steps": 2.0, + "mae": [ + 0.5599585771560669, + 0.6114262342453003 + ], + "mae_sum": 1.1713848114013672 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s123_ns2_test_adaptive.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s123_ns2_test_adaptive.json new file mode 100644 index 0000000..0a7e649 --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s123_ns2_test_adaptive.json @@ -0,0 +1,43 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s123.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 2, + "eval_n_sup": 2, + "adaptive": true, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 2, + "adaptive": true, + "avg_steps": 1.998, + "mae": [ + 0.6409543752670288, + 0.6232001185417175 + ], + "mae_sum": 1.2641544938087463 + }, + { + "T_eval": 1, + "n_sup_eval": 2, + "adaptive": true, + "avg_steps": 1.998, + "mae": [ + 0.5365839004516602, + 0.6184093952178955 + ], + "mae_sum": 1.1549932956695557 + }, + { + "T_eval": 2, + "n_sup_eval": 2, + "adaptive": true, + "avg_steps": 1.998, + "mae": [ + 0.5598364472389221, + 0.6113667488098145 + ], + "mae_sum": 1.1712031960487366 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s124_ns2_test.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s124_ns2_test.json new file mode 100644 index 0000000..89e7ac8 --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s124_ns2_test.json @@ -0,0 +1,43 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s124.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 2, + "eval_n_sup": 2, + "adaptive": false, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 2, + "adaptive": false, + "avg_steps": 2.0, + "mae": [ + 0.5493720173835754, + 0.6576622724533081 + ], + "mae_sum": 1.2070342898368835 + }, + { + "T_eval": 1, + "n_sup_eval": 2, + "adaptive": false, + "avg_steps": 2.0, + "mae": [ + 0.5429545640945435, + 0.689839243888855 + ], + "mae_sum": 1.2327938079833984 + }, + { + "T_eval": 2, + "n_sup_eval": 2, + "adaptive": false, + "avg_steps": 2.0, + "mae": [ + 0.5237374305725098, + 0.6338798999786377 + ], + "mae_sum": 1.1576173305511475 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s124_ns2_test_adaptive.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s124_ns2_test_adaptive.json new file mode 100644 index 0000000..34c226f --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s124_ns2_test_adaptive.json @@ -0,0 +1,43 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns2_act2_s124.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 2, + "eval_n_sup": 2, + "adaptive": true, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 2, + "adaptive": true, + "avg_steps": 2.0, + "mae": [ + 0.5493719577789307, + 0.6576622724533081 + ], + "mae_sum": 1.2070342302322388 + }, + { + "T_eval": 1, + "n_sup_eval": 2, + "adaptive": true, + "avg_steps": 2.0, + "mae": [ + 0.5429545640945435, + 0.689839243888855 + ], + "mae_sum": 1.2327938079833984 + }, + { + "T_eval": 2, + "n_sup_eval": 2, + "adaptive": true, + "avg_steps": 2.0, + "mae": [ + 0.5237374901771545, + 0.6338798999786377 + ], + "mae_sum": 1.1576173901557922 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_e200_s0_ns8_test.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_e200_s0_ns8_test.json new file mode 100644 index 0000000..41de52c --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_e200_s0_ns8_test.json @@ -0,0 +1,76 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_e200_s0.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 3, + "eval_n_sup": 8, + "adaptive": false, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.5232908725738525, + 0.7065197229385376 + ], + "mae_sum": 1.2298105955123901 + }, + { + "T_eval": 1, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.35694339871406555, + 0.32599589228630066 + ], + "mae_sum": 0.6829392910003662 + }, + { + "T_eval": 2, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.34778130054473877, + 0.7186371684074402 + ], + "mae_sum": 1.066418468952179 + }, + { + "T_eval": 3, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.31050366163253784, + 0.7275600433349609 + ], + "mae_sum": 1.0380637049674988 + }, + { + "T_eval": 5, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.4022192358970642, + 0.7831410765647888 + ], + "mae_sum": 1.185360312461853 + }, + { + "T_eval": 8, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.4811066687107086, + 0.7915135025978088 + ], + "mae_sum": 1.2726201713085175 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_e200_s0_ns8_test_adaptive.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_e200_s0_ns8_test_adaptive.json new file mode 100644 index 0000000..4f7e847 --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_e200_s0_ns8_test_adaptive.json @@ -0,0 +1,76 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_e200_s0.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 3, + "eval_n_sup": 8, + "adaptive": true, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 7.958, + "mae": [ + 0.5232908725738525, + 0.7065197229385376 + ], + "mae_sum": 1.2298105955123901 + }, + { + "T_eval": 1, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 1.717, + "mae": [ + 0.15837429463863373, + 0.22618268430233002 + ], + "mae_sum": 0.38455697894096375 + }, + { + "T_eval": 2, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 5.774, + "mae": [ + 0.36895444989204407, + 0.7003458738327026 + ], + "mae_sum": 1.0693003237247467 + }, + { + "T_eval": 3, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 5.905, + "mae": [ + 0.32024097442626953, + 0.706447958946228 + ], + "mae_sum": 1.0266889333724976 + }, + { + "T_eval": 5, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 6.277, + "mae": [ + 0.41388994455337524, + 0.7770671248435974 + ], + "mae_sum": 1.1909570693969727 + }, + { + "T_eval": 8, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 6.194, + "mae": [ + 0.4935642182826996, + 0.7972421050071716 + ], + "mae_sum": 1.2908063232898712 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_s0_ns8_test.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_s0_ns8_test.json new file mode 100644 index 0000000..2e96f6d --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_s0_ns8_test.json @@ -0,0 +1,76 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_s0.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 3, + "eval_n_sup": 8, + "adaptive": false, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 8, + "adaptive": 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} + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_s0_ns8_test_adaptive.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_s0_ns8_test_adaptive.json new file mode 100644 index 0000000..fa0a80b --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_s0_ns8_test_adaptive.json @@ -0,0 +1,76 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_binary0.3_s0.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 3, + "eval_n_sup": 8, + "adaptive": true, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 4.759, + "mae": [ + 0.4224133789539337, + 0.40480512380599976 + ], + "mae_sum": 0.8272185027599335 + }, + { + "T_eval": 1, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 3.227, + "mae": [ + 0.2506031394004822, + 0.36558958888053894 + ], + "mae_sum": 0.6161927282810211 + }, + { + "T_eval": 2, + "n_sup_eval": 8, + 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b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0_ns8_test.json new file mode 100644 index 0000000..a790bc9 --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0_ns8_test.json @@ -0,0 +1,76 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 3, + "eval_n_sup": 8, + "adaptive": false, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.38682764768600464, + 0.45607417821884155 + ], + "mae_sum": 0.8429018259048462 + }, + { + "T_eval": 1, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.38368427753448486, + 0.4671553671360016 + ], + "mae_sum": 0.8508396446704865 + }, + { + "T_eval": 2, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.40771323442459106, + 0.5411470532417297 + ], + "mae_sum": 0.9488602876663208 + }, + { + "T_eval": 3, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.4195733070373535, + 0.5811861753463745 + ], + "mae_sum": 1.000759482383728 + }, + { + "T_eval": 5, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.42317721247673035, + 0.5997551083564758 + ], + "mae_sum": 1.0229323208332062 + }, + { + "T_eval": 8, + "n_sup_eval": 8, + "adaptive": false, + "avg_steps": 8.0, + "mae": [ + 0.4142177104949951, + 0.5873055458068848 + ], + "mae_sum": 1.0015232563018799 + } + ] +} \ No newline at end of file diff --git a/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0_ns8_test_adaptive.json b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0_ns8_test_adaptive.json new file mode 100644 index 0000000..c3880ac --- /dev/null +++ b/runs/ttc_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0_ns8_test_adaptive.json @@ -0,0 +1,76 @@ +{ + "ckpt": "runs/ckpt_rec_rrog_full_sig0.0_K1_none_T1_ns3_actfull8_s0.pt", + "split": "test", + "train_T": 1, + "train_n_sup": 3, + "eval_n_sup": 8, + "adaptive": true, + "rows": [ + { + "T_eval": 0, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 6.95, + "mae": [ + 0.38682764768600464, + 0.45607417821884155 + ], + "mae_sum": 0.8429018259048462 + }, + { + "T_eval": 1, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 5.9, + "mae": [ + 0.33561548590660095, + 0.4454902410507202 + ], + "mae_sum": 0.7811057269573212 + }, + { + "T_eval": 2, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 5.285, + "mae": [ + 0.34025096893310547, + 0.45459678769111633 + ], + "mae_sum": 0.7948477566242218 + }, + { + "T_eval": 3, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 5.079, + "mae": [ + 0.3467695415019989, + 0.4739716351032257 + ], + "mae_sum": 0.8207411766052246 + }, + { + "T_eval": 5, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 5.037, + "mae": [ + 0.35314130783081055, + 0.49610018730163574 + ], + "mae_sum": 0.8492414951324463 + }, + { + "T_eval": 8, + "n_sup_eval": 8, + "adaptive": true, + "avg_steps": 5.249, + "mae": [ + 0.358676016330719, + 0.5090946555137634 + ], + "mae_sum": 0.8677706718444824 + } + ] +} \ No newline at end of file diff --git a/runs/zinc_gine_after_ogb.log b/runs/zinc_gine_after_ogb.log new file mode 100644 index 0000000..b39e901 --- /dev/null +++ b/runs/zinc_gine_after_ogb.log @@ -0,0 +1 @@ +[wait] OGB queue pid=2654451 diff --git a/scripts/analyze_ogb_hiv_log.py b/scripts/analyze_ogb_hiv_log.py new file mode 100644 index 0000000..21253fe --- /dev/null +++ b/scripts/analyze_ogb_hiv_log.py @@ -0,0 +1,312 @@ +#!/usr/bin/env python3 +import argparse +import csv +import json +import math +import re +from collections import defaultdict +from pathlib import Path + + +RUN_RE = re.compile( + r"^\[run\]\s+" + r"(?P\S+)\s+view=(?P\S+)\s+compute=(?P\S+)\s+" + r"T=(?P\d+)\s+ns=(?P\d+)" +) +EP_RE = re.compile( + r"^ep(?P\d+)\s+val_(?P\w+)=(?P[-+0-9.eE]+).*" + r"train_steps=(?P[-+0-9.eE]+)" +) + + +def _load_json(path: Path) -> dict | None: + try: + with path.open() as f: + return json.load(f) + except (OSError, json.JSONDecodeError): + return None + + +def _score(rep: dict, split: str) -> float | None: + metric = rep.get("metric") + if not metric: + return None + value = rep.get(split, {}).get(metric) + return None if value is None else float(value) + + +def parse_curves(path: Path): + curves = defaultdict(list) + current = None + with path.open(errors="replace") as f: + for line in f: + line = line.strip() + m = RUN_RE.match(line) + if m: + current = ( + m.group("dataset"), + m.group("view"), + m.group("compute"), + int(m.group("T")), + int(m.group("ns")), + ) + continue + m = EP_RE.match(line) + if current is not None and m: + curves[current].append({ + "ep": int(m.group("ep")), + "metric": m.group("metric"), + "val": float(m.group("val")), + "train_steps": float(m.group("steps")), + }) + return curves + + +def load_runs(runs_dir: Path, dataset: str): + runs = {} + for path in sorted(runs_dir.glob(f"{dataset}_*.json")): + rep = _load_json(path) + if rep is None: + continue + if rep.get("dataset") != dataset: + continue + key = ( + rep.get("view"), + rep.get("compute"), + int(rep.get("T", -1)), + int(rep.get("n_sup", -1)), + int(rep.get("seed", -1)), + ) + runs[key] = rep + return runs + + +def curve_stats(curve: list[dict]) -> dict: + if not curve: + return { + "curve_best_ep": None, + "curve_best_val": None, + "curve_final_ep": None, + "curve_final_val": None, + "final_gap": None, + "late_slope": None, + "range": None, + } + best = max(curve, key=lambda x: x["val"]) + final = curve[-1] + late_slope = None + if len(curve) >= 2: + late_slope = final["val"] - curve[-2]["val"] + vals = [x["val"] for x in curve] + return { + "curve_best_ep": best["ep"], + "curve_best_val": best["val"], + "curve_final_ep": final["ep"], + "curve_final_val": final["val"], + "final_gap": best["val"] - final["val"], + "late_slope": late_slope, + "range": max(vals) - min(vals), + } + + +def labels_for(row: dict, *, val_tol: float, test_tol: float, collapse_gap: float) -> str: + labels = [] + if row["val_delta"] >= -val_tol and row["test_delta"] >= -test_tol: + labels.append("positive_or_tie") + elif row["val_delta"] >= -val_tol and row["test_delta"] < -test_tol: + labels.append("val_up_test_down") + elif row["val_delta"] < -val_tol and row["test_delta"] >= -test_tol: + labels.append("test_up_val_down") + else: + labels.append("val_and_test_down") + + if row["val_delta"] < -0.02: + labels.append("fixed_val_lags_classic") + if row["cand_final_gap"] is not None and row["cand_final_gap"] > collapse_gap: + labels.append("late_collapse") + if ( + row["cand_curve_best_ep"] is not None + and row["cand_curve_final_ep"] is not None + and row["cand_curve_best_ep"] >= row["cand_curve_final_ep"] - 10 + and (row["cand_final_gap"] is None or row["cand_final_gap"] <= 0.01) + ): + labels.append("maybe_undertrained") + return ",".join(labels) + + +def fmt(x, digits=4): + if x is None: + return "" + if isinstance(x, int): + return str(x) + return f"{x:.{digits}f}" + + +def markdown_table(headers, rows): + out = [ + "| " + " | ".join(headers) + " |", + "| " + " | ".join(["---"] * len(headers)) + " |", + ] + out.extend("| " + " | ".join(row) + " |" for row in rows) + return "\n".join(out) + + +def mean(xs): + return sum(xs) / len(xs) if xs else 0.0 + + +def corr(xs, ys): + if len(xs) != len(ys) or len(xs) < 2: + return 0.0 + mx = mean(xs) + my = mean(ys) + den = math.sqrt(sum((x - mx) ** 2 for x in xs) * sum((y - my) ** 2 for y in ys)) + if den == 0: + return 0.0 + return sum((x - mx) * (y - my) for x, y in zip(xs, ys)) / den + + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument("--dataset", default="ogbg-molhiv") + ap.add_argument("--runs-dir", default="runs") + ap.add_argument("--log", default="logs/ogbg-molhiv_0.log") + ap.add_argument("--out-dir", default="analysis") + ap.add_argument("--candidate-compute", default="fixed-rrog") + ap.add_argument("--candidate-T", type=int, default=3) + ap.add_argument("--candidate-n-sup", type=int, default=3) + ap.add_argument("--baseline-compute", default="classic") + ap.add_argument("--baseline-T", type=int, default=0) + ap.add_argument("--baseline-n-sup", type=int, default=1) + ap.add_argument("--seed", type=int, default=0) + ap.add_argument("--val-tol", type=float, default=0.0) + ap.add_argument("--test-tol", type=float, default=0.0) + ap.add_argument("--collapse-gap", type=float, default=0.03) + args = ap.parse_args() + + runs_dir = Path(args.runs_dir) + curves = parse_curves(Path(args.log)) + runs = load_runs(runs_dir, args.dataset) + out_dir = Path(args.out_dir) + out_dir.mkdir(parents=True, exist_ok=True) + + rows = [] + views = sorted({ + view for (view, compute, _t, _ns, seed) in runs + if seed == args.seed and compute == args.baseline_compute + }) + for view in views: + base_key = (view, args.baseline_compute, args.baseline_T, args.baseline_n_sup, args.seed) + cand_key = (view, args.candidate_compute, args.candidate_T, args.candidate_n_sup, args.seed) + base = runs.get(base_key) + cand = runs.get(cand_key) + if base is None or cand is None: + continue + metric = cand["metric"] + base_val = _score(base, "val") + base_test = _score(base, "test") + cand_val = _score(cand, "val") + cand_test = _score(cand, "test") + if None in {base_val, base_test, cand_val, cand_test}: + continue + base_curve = curve_stats(curves.get((args.dataset, view, args.baseline_compute, args.baseline_T, args.baseline_n_sup), [])) + cand_curve = curve_stats(curves.get((args.dataset, view, args.candidate_compute, args.candidate_T, args.candidate_n_sup), [])) + row = { + "view": view, + "metric": metric, + "base_ep": int(base.get("ep") or 0), + "base_val": base_val, + "base_test": base_test, + "cand_ep": int(cand.get("ep") or 0), + "cand_val": cand_val, + "cand_test": cand_test, + "val_delta": cand_val - base_val, + "test_delta": cand_test - base_test, + "base_curve_best_ep": base_curve["curve_best_ep"], + "base_final_gap": base_curve["final_gap"], + "cand_curve_best_ep": cand_curve["curve_best_ep"], + "cand_curve_final_ep": cand_curve["curve_final_ep"], + "cand_final_gap": cand_curve["final_gap"], + "cand_late_slope": cand_curve["late_slope"], + "cand_range": cand_curve["range"], + } + row["labels"] = labels_for( + row, + val_tol=args.val_tol, + test_tol=args.test_tol, + collapse_gap=args.collapse_gap, + ) + rows.append(row) + + csv_path = out_dir / f"{args.dataset}_{args.candidate_compute}_T{args.candidate_T}_ns{args.candidate_n_sup}_diagnostics.csv" + fieldnames = [ + "view", "metric", "base_ep", "base_val", "base_test", "cand_ep", "cand_val", "cand_test", + "val_delta", "test_delta", "base_curve_best_ep", "base_final_gap", + "cand_curve_best_ep", "cand_curve_final_ep", "cand_final_gap", "cand_late_slope", + "cand_range", "labels", + ] + with csv_path.open("w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=fieldnames) + writer.writeheader() + writer.writerows(rows) + + counts = defaultdict(int) + for row in rows: + for label in row["labels"].split(","): + counts[label] += 1 + + pos = [r for r in rows if r["val_delta"] >= 0 and r["test_delta"] >= 0] + val_up_test_down = [r for r in rows if r["val_delta"] >= 0 and r["test_delta"] < 0] + val_down_test_up = [r for r in rows if r["val_delta"] < 0 and r["test_delta"] >= 0] + both_down = [r for r in rows if r["val_delta"] < 0 and r["test_delta"] < 0] + late = [r for r in rows if "maybe_undertrained" in r["labels"]] + collapse = [r for r in rows if "late_collapse" in r["labels"]] + val_deltas = [r["val_delta"] for r in rows] + test_deltas = [r["test_delta"] for r in rows] + + def row_line(r): + return [ + r["view"], + fmt(r["base_val"]), + fmt(r["cand_val"]), + fmt(r["val_delta"]), + fmt(r["base_test"]), + fmt(r["cand_test"]), + fmt(r["test_delta"]), + str(r["cand_ep"]), + fmt(r["cand_final_gap"]), + r["labels"], + ] + + md_path = csv_path.with_suffix(".md") + with md_path.open("w") as f: + f.write(f"# {args.dataset} {args.candidate_compute} T={args.candidate_T} ns={args.candidate_n_sup} diagnostics\n\n") + f.write(f"- rows: {len(rows)}\n") + f.write(f"- val+test positive: {len(pos)}\n") + f.write(f"- val up, test down: {len(val_up_test_down)}\n") + f.write(f"- val down, test up: {len(val_down_test_up)}\n") + f.write(f"- val+test down: {len(both_down)}\n") + f.write(f"- maybe undertrained: {len(late)}\n") + f.write(f"- late collapse: {len(collapse)}\n\n") + f.write(f"- mean val delta: {fmt(mean(val_deltas))}\n") + f.write(f"- mean test delta: {fmt(mean(test_deltas))}\n") + f.write(f"- val/test delta corr: {fmt(corr(val_deltas, test_deltas))}\n\n") + f.write("## Label Counts\n\n") + f.write(markdown_table(["label", "n"], [[k, str(v)] for k, v in sorted(counts.items())])) + f.write("\n\n## Per-Backbone Rows\n\n") + headers = [ + "view", "base_val", "cand_val", "d_val", "base_test", "cand_test", + "d_test", "cand_ep", "cand_final_gap", "labels", + ] + f.write(markdown_table(headers, [row_line(r) for r in rows])) + f.write("\n") + + print(f"wrote {csv_path}") + print(f"wrote {md_path}") + print(f"rows={len(rows)} val+test={len(pos)} val_up_test_down={len(val_up_test_down)} " + f"val_down_test_up={len(val_down_test_up)} both_down={len(both_down)} " + f"maybe_undertrained={len(late)} late_collapse={len(collapse)}") + + +if __name__ == "__main__": + main() diff --git a/scripts/collect_results.sh b/scripts/collect_results.sh new file mode 100755 index 0000000..360f05b --- /dev/null +++ b/scripts/collect_results.sh @@ -0,0 +1,10 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +mkdir -p summaries +python3 -m rrog.cli zinc-results --epochs "${ZINC_EPOCHS:-200}" | tee summaries/zinc_cycle56.md +python3 -m rrog.cli results --epochs "${OGB_EPOCHS:-100}" | tee summaries/ogb_graphprop.md diff --git a/scripts/run_ogb_act_task.sh b/scripts/run_ogb_act_task.sh new file mode 100755 index 0000000..37eb1a6 --- /dev/null +++ b/scripts/run_ogb_act_task.sh @@ -0,0 +1,119 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +TASK="${TASK:-ogbg-molhiv}" +DEVICE="${DEVICE:-cuda:0}" +EPOCHS="${EPOCHS:-100}" +SEEDS="${SEEDS:-${SEED:-0}}" +HIDDEN="${HIDDEN:-128}" +BS="${BS:-128}" +LR="${LR:-}" +EVAL_EVERY="${EVAL_EVERY:-10}" +NUM_WORKERS="${NUM_WORKERS:-0}" +T="${T:-1}" +N_SUP="${N_SUP:-3}" +HALT_MAX="${HALT_MAX:-8}" +HALT_MIN="${HALT_MIN:-2}" +HALT_TARGET="${HALT_TARGET:-loss}" +HALT_LOSS_THRESHOLD="${HALT_LOSS_THRESHOLD:-0.2}" +HALT_EXPLORATION_PROB="${HALT_EXPLORATION_PROB:-0.1}" +LAM_Q="${LAM_Q:-0.1}" +Q_WARMUP="${Q_WARMUP:-0}" +ACT_TRAIN_MODE="${ACT_TRAIN_MODE:-stream}" +EMA="${EMA:-0}" +MAX_TRAIN_BATCHES="${MAX_TRAIN_BATCHES:-}" +MAX_EVAL_BATCHES="${MAX_EVAL_BATCHES:-}" +COLLECT="${COLLECT:-1}" +VIEWS="${VIEWS:-gin gine gcn graphsage gatv2 graphconv transformer pna gen film resgated tag sgc cheb arma mf appnp}" + +mkdir -p runs logs summaries + +fmt_float() { + python3 - "$1" <<'PY' +import sys +print(f"{float(sys.argv[1]):g}") +PY +} + +result_path() { + local view="$1" + local seed="$2" + local target_tag="${HALT_TARGET}" + local loss_tag + local lam_tag + local hex_tag + local ema_tag="" + loss_tag="$(fmt_float "${HALT_LOSS_THRESHOLD}")" + lam_tag="$(fmt_float "${LAM_Q}")" + hex_tag="$(fmt_float "${HALT_EXPLORATION_PROB}")" + if [[ "${HALT_TARGET}" == "loss" ]]; then + target_tag="loss${loss_tag}" + fi + if [[ "$(fmt_float "${EMA}")" != "0" ]]; then + ema_tag="_ema$(fmt_float "${EMA}")" + fi + echo "runs/${TASK}_${view}_rrog-act_T${T}_ns${N_SUP}_${ACT_TRAIN_MODE}_hm${HALT_MAX}_hmin${HALT_MIN}_${target_tag}_lq${lam_tag}_hex${hex_tag}_qw${Q_WARMUP}_h${HIDDEN}_e${EPOCHS}${ema_tag}_s${seed}.json" +} + +run_cell() { + local view="$1" + local seed="$2" + local out + out="$(result_path "${view}" "${seed}")" + if [[ -f "${out}" ]]; then + echo "[skip] ${out}" + return + fi + + echo "[run] ${TASK} view=${view} compute=rrog-act mode=${ACT_TRAIN_MODE} T=${T} ns=${N_SUP} seed=${seed} device=${DEVICE}" + cmd=( + python3 -m rrog.cli run + --task "${TASK}" + --view "${view}" + --compute rrog-act + --epochs "${EPOCHS}" + --hidden "${HIDDEN}" + --bs "${BS}" + --T "${T}" + --n_sup "${N_SUP}" + --halt_max_steps "${HALT_MAX}" + --halt_min_steps "${HALT_MIN}" + --halt_target "${HALT_TARGET}" + --halt_loss_threshold "${HALT_LOSS_THRESHOLD}" + --halt_exploration_prob "${HALT_EXPLORATION_PROB}" + --lam_q "${LAM_Q}" + --q_warmup_epochs "${Q_WARMUP}" + --act_train_mode "${ACT_TRAIN_MODE}" + --eval_every "${EVAL_EVERY}" + --num_workers "${NUM_WORKERS}" + --seed "${seed}" + --device "${DEVICE}" + ) + if [[ -n "${LR}" ]]; then + cmd+=(--lr "${LR}") + fi + if [[ "$(fmt_float "${EMA}")" != "0" ]]; then + cmd+=(--ema "${EMA}") + fi + if [[ -n "${MAX_TRAIN_BATCHES}" ]]; then + cmd+=(--max_train_batches "${MAX_TRAIN_BATCHES}") + fi + if [[ -n "${MAX_EVAL_BATCHES}" ]]; then + cmd+=(--max_eval_batches "${MAX_EVAL_BATCHES}") + fi + "${cmd[@]}" +} + +for seed in ${SEEDS}; do + for view in ${VIEWS}; do + run_cell "${view}" "${seed}" + done +done + +if [[ "${COLLECT}" == "1" ]]; then + python3 -m rrog.cli results --epochs "${EPOCHS}" | tee "summaries/ogb_graphprop_act_${TASK}_e${EPOCHS}.md" +fi diff --git a/scripts/run_ogb_act_two_gpu.sh b/scripts/run_ogb_act_two_gpu.sh new file mode 100755 index 0000000..f51262b --- /dev/null +++ b/scripts/run_ogb_act_two_gpu.sh @@ -0,0 +1,91 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +GPU0="${GPU0:-cuda:0}" +GPU1="${GPU1:-cuda:1}" +if [[ -z "${TASKS_GPU0+x}" ]]; then + TASKS_GPU0="ogbg-molhiv ogbg-molbbbp ogbg-molsider ogbg-molbace" +fi +if [[ -z "${TASKS_GPU1+x}" ]]; then + TASKS_GPU1="ogbg-molesol ogbg-mollipo ogbg-moltox21 ogbg-molclintox" +fi +EPOCHS="${EPOCHS:-100}" +SEEDS="${SEEDS:-${SEED:-0}}" +HALT_MAX="${HALT_MAX:-8}" +HALT_MIN="${HALT_MIN:-2}" +HALT_TARGET="${HALT_TARGET:-loss}" +HALT_LOSS_THRESHOLD="${HALT_LOSS_THRESHOLD:-0.2}" +HALT_EXPLORATION_PROB="${HALT_EXPLORATION_PROB:-0.1}" +LAM_Q="${LAM_Q:-0.1}" +Q_WARMUP="${Q_WARMUP:-0}" +ACT_TRAIN_MODE="${ACT_TRAIN_MODE:-stream}" + +mkdir -p logs summaries + +fmt_float() { + python3 - "$1" <<'PY' +import sys +print(f"{float(sys.argv[1]):g}") +PY +} + +target_log_tag() { + local target_tag="${HALT_TARGET}" + if [[ "${HALT_TARGET}" == "loss" ]]; then + target_tag="loss$(fmt_float "${HALT_LOSS_THRESHOLD}")" + fi + echo "${ACT_TRAIN_MODE}_hm${HALT_MAX}_hmin${HALT_MIN}_${target_tag}_lq$(fmt_float "${LAM_Q}")_hex$(fmt_float "${HALT_EXPLORATION_PROB}")_qw${Q_WARMUP}_e${EPOCHS}_s${SEEDS// /-}" +} + +run_queue() { + local device="$1" + shift + local tasks=("$@") + local task + local tag + tag="$(target_log_tag)" + for task in "${tasks[@]}"; do + if [[ -z "${task}" ]]; then + continue + fi + echo "[task] ${task} on ${device}" + TASK="${task}" DEVICE="${device}" EPOCHS="${EPOCHS}" SEEDS="${SEEDS}" \ + HALT_MAX="${HALT_MAX}" HALT_MIN="${HALT_MIN}" HALT_TARGET="${HALT_TARGET}" \ + HALT_LOSS_THRESHOLD="${HALT_LOSS_THRESHOLD}" HALT_EXPLORATION_PROB="${HALT_EXPLORATION_PROB}" \ + LAM_Q="${LAM_Q}" Q_WARMUP="${Q_WARMUP}" \ + ACT_TRAIN_MODE="${ACT_TRAIN_MODE}" COLLECT=0 \ + ./scripts/run_ogb_act_task.sh 2>&1 | tee "logs/${task}_act_${tag}.log" + done +} + +tasks0=() +tasks1=() +if [[ -n "${TASKS_GPU0}" ]]; then + read -r -a tasks0 <<< "${TASKS_GPU0}" +fi +if [[ -n "${TASKS_GPU1}" ]]; then + read -r -a tasks1 <<< "${TASKS_GPU1}" +fi + +pids=() +if (( ${#tasks0[@]} > 0 )); then + echo "[launch] ${GPU0}: ${tasks0[*]}" + run_queue "${GPU0}" "${tasks0[@]}" & + pids+=("$!") +fi +if (( ${#tasks1[@]} > 0 )); then + echo "[launch] ${GPU1}: ${tasks1[*]}" + run_queue "${GPU1}" "${tasks1[@]}" & + pids+=("$!") +fi + +for pid in "${pids[@]}"; do + wait "${pid}" +done + +echo "[done] collecting summaries" +OGB_EPOCHS="${EPOCHS}" ./scripts/collect_results.sh diff --git a/scripts/run_ogb_mol_all_tasks.sh b/scripts/run_ogb_mol_all_tasks.sh new file mode 100755 index 0000000..b191d79 --- /dev/null +++ b/scripts/run_ogb_mol_all_tasks.sh @@ -0,0 +1,17 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" + +DEVICE="${DEVICE:-cuda:1}" +EPOCHS="${EPOCHS:-100}" +SEED="${SEED:-0}" +TASKS="${TASKS:-ogbg-molhiv ogbg-molbbbp ogbg-molbace ogbg-moltox21 ogbg-molclintox ogbg-molsider ogbg-molesol ogbg-molfreesolv ogbg-mollipo}" + +mkdir -p logs +for task in ${TASKS}; do + echo "[task] ${task}" + TASK="${task}" DEVICE="${DEVICE}" EPOCHS="${EPOCHS}" SEED="${SEED}" \ + ./scripts/run_ogb_mol_task_full.sh 2>&1 | tee "logs/${task}_${SEED}.log" +done diff --git a/scripts/run_ogb_mol_task_full.sh b/scripts/run_ogb_mol_task_full.sh new file mode 100755 index 0000000..71ddba1 --- /dev/null +++ b/scripts/run_ogb_mol_task_full.sh @@ -0,0 +1,56 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +TASK="${TASK:-ogbg-molhiv}" +DEVICE="${DEVICE:-cuda:1}" +EPOCHS="${EPOCHS:-100}" +SEED="${SEED:-0}" +HIDDEN="${HIDDEN:-128}" +FIXED_T="${FIXED_T:-3}" +FIXED_NS="${FIXED_NS:-3}" +VIEWS="${VIEWS:-gin gine gcn graphsage gatv2 graphconv transformer pna gen film resgated tag sgc cheb arma mf appnp}" + +mkdir -p runs logs + +result_path() { + local view="$1" + local compute="$2" + local t="$3" + local ns="$4" + echo "runs/${TASK}_${view}_${compute}_T${t}_ns${ns}_h${HIDDEN}_e${EPOCHS}_s${SEED}.json" +} + +run_cell() { + local view="$1" + local compute="$2" + local t="$3" + local ns="$4" + local out + out="$(result_path "${view}" "${compute}" "${t}" "${ns}")" + if [[ -f "${out}" ]]; then + echo "[skip] ${out}" + return + fi + echo "[run] ${TASK} view=${view} compute=${compute} T=${t} ns=${ns} device=${DEVICE}" + python3 -m rrog.cli run \ + --task "${TASK}" \ + --view "${view}" \ + --compute "${compute}" \ + --epochs "${EPOCHS}" \ + --hidden "${HIDDEN}" \ + --T "${t}" \ + --n_sup "${ns}" \ + --seed "${SEED}" \ + --device "${DEVICE}" +} + +for view in ${VIEWS}; do + run_cell "${view}" classic 0 1 + run_cell "${view}" fixed-rrog "${FIXED_T}" "${FIXED_NS}" +done + +python3 -m rrog.cli results --epochs "${EPOCHS}" diff --git a/scripts/run_smoke.sh b/scripts/run_smoke.sh new file mode 100755 index 0000000..6365cec --- /dev/null +++ b/scripts/run_smoke.sh @@ -0,0 +1,19 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +DEVICE="${DEVICE:-cuda:0}" +mkdir -p runs logs + +python3 -m rrog.cli run \ + --task ogbg-molhiv --view gin --compute classic \ + --epochs 1 --hidden 32 --bs 64 --seed 991 --device "${DEVICE}" \ + --max_train_batches 2 --max_eval_batches 2 + +python3 -m rrog.cli run \ + --task ogbg-molhiv --view gin --compute fixed-rrog \ + --epochs 1 --hidden 32 --bs 64 --T 1 --n_sup 2 --seed 992 --device "${DEVICE}" \ + --max_train_batches 2 --max_eval_batches 2 diff --git a/scripts/run_two_a6000.sh b/scripts/run_two_a6000.sh new file mode 100755 index 0000000..8d9851f --- /dev/null +++ b/scripts/run_two_a6000.sh @@ -0,0 +1,32 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +ZINC_DEVICE="${ZINC_DEVICE:-cuda:0}" +OGB_DEVICE="${OGB_DEVICE:-cuda:1}" +OGB_TASK="${OGB_TASK:-ogbg-molhiv}" +ZINC_EPOCHS="${ZINC_EPOCHS:-200}" +OGB_EPOCHS="${OGB_EPOCHS:-100}" +SEED="${SEED:-0}" + +mkdir -p runs logs + +echo "[launch] ZINC-cycle56 on ${ZINC_DEVICE}" +DEVICE="${ZINC_DEVICE}" EPOCHS="${ZINC_EPOCHS}" SEED="${SEED}" \ + ./scripts/run_zinc_cycle56_full.sh > "logs/zinc_cycle56_${SEED}.log" 2>&1 & +zinc_pid=$! + +echo "[launch] ${OGB_TASK} on ${OGB_DEVICE}" +TASK="${OGB_TASK}" DEVICE="${OGB_DEVICE}" EPOCHS="${OGB_EPOCHS}" SEED="${SEED}" \ + ./scripts/run_ogb_mol_task_full.sh > "logs/${OGB_TASK}_${SEED}.log" 2>&1 & +ogb_pid=$! + +echo "[pids] zinc=${zinc_pid} ogb=${ogb_pid}" +wait "${zinc_pid}" +wait "${ogb_pid}" + +echo "[done] collecting summaries" +./scripts/collect_results.sh diff --git a/scripts/run_zinc_cycle56_full.sh b/scripts/run_zinc_cycle56_full.sh new file mode 100755 index 0000000..151a51e --- /dev/null +++ b/scripts/run_zinc_cycle56_full.sh @@ -0,0 +1,54 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" +export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}" + +DEVICE="${DEVICE:-cuda:0}" +EPOCHS="${EPOCHS:-200}" +SEED="${SEED:-0}" +VIEWS="${VIEWS:-gin gine gcn graphsage gatv2 graphconv transformer pna gen film resgated tag sgc cheb arma mf appnp}" + +mkdir -p runs logs + +result_path() { + local view="$1" + local t="$2" + local ns="$3" + local view_tag="" + if [[ "${view}" != "gin" ]]; then + view_tag="_${view}" + fi + echo "runs/rec_rrog${view_tag}_full_sig0.0_K1_none_T${t}_ns${ns}_trace_s${SEED}.json" +} + +run_cell() { + local view="$1" + local compute="$2" + local t="$3" + local ns="$4" + local out + out="$(result_path "${view}" "${t}" "${ns}")" + if [[ -f "${out}" ]]; then + echo "[skip] ${out}" + return + fi + echo "[run] zinc-cycle56 view=${view} compute=${compute} T=${t} ns=${ns} device=${DEVICE}" + python3 -m rrog.cli run \ + --task zinc-cycle56 \ + --view "${view}" \ + --compute "${compute}" \ + --epochs "${EPOCHS}" \ + --T "${t}" \ + --n_sup "${ns}" \ + --seed "${SEED}" \ + --device "${DEVICE}" +} + +for view in ${VIEWS}; do + run_cell "${view}" classic 0 1 + run_cell "${view}" fixed-rrog 1 3 +done + +python3 -m rrog.cli zinc-results --epochs "${EPOCHS}" diff --git a/scripts/setup_and_run_two_a6000.sh b/scripts/setup_and_run_two_a6000.sh new file mode 100755 index 0000000..ec4e3da --- /dev/null +++ b/scripts/setup_and_run_two_a6000.sh @@ -0,0 +1,15 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" + +if [[ "${SKIP_SETUP:-0}" != "1" ]]; then + ./scripts/setup_env.sh +fi + +if [[ -d "${VENV_DIR:-.venv}" ]]; then + source "${VENV_DIR:-.venv}/bin/activate" +fi + +./scripts/run_two_a6000.sh diff --git a/scripts/setup_env.sh b/scripts/setup_env.sh new file mode 100755 index 0000000..66a94c8 --- /dev/null +++ b/scripts/setup_env.sh @@ -0,0 +1,35 @@ +#!/usr/bin/env bash +set -euo pipefail + +ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)" +cd "${ROOT_DIR}" + +PYTHON_BIN="${PYTHON_BIN:-python3}" +VENV_DIR="${VENV_DIR:-.venv}" +TORCH_INDEX_URL="${TORCH_INDEX_URL:-https://download.pytorch.org/whl/cu124}" + +if [[ ! -d "${VENV_DIR}" ]]; then + "${PYTHON_BIN}" -m venv "${VENV_DIR}" +fi + +source "${VENV_DIR}/bin/activate" +python -m pip install --upgrade pip wheel setuptools + +if ! python - <<'PY' >/dev/null 2>&1 +import torch +assert torch.cuda.is_available() or True +PY +then + python -m pip install torch --index-url "${TORCH_INDEX_URL}" +fi + +python -m pip install -r requirements.txt + +python - <<'PY' +import torch +import torch_geometric +import ogb +print("torch", torch.__version__, "cuda_available", torch.cuda.is_available()) +print("torch_geometric", torch_geometric.__version__) +print("ogb", ogb.__version__) +PY diff --git a/summaries/ogb_graphprop.md b/summaries/ogb_graphprop.md new file mode 100644 index 0000000..ff3e0ee --- /dev/null +++ b/summaries/ogb_graphprop.md @@ -0,0 +1,467 @@ + +Classic baseline: task x backbone +| task | backbone | metric | n | val | test | +| --- | --- | --- | --- | --- | --- | +| ogbg-molbace | appnp | rocauc | 1 | 0.6564 +/- 0.0000 | 0.7423 +/- 0.0000 | +| ogbg-molbace | arma | rocauc | 1 | 0.6923 +/- 0.0000 | 0.7839 +/- 0.0000 | +| ogbg-molbace | cheb | rocauc | 1 | 0.7267 +/- 0.0000 | 0.7969 +/- 0.0000 | +| ogbg-molbace | film | rocauc | 1 | 0.6703 +/- 0.0000 | 0.7242 +/- 0.0000 | +| ogbg-molbace | gatv2 | rocauc | 1 | 0.7029 +/- 0.0000 | 0.7400 +/- 0.0000 | +| ogbg-molbace | gcn | rocauc | 1 | 0.6381 +/- 0.0000 | 0.7393 +/- 0.0000 | +| ogbg-molbace | gen | rocauc | 1 | 0.7128 +/- 0.0000 | 0.7326 +/- 0.0000 | +| ogbg-molbace | gin | rocauc | 1 | 0.6520 +/- 0.0000 | 0.7336 +/- 0.0000 | +| ogbg-molbace | gine | rocauc | 1 | 0.6641 +/- 0.0000 | 0.7454 +/- 0.0000 | +| ogbg-molbace | graphconv | rocauc | 1 | 0.7311 +/- 0.0000 | 0.8035 +/- 0.0000 | +| ogbg-molbace | graphsage | rocauc | 1 | 0.6758 +/- 0.0000 | 0.7759 +/- 0.0000 | +| ogbg-molbace | mf | rocauc | 1 | 0.7421 +/- 0.0000 | 0.7760 +/- 0.0000 | +| ogbg-molbace | pna | rocauc | 1 | 0.7516 +/- 0.0000 | 0.6912 +/- 0.0000 | +| ogbg-molbace | resgated | rocauc | 1 | 0.7172 +/- 0.0000 | 0.7877 +/- 0.0000 | +| ogbg-molbace | sgc | rocauc | 1 | 0.6575 +/- 0.0000 | 0.6966 +/- 0.0000 | +| ogbg-molbace | tag | rocauc | 1 | 0.7084 +/- 0.0000 | 0.7345 +/- 0.0000 | +| ogbg-molbace | transformer | rocauc | 1 | 0.6663 +/- 0.0000 | 0.7364 +/- 0.0000 | +| ogbg-molbbbp | appnp | rocauc | 1 | 0.9147 +/- 0.0000 | 0.6388 +/- 0.0000 | +| ogbg-molbbbp | arma | rocauc | 1 | 0.9367 +/- 0.0000 | 0.6651 +/- 0.0000 | +| ogbg-molbbbp | cheb | rocauc | 1 | 0.9452 +/- 0.0000 | 0.6514 +/- 0.0000 | +| ogbg-molbbbp | film | rocauc | 1 | 0.9285 +/- 0.0000 | 0.6300 +/- 0.0000 | +| ogbg-molbbbp | gatv2 | rocauc | 1 | 0.9347 +/- 0.0000 | 0.6324 +/- 0.0000 | +| ogbg-molbbbp | gcn | rocauc | 1 | 0.9386 +/- 0.0000 | 0.6679 +/- 0.0000 | +| ogbg-molbbbp | gen | rocauc | 1 | 0.9549 +/- 0.0000 | 0.6775 +/- 0.0000 | +| ogbg-molbbbp | gin | rocauc | 1 | 0.9251 +/- 0.0000 | 0.5670 +/- 0.0000 | +| ogbg-molbbbp | gine | rocauc | 1 | 0.9324 +/- 0.0000 | 0.6160 +/- 0.0000 | +| ogbg-molbbbp | graphconv | rocauc | 1 | 0.9268 +/- 0.0000 | 0.5900 +/- 0.0000 | +| ogbg-molbbbp | graphsage | rocauc | 1 | 0.9483 +/- 0.0000 | 0.6288 +/- 0.0000 | +| ogbg-molbbbp | mf | rocauc | 1 | 0.9395 +/- 0.0000 | 0.6365 +/- 0.0000 | +| ogbg-molbbbp | pna | rocauc | 1 | 0.9554 +/- 0.0000 | 0.6418 +/- 0.0000 | +| ogbg-molbbbp | resgated | rocauc | 1 | 0.9183 +/- 0.0000 | 0.6626 +/- 0.0000 | +| ogbg-molbbbp | sgc | rocauc | 1 | 0.9300 +/- 0.0000 | 0.6239 +/- 0.0000 | +| ogbg-molbbbp | tag | rocauc | 1 | 0.9476 +/- 0.0000 | 0.6100 +/- 0.0000 | +| ogbg-molbbbp | transformer | rocauc | 1 | 0.9495 +/- 0.0000 | 0.6156 +/- 0.0000 | +| ogbg-molclintox | appnp | rocauc | 1 | 0.8516 +/- 0.0000 | 0.9184 +/- 0.0000 | +| ogbg-molclintox | arma | rocauc | 1 | 0.9463 +/- 0.0000 | 0.8678 +/- 0.0000 | +| ogbg-molclintox | cheb | rocauc | 1 | 0.8928 +/- 0.0000 | 0.9152 +/- 0.0000 | +| ogbg-molclintox | film | rocauc | 1 | 0.9048 +/- 0.0000 | 0.7731 +/- 0.0000 | +| ogbg-molclintox | gatv2 | rocauc | 1 | 0.9515 +/- 0.0000 | 0.8493 +/- 0.0000 | +| ogbg-molclintox | gcn | rocauc | 1 | 0.9318 +/- 0.0000 | 0.8932 +/- 0.0000 | +| ogbg-molclintox | gen | rocauc | 1 | 0.9820 +/- 0.0000 | 0.8128 +/- 0.0000 | +| ogbg-molclintox | gin | rocauc | 1 | 0.9547 +/- 0.0000 | 0.8586 +/- 0.0000 | +| ogbg-molclintox | gine | rocauc | 1 | 0.9353 +/- 0.0000 | 0.8869 +/- 0.0000 | +| ogbg-molclintox | graphconv | rocauc | 1 | 0.8917 +/- 0.0000 | 0.8501 +/- 0.0000 | +| ogbg-molclintox | graphsage | rocauc | 1 | 0.9143 +/- 0.0000 | 0.8882 +/- 0.0000 | +| ogbg-molclintox | mf | rocauc | 1 | 0.9252 +/- 0.0000 | 0.8370 +/- 0.0000 | +| ogbg-molclintox | pna | rocauc | 1 | 0.9286 +/- 0.0000 | 0.8603 +/- 0.0000 | +| ogbg-molclintox | resgated | rocauc | 1 | 0.9244 +/- 0.0000 | 0.9184 +/- 0.0000 | +| ogbg-molclintox | sgc | rocauc | 1 | 0.9195 +/- 0.0000 | 0.8986 +/- 0.0000 | +| ogbg-molclintox | tag | rocauc | 1 | 0.9237 +/- 0.0000 | 0.7998 +/- 0.0000 | +| ogbg-molclintox | transformer | rocauc | 1 | 0.9271 +/- 0.0000 | 0.8764 +/- 0.0000 | +| ogbg-molesol | appnp | rmse | 1 | 1.6083 +/- 0.0000 | 1.5212 +/- 0.0000 | +| ogbg-molesol | arma | rmse | 1 | 1.0195 +/- 0.0000 | 1.0666 +/- 0.0000 | +| ogbg-molesol | cheb | rmse | 1 | 0.9650 +/- 0.0000 | 0.8722 +/- 0.0000 | +| ogbg-molesol | film | rmse | 1 | 1.0718 +/- 0.0000 | 1.2896 +/- 0.0000 | +| ogbg-molesol | gatv2 | rmse | 1 | 1.0368 +/- 0.0000 | 0.9878 +/- 0.0000 | +| ogbg-molesol | gcn | rmse | 1 | 1.0409 +/- 0.0000 | 1.1161 +/- 0.0000 | +| ogbg-molesol | gen | rmse | 1 | 1.0089 +/- 0.0000 | 0.8762 +/- 0.0000 | +| ogbg-molesol | gin | rmse | 1 | 1.0187 +/- 0.0000 | 0.9900 +/- 0.0000 | +| ogbg-molesol | gine | rmse | 1 | 1.0286 +/- 0.0000 | 1.0807 +/- 0.0000 | +| ogbg-molesol | graphconv | rmse | 1 | 0.9741 +/- 0.0000 | 0.9732 +/- 0.0000 | +| ogbg-molesol | graphsage | rmse | 1 | 0.9680 +/- 0.0000 | 1.0038 +/- 0.0000 | +| ogbg-molesol | mf | rmse | 1 | 1.1494 +/- 0.0000 | 1.0639 +/- 0.0000 | +| ogbg-molesol | pna | rmse | 1 | 0.9116 +/- 0.0000 | 0.9153 +/- 0.0000 | +| ogbg-molesol | resgated | rmse | 1 | 0.9492 +/- 0.0000 | 0.8908 +/- 0.0000 | +| ogbg-molesol | sgc | rmse | 1 | 1.0617 +/- 0.0000 | 0.9780 +/- 0.0000 | +| ogbg-molesol | tag | rmse | 1 | 0.9323 +/- 0.0000 | 0.9678 +/- 0.0000 | +| ogbg-molesol | transformer | rmse | 1 | 0.9398 +/- 0.0000 | 0.9492 +/- 0.0000 | +| ogbg-molfreesolv | appnp | rmse | 1 | 6.0462 +/- 0.0000 | 4.6478 +/- 0.0000 | +| ogbg-molfreesolv | arma | rmse | 1 | 4.2662 +/- 0.0000 | 2.9769 +/- 0.0000 | +| ogbg-molfreesolv | cheb | rmse | 1 | 2.9481 +/- 0.0000 | 2.2431 +/- 0.0000 | +| ogbg-molfreesolv | film | rmse | 1 | 3.1546 +/- 0.0000 | 2.9581 +/- 0.0000 | +| ogbg-molfreesolv | gatv2 | rmse | 1 | 4.2086 +/- 0.0000 | 2.7368 +/- 0.0000 | +| ogbg-molfreesolv | gcn | rmse | 1 | 3.7172 +/- 0.0000 | 2.4851 +/- 0.0000 | +| ogbg-molfreesolv | gen | rmse | 1 | 3.9998 +/- 0.0000 | 2.5588 +/- 0.0000 | +| ogbg-molfreesolv | gin | rmse | 1 | 4.0190 +/- 0.0000 | 3.4898 +/- 0.0000 | +| ogbg-molfreesolv | gine | rmse | 1 | 3.2961 +/- 0.0000 | 3.1442 +/- 0.0000 | +| ogbg-molfreesolv | graphconv | rmse | 1 | 2.5314 +/- 0.0000 | 2.7953 +/- 0.0000 | +| ogbg-molfreesolv | graphsage | rmse | 1 | 3.5022 +/- 0.0000 | 2.2977 +/- 0.0000 | +| ogbg-molfreesolv | mf | rmse | 1 | 2.7374 +/- 0.0000 | 2.8885 +/- 0.0000 | +| ogbg-molfreesolv | pna | rmse | 1 | 2.3625 +/- 0.0000 | 2.2610 +/- 0.0000 | +| ogbg-molfreesolv | resgated | rmse | 1 | 2.4772 +/- 0.0000 | 2.0041 +/- 0.0000 | +| ogbg-molfreesolv | sgc | rmse | 1 | 3.9147 +/- 0.0000 | 2.4146 +/- 0.0000 | +| ogbg-molfreesolv | tag | rmse | 1 | 2.6874 +/- 0.0000 | 2.3826 +/- 0.0000 | +| ogbg-molfreesolv | transformer | rmse | 1 | 4.0942 +/- 0.0000 | 2.3205 +/- 0.0000 | +| ogbg-molhiv | appnp | rocauc | 3 | 0.7274 +/- 0.0374 | 0.6982 +/- 0.0073 | +| ogbg-molhiv | arma | rocauc | 3 | 0.7799 +/- 0.0063 | 0.7396 +/- 0.0263 | +| ogbg-molhiv | cheb | rocauc | 3 | 0.7799 +/- 0.0207 | 0.7264 +/- 0.0039 | +| ogbg-molhiv | film | rocauc | 3 | 0.7840 +/- 0.0421 | 0.7505 +/- 0.0298 | +| ogbg-molhiv | gatv2 | rocauc | 3 | 0.7841 +/- 0.0088 | 0.7292 +/- 0.0262 | +| ogbg-molhiv | gcn | rocauc | 3 | 0.7751 +/- 0.0003 | 0.7360 +/- 0.0190 | +| ogbg-molhiv | gen | rocauc | 3 | 0.7626 +/- 0.0141 | 0.7438 +/- 0.0126 | +| ogbg-molhiv | gin | rocauc | 3 | 0.8052 +/- 0.0145 | 0.7600 +/- 0.0179 | +| ogbg-molhiv | gine | rocauc | 3 | 0.7787 +/- 0.0156 | 0.7505 +/- 0.0200 | +| ogbg-molhiv | graphconv | rocauc | 3 | 0.7656 +/- 0.0284 | 0.7330 +/- 0.0222 | +| ogbg-molhiv | graphsage | rocauc | 3 | 0.7865 +/- 0.0102 | 0.7506 +/- 0.0195 | +| ogbg-molhiv | mf | rocauc | 3 | 0.7718 +/- 0.0137 | 0.7352 +/- 0.0319 | +| ogbg-molhiv | pna | rocauc | 3 | 0.7943 +/- 0.0148 | 0.7520 +/- 0.0114 | +| ogbg-molhiv | resgated | rocauc | 3 | 0.7963 +/- 0.0157 | 0.7316 +/- 0.0205 | +| ogbg-molhiv | sgc | rocauc | 3 | 0.7699 +/- 0.0225 | 0.7038 +/- 0.0055 | +| ogbg-molhiv | tag | rocauc | 3 | 0.7488 +/- 0.0133 | 0.7432 +/- 0.0156 | +| ogbg-molhiv | transformer | rocauc | 3 | 0.7668 +/- 0.0086 | 0.7714 +/- 0.0168 | +| ogbg-mollipo | appnp | rmse | 1 | 0.9015 +/- 0.0000 | 0.9070 +/- 0.0000 | +| ogbg-mollipo | arma | rmse | 1 | 0.7325 +/- 0.0000 | 0.7295 +/- 0.0000 | +| ogbg-mollipo | cheb | rmse | 1 | 0.7188 +/- 0.0000 | 0.7180 +/- 0.0000 | +| ogbg-mollipo | film | rmse | 1 | 0.7620 +/- 0.0000 | 0.7371 +/- 0.0000 | +| ogbg-mollipo | gatv2 | rmse | 1 | 0.6865 +/- 0.0000 | 0.7308 +/- 0.0000 | +| ogbg-mollipo | gcn | rmse | 1 | 0.7379 +/- 0.0000 | 0.7828 +/- 0.0000 | +| ogbg-mollipo | gen | rmse | 1 | 0.7046 +/- 0.0000 | 0.7379 +/- 0.0000 | +| ogbg-mollipo | gin | rmse | 1 | 0.6854 +/- 0.0000 | 0.7390 +/- 0.0000 | +| ogbg-mollipo | gine | rmse | 1 | 0.6615 +/- 0.0000 | 0.7341 +/- 0.0000 | +| ogbg-mollipo | graphconv | rmse | 1 | 0.7178 +/- 0.0000 | 0.7297 +/- 0.0000 | +| ogbg-mollipo | graphsage | rmse | 1 | 0.7239 +/- 0.0000 | 0.7783 +/- 0.0000 | +| ogbg-mollipo | mf | rmse | 1 | 0.7129 +/- 0.0000 | 0.7405 +/- 0.0000 | +| ogbg-mollipo | pna | rmse | 1 | 0.7179 +/- 0.0000 | 0.7749 +/- 0.0000 | +| ogbg-mollipo | resgated | rmse | 1 | 0.6721 +/- 0.0000 | 0.7270 +/- 0.0000 | +| ogbg-mollipo | sgc | rmse | 1 | 0.7505 +/- 0.0000 | 0.8176 +/- 0.0000 | +| ogbg-mollipo | tag | rmse | 1 | 0.6692 +/- 0.0000 | 0.7227 +/- 0.0000 | +| ogbg-mollipo | transformer | rmse | 1 | 0.6810 +/- 0.0000 | 0.7346 +/- 0.0000 | +| ogbg-molsider | appnp | rocauc | 1 | 0.5886 +/- 0.0000 | 0.6004 +/- 0.0000 | +| ogbg-molsider | arma | rocauc | 1 | 0.6273 +/- 0.0000 | 0.6159 +/- 0.0000 | +| ogbg-molsider | cheb | rocauc | 1 | 0.6237 +/- 0.0000 | 0.6033 +/- 0.0000 | +| ogbg-molsider | film | rocauc | 1 | 0.6024 +/- 0.0000 | 0.5898 +/- 0.0000 | +| ogbg-molsider | gatv2 | rocauc | 1 | 0.6071 +/- 0.0000 | 0.6013 +/- 0.0000 | +| ogbg-molsider | gcn | rocauc | 1 | 0.6293 +/- 0.0000 | 0.6086 +/- 0.0000 | +| ogbg-molsider | gen | rocauc | 1 | 0.6519 +/- 0.0000 | 0.5854 +/- 0.0000 | +| ogbg-molsider | gin | rocauc | 1 | 0.6225 +/- 0.0000 | 0.5748 +/- 0.0000 | +| ogbg-molsider | gine | rocauc | 1 | 0.6327 +/- 0.0000 | 0.5495 +/- 0.0000 | +| ogbg-molsider | graphconv | rocauc | 1 | 0.5921 +/- 0.0000 | 0.6151 +/- 0.0000 | +| ogbg-molsider | graphsage | rocauc | 1 | 0.6217 +/- 0.0000 | 0.5807 +/- 0.0000 | +| ogbg-molsider | mf | rocauc | 1 | 0.6202 +/- 0.0000 | 0.5861 +/- 0.0000 | +| ogbg-molsider | pna | rocauc | 1 | 0.6219 +/- 0.0000 | 0.5965 +/- 0.0000 | +| ogbg-molsider | resgated | rocauc | 1 | 0.6209 +/- 0.0000 | 0.5910 +/- 0.0000 | +| ogbg-molsider | sgc | rocauc | 1 | 0.6174 +/- 0.0000 | 0.6043 +/- 0.0000 | +| ogbg-molsider | tag | rocauc | 1 | 0.6439 +/- 0.0000 | 0.6143 +/- 0.0000 | +| ogbg-molsider | transformer | rocauc | 1 | 0.6160 +/- 0.0000 | 0.5980 +/- 0.0000 | +| ogbg-moltox21 | appnp | rocauc | 1 | 0.7255 +/- 0.0000 | 0.7158 +/- 0.0000 | +| ogbg-moltox21 | arma | rocauc | 1 | 0.7799 +/- 0.0000 | 0.7223 +/- 0.0000 | +| ogbg-moltox21 | cheb | rocauc | 1 | 0.7834 +/- 0.0000 | 0.7301 +/- 0.0000 | +| ogbg-moltox21 | film | rocauc | 1 | 0.7702 +/- 0.0000 | 0.7160 +/- 0.0000 | +| ogbg-moltox21 | gatv2 | rocauc | 1 | 0.7627 +/- 0.0000 | 0.7160 +/- 0.0000 | +| ogbg-moltox21 | gcn | rocauc | 1 | 0.7580 +/- 0.0000 | 0.7171 +/- 0.0000 | +| ogbg-moltox21 | gen | rocauc | 1 | 0.7835 +/- 0.0000 | 0.7444 +/- 0.0000 | +| ogbg-moltox21 | gin | rocauc | 1 | 0.7690 +/- 0.0000 | 0.7242 +/- 0.0000 | +| ogbg-moltox21 | gine | rocauc | 1 | 0.7744 +/- 0.0000 | 0.7328 +/- 0.0000 | +| ogbg-moltox21 | graphconv | rocauc | 1 | 0.7831 +/- 0.0000 | 0.7147 +/- 0.0000 | +| ogbg-moltox21 | graphsage | rocauc | 1 | 0.7709 +/- 0.0000 | 0.7196 +/- 0.0000 | +| ogbg-moltox21 | mf | rocauc | 1 | 0.7773 +/- 0.0000 | 0.7281 +/- 0.0000 | +| ogbg-moltox21 | pna | rocauc | 1 | 0.7660 +/- 0.0000 | 0.6946 +/- 0.0000 | +| ogbg-moltox21 | resgated | rocauc | 1 | 0.7950 +/- 0.0000 | 0.7275 +/- 0.0000 | +| ogbg-moltox21 | sgc | rocauc | 1 | 0.7611 +/- 0.0000 | 0.7240 +/- 0.0000 | +| ogbg-moltox21 | tag | rocauc | 1 | 0.7866 +/- 0.0000 | 0.7416 +/- 0.0000 | +| ogbg-moltox21 | transformer | rocauc | 1 | 0.7656 +/- 0.0000 | 0.7309 +/- 0.0000 | + +Delta vs matching classic +| task | backbone | compute | metric | n | val score (delta) | test score (delta) | adaptive test (delta) | steps | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | +| ogbg-molbace | appnp | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7168 (0.0604) | 0.7209 (-0.0214) | | | +| ogbg-molbace | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6835 (0.0271) | 0.7119 (-0.0304) | 0.7328 (-0.0095) | 2.13 | +| ogbg-molbace | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7179 (0.0256) | 0.7672 (-0.0167) | | | +| ogbg-molbace | arma | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7355 (0.0432) | 0.7451 (-0.0388) | 0.7646 (-0.0193) | 4.38 | +| ogbg-molbace | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7114 (-0.0154) | 0.7533 (-0.0436) | | | +| ogbg-molbace | cheb | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7165 (-0.0103) | 0.8007 (0.0038) | 0.8120 (0.0151) | 2.60 | +| ogbg-molbace | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6652 (-0.0051) | 0.7242 (0.0000) | | | +| ogbg-molbace | film | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6467 (-0.0236) | 0.6802 (-0.0440) | 0.6733 (-0.0509) | 5.26 | +| ogbg-molbace | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7026 (-0.0004) | 0.7519 (0.0118) | | | +| ogbg-molbace | gatv2 | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7132 (0.0103) | 0.8261 (0.0861) | 0.8263 (0.0862) | 4.01 | +| ogbg-molbace | gcn | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6374 (-0.0007) | 0.7733 (0.0339) | | | +| ogbg-molbace | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7201 (0.0821) | 0.7484 (0.0090) | 0.7451 (0.0057) | 3.96 | +| ogbg-molbace | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6894 (-0.0234) | 0.7449 (0.0123) | | | +| ogbg-molbace | gen | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6535 (-0.0593) | 0.6915 (-0.0410) | 0.6788 (-0.0537) | 3.98 | +| ogbg-molbace | gin | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6538 (0.0018) | 0.7169 (-0.0167) | | | +| ogbg-molbace | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6802 (0.0282) | 0.7235 (-0.0101) | 0.7220 (-0.0117) | 3.47 | +| ogbg-molbace | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6685 (0.0044) | 0.6994 (-0.0461) | | | +| ogbg-molbace | gine | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6824 (0.0183) | 0.7719 (0.0264) | 0.7698 (0.0243) | 3.17 | +| ogbg-molbace | graphconv | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7462 (0.0150) | 0.7983 (-0.0052) | | | +| ogbg-molbace | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6908 (-0.0403) | 0.7475 (-0.0560) | 0.7639 (-0.0396) | 4.28 | +| ogbg-molbace | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6703 (-0.0055) | 0.7119 (-0.0640) | | | +| ogbg-molbace | graphsage | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7092 (0.0333) | 0.7821 (0.0063) | 0.7910 (0.0151) | 3.75 | +| ogbg-molbace | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7234 (-0.0187) | 0.7684 (-0.0077) | | | +| ogbg-molbace | mf | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7747 (0.0326) | 0.8019 (0.0259) | 0.7950 (0.0190) | 4.98 | +| ogbg-molbace | pna | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7037 (-0.0480) | 0.7967 (0.1055) | | | +| ogbg-molbace | pna | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7095 (-0.0421) | 0.7809 (0.0897) | 0.7338 (0.0426) | 3.91 | +| ogbg-molbace | resgated | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6912 (-0.0260) | 0.7465 (-0.0412) | | | +| ogbg-molbace | resgated | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7396 (0.0223) | 0.7314 (-0.0563) | 0.7618 (-0.0259) | 3.39 | +| ogbg-molbace | sgc | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6454 (-0.0121) | 0.7727 (0.0762) | | | +| ogbg-molbace | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6615 (0.0040) | 0.7971 (0.1005) | 0.7988 (0.1022) | 3.64 | +| ogbg-molbace | tag | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7355 (0.0271) | 0.6806 (-0.0539) | | | +| ogbg-molbace | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7084 (0.0000) | 0.7960 (0.0616) | 0.7776 (0.0431) | 2.55 | +| ogbg-molbace | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6982 (0.0319) | 0.7487 (0.0123) | | | +| ogbg-molbace | transformer | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6535 (-0.0128) | 0.7192 (-0.0172) | 0.7293 (-0.0071) | 2.71 | +| ogbg-molbbbp | appnp | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9360 (0.0213) | 0.6073 (-0.0314) | | | +| ogbg-molbbbp | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9066 (-0.0081) | 0.5574 (-0.0814) | 0.6226 (-0.0162) | 2.01 | +| ogbg-molbbbp | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9415 (0.0048) | 0.6635 (-0.0016) | | | +| ogbg-molbbbp | arma | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9405 (0.0038) | 0.6411 (-0.0240) | 0.6368 (-0.0284) | 2.15 | +| ogbg-molbbbp | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9278 (-0.0174) | 0.6659 (0.0145) | | | +| ogbg-molbbbp | cheb | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9496 (0.0044) | 0.6182 (-0.0332) | 0.6110 (-0.0404) | 2.17 | +| ogbg-molbbbp | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9400 (0.0115) | 0.6323 (0.0023) | | | +| ogbg-molbbbp | film | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9393 (0.0108) | 0.5584 (-0.0716) | 0.5746 (-0.0555) | 3.21 | +| ogbg-molbbbp | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9356 (0.0009) | 0.6560 (0.0235) | | | +| ogbg-molbbbp | gatv2 | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9303 (-0.0044) | 0.6648 (0.0324) | 0.6627 (0.0303) | 2.14 | +| ogbg-molbbbp | gcn | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9417 (0.0031) | 0.6017 (-0.0663) | | | +| ogbg-molbbbp | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9528 (0.0142) | 0.6795 (0.0116) | 0.6629 (-0.0050) | 2.27 | +| ogbg-molbbbp | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9429 (-0.0119) | 0.6037 (-0.0738) | | | +| ogbg-molbbbp | gen | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9251 (-0.0298) | 0.6314 (-0.0461) | 0.6291 (-0.0483) | 3.79 | +| ogbg-molbbbp | gin | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9526 (0.0275) | 0.5932 (0.0261) | | | +| ogbg-molbbbp | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9204 (-0.0047) | 0.6528 (0.0857) | 0.6526 (0.0856) | 4.87 | +| ogbg-molbbbp | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9421 (0.0098) | 0.6976 (0.0816) | | | +| ogbg-molbbbp | gine | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9205 (-0.0118) | 0.5918 (-0.0242) | 0.5948 (-0.0212) | 2.92 | +| ogbg-molbbbp | graphconv | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9337 (0.0069) | 0.6518 (0.0618) | | | +| ogbg-molbbbp | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9234 (-0.0034) | 0.6602 (0.0702) | 0.6875 (0.0975) | 2.79 | +| ogbg-molbbbp | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9502 (0.0019) | 0.5934 (-0.0354) | | | +| ogbg-molbbbp | graphsage | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9407 (-0.0077) | 0.6040 (-0.0248) | 0.6148 (-0.0140) | 2.57 | +| ogbg-molbbbp | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9488 (0.0094) | 0.6481 (0.0116) | | | +| ogbg-molbbbp | mf | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9368 (-0.0027) | 0.6621 (0.0257) | 0.6678 (0.0313) | 3.54 | +| ogbg-molbbbp | pna | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9585 (0.0031) | 0.6682 (0.0264) | | | +| ogbg-molbbbp | pna | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9500 (-0.0054) | 0.6173 (-0.0245) | 0.6180 (-0.0238) | 4.69 | +| ogbg-molbbbp | resgated | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9535 (0.0352) | 0.5839 (-0.0787) | | | +| ogbg-molbbbp | resgated | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9133 (-0.0050) | 0.5753 (-0.0873) | 0.5887 (-0.0739) | 3.59 | +| ogbg-molbbbp | sgc | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9285 (-0.0015) | 0.6454 (0.0215) | | | +| ogbg-molbbbp | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9475 (0.0175) | 0.6593 (0.0354) | 0.6675 (0.0436) | 2.25 | +| ogbg-molbbbp | tag | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9459 (-0.0017) | 0.6420 (0.0320) | | | +| ogbg-molbbbp | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9496 (0.0020) | 0.6580 (0.0480) | 0.6551 (0.0451) | 2.62 | +| ogbg-molbbbp | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9355 (-0.0140) | 0.6221 (0.0065) | | | +| ogbg-molbbbp | transformer | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9398 (-0.0098) | 0.6426 (0.0269) | 0.6310 (0.0153) | 2.23 | +| ogbg-molclintox | appnp | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9029 (0.0513) | 0.8898 (-0.0286) | | | +| ogbg-molclintox | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9156 (0.0640) | 0.7780 (-0.1404) | 0.8861 (-0.0323) | 2.16 | +| ogbg-molclintox | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9135 (-0.0328) | 0.8863 (0.0185) | | | +| ogbg-molclintox | arma | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9423 (-0.0040) | 0.8458 (-0.0220) | 0.8651 (-0.0027) | 2.72 | +| ogbg-molclintox | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.8816 (-0.0112) | 0.8982 (-0.0170) | | | +| ogbg-molclintox | cheb | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9172 (0.0244) | 0.9066 (-0.0086) | 0.9058 (-0.0094) | 2.98 | +| ogbg-molclintox | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9454 (0.0406) | 0.8430 (0.0699) | | | +| ogbg-molclintox | film | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8532 (-0.0516) | 0.8230 (0.0499) | 0.8409 (0.0679) | 3.57 | +| ogbg-molclintox | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9351 (-0.0164) | 0.8328 (-0.0164) | | | +| ogbg-molclintox | gatv2 | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9507 (-0.0008) | 0.8618 (0.0125) | 0.8344 (-0.0149) | 2.34 | +| ogbg-molclintox | gcn | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9097 (-0.0221) | 0.8792 (-0.0140) | | | +| ogbg-molclintox | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9460 (0.0142) | 0.8712 (-0.0220) | 0.8802 (-0.0130) | 2.20 | +| ogbg-molclintox | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9399 (-0.0421) | 0.8194 (0.0066) | | | +| ogbg-molclintox | gen | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9627 (-0.0194) | 0.7994 (-0.0134) | 0.8025 (-0.0103) | 2.52 | +| ogbg-molclintox | gin | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9164 (-0.0383) | 0.8788 (0.0202) | | | +| ogbg-molclintox | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9600 (0.0053) | 0.8034 (-0.0553) | 0.8111 (-0.0475) | 2.71 | +| ogbg-molclintox | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9225 (-0.0127) | 0.8840 (-0.0030) | | | +| ogbg-molclintox | gine | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9456 (0.0104) | 0.9048 (0.0179) | 0.9069 (0.0200) | 2.30 | +| ogbg-molclintox | graphconv | fixed-rrog-T1-ns3 | rocauc | 1 | 0.8494 (-0.0424) | 0.8186 (-0.0316) | | | +| ogbg-molclintox | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9575 (0.0657) | 0.8813 (0.0311) | 0.8485 (-0.0016) | 2.41 | +| ogbg-molclintox | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9579 (0.0436) | 0.8664 (-0.0217) | | | +| ogbg-molclintox | graphsage | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9516 (0.0373) | 0.8822 (-0.0060) | 0.8780 (-0.0101) | 2.43 | +| ogbg-molclintox | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9147 (-0.0104) | 0.8047 (-0.0323) | | | +| ogbg-molclintox | mf | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9416 (0.0165) | 0.8527 (0.0157) | 0.8698 (0.0328) | 2.57 | +| ogbg-molclintox | pna | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9064 (-0.0222) | 0.8735 (0.0132) | | | +| ogbg-molclintox | pna | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8741 (-0.0544) | 0.8539 (-0.0064) | 0.8614 (0.0011) | 3.68 | +| ogbg-molclintox | resgated | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9055 (-0.0188) | 0.8979 (-0.0205) | | | +| ogbg-molclintox | resgated | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9577 (0.0333) | 0.8777 (-0.0407) | 0.8951 (-0.0233) | 2.26 | +| ogbg-molclintox | sgc | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9220 (0.0025) | 0.9054 (0.0068) | | | +| ogbg-molclintox | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9153 (-0.0042) | 0.8883 (-0.0103) | 0.8905 (-0.0081) | 2.25 | +| ogbg-molclintox | tag | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9183 (-0.0054) | 0.8433 (0.0435) | | | +| ogbg-molclintox | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9001 (-0.0236) | 0.8009 (0.0011) | 0.8084 (0.0085) | 2.59 | +| ogbg-molclintox | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9322 (0.0051) | 0.8522 (-0.0242) | | | +| ogbg-molclintox | transformer | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8521 (-0.0749) | 0.7333 (-0.1431) | 0.7908 (-0.0855) | 3.26 | +| ogbg-molesol | appnp | fixed-rrog-T1-ns3 | rmse | 1 | 1.4196 (0.1887) | 1.4929 (0.0284) | | | +| ogbg-molesol | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.6270 (-0.0187) | 1.2973 (0.2239) | 1.0733 (0.4479) | 2.81 | +| ogbg-molesol | arma | fixed-rrog-T1-ns3 | rmse | 1 | 1.0034 (0.0160) | 1.1272 (-0.0606) | | | +| ogbg-molesol | arma | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.3100 (-0.2905) | 1.5310 (-0.4644) | 1.0386 (0.0280) | 2.58 | +| ogbg-molesol | cheb | fixed-rrog-T1-ns3 | rmse | 1 | 0.9199 (0.0451) | 0.8841 (-0.0118) | | | +| ogbg-molesol | cheb | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0643 (-0.0993) | 1.0342 (-0.1620) | 0.8498 (0.0225) | 2.60 | +| ogbg-molesol | film | fixed-rrog-T1-ns3 | rmse | 1 | 1.0196 (0.0521) | 1.0849 (0.2047) | | | +| ogbg-molesol | film | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.3674 (-0.2956) | 1.3648 (-0.0752) | 1.1286 (0.1610) | 3.61 | +| ogbg-molesol | gatv2 | fixed-rrog-T1-ns3 | rmse | 1 | 1.0018 (0.0350) | 0.9780 (0.0098) | | | +| ogbg-molesol | gatv2 | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.9842 (0.0525) | 0.9534 (0.0344) | 0.8806 (0.1072) | 2.49 | +| ogbg-molesol | gcn | fixed-rrog-T1-ns3 | rmse | 1 | 0.9591 (0.0818) | 0.9305 (0.1856) | | | +| ogbg-molesol | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0294 (0.0115) | 1.2573 (-0.1411) | 0.9222 (0.1940) | 2.72 | +| ogbg-molesol | gen | fixed-rrog-T1-ns3 | rmse | 1 | 1.0027 (0.0062) | 0.9206 (-0.0444) | | | +| ogbg-molesol | gen | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.1622 (-0.1534) | 1.4459 (-0.5697) | 1.0919 (-0.2157) | 2.61 | +| ogbg-molesol | gin | fixed-rrog-T1-ns3 | rmse | 1 | 0.9647 (0.0540) | 1.0798 (-0.0899) | | | +| ogbg-molesol | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.4047 (-0.3860) | 2.0651 (-1.0751) | 0.9663 (0.0236) | 2.98 | +| ogbg-molesol | gine | fixed-rrog-T1-ns3 | rmse | 1 | 1.0581 (-0.0295) | 1.0951 (-0.0144) | | | +| ogbg-molesol | gine | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.3110 (-0.2824) | 2.0394 (-0.9588) | 1.0993 (-0.0186) | 2.88 | +| ogbg-molesol | graphconv | fixed-rrog-T1-ns3 | rmse | 1 | 1.0048 (-0.0307) | 0.9968 (-0.0236) | | | +| ogbg-molesol | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.1480 (-0.1739) | 1.2081 (-0.2348) | 1.0046 (-0.0314) | 2.74 | +| ogbg-molesol | graphsage | fixed-rrog-T1-ns3 | rmse | 1 | 0.9934 (-0.0254) | 1.0794 (-0.0757) | | | +| ogbg-molesol | graphsage | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.1587 (-0.1907) | 1.3229 (-0.3191) | 0.9324 (0.0714) | 2.40 | +| ogbg-molesol | mf | fixed-rrog-T1-ns3 | rmse | 1 | 1.0553 (0.0942) | 1.0368 (0.0271) | | | +| ogbg-molesol | mf | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0765 (0.0729) | 1.0844 (-0.0205) | 0.9589 (0.1050) | 3.41 | +| ogbg-molesol | pna | fixed-rrog-T1-ns3 | rmse | 1 | 0.9841 (-0.0725) | 0.9092 (0.0060) | | | +| ogbg-molesol | pna | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.2810 (-0.3694) | 1.4176 (-0.5023) | 0.9829 (-0.0677) | 2.60 | +| ogbg-molesol | resgated | fixed-rrog-T1-ns3 | rmse | 1 | 0.9873 (-0.0382) | 0.8825 (0.0083) | | | +| ogbg-molesol | resgated | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0939 (-0.1447) | 1.0833 (-0.1925) | 0.9181 (-0.0273) | 3.23 | +| ogbg-molesol | sgc | fixed-rrog-T1-ns3 | rmse | 1 | 1.0129 (0.0488) | 0.9373 (0.0407) | | | +| ogbg-molesol | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0345 (0.0272) | 1.0466 (-0.0686) | 0.9781 (-0.0001) | 3.28 | +| ogbg-molesol | tag | fixed-rrog-T1-ns3 | rmse | 1 | 0.9036 (0.0288) | 0.9462 (0.0215) | | | +| ogbg-molesol | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0871 (-0.1548) | 1.2508 (-0.2831) | 1.0190 (-0.0512) | 2.35 | +| ogbg-molesol | transformer | fixed-rrog-T1-ns3 | rmse | 1 | 0.9841 (-0.0443) | 1.0004 (-0.0512) | | | +| ogbg-molesol | transformer | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0664 (-0.1267) | 0.9534 (-0.0042) | 0.8505 (0.0987) | 2.28 | +| ogbg-molfreesolv | appnp | fixed-rrog-T1-ns3 | rmse | 1 | 5.5593 (0.4869) | 3.6549 (0.9928) | | | +| ogbg-molfreesolv | arma | fixed-rrog-T1-ns3 | rmse | 1 | 5.0683 (-0.8021) | 3.6823 (-0.7053) | | | +| ogbg-molfreesolv | cheb | fixed-rrog-T1-ns3 | rmse | 1 | 3.0142 (-0.0662) | 2.2399 (0.0032) | | | +| ogbg-molfreesolv | film | fixed-rrog-T1-ns3 | rmse | 1 | 3.2952 (-0.1406) | 3.3042 (-0.3460) | | | +| ogbg-molfreesolv | gatv2 | fixed-rrog-T1-ns3 | rmse | 1 | 3.9984 (0.2103) | 2.5966 (0.1403) | | | +| ogbg-molfreesolv | gcn | fixed-rrog-T1-ns3 | rmse | 1 | 3.5888 (0.1285) | 2.4444 (0.0407) | | | +| ogbg-molfreesolv | gen | fixed-rrog-T1-ns3 | rmse | 1 | 4.3009 (-0.3011) | 2.9063 (-0.3476) | | | +| ogbg-molfreesolv | gin | fixed-rrog-T1-ns3 | rmse | 1 | 3.9743 (0.0447) | 3.4292 (0.0607) | | | +| ogbg-molfreesolv | gine | fixed-rrog-T1-ns3 | rmse | 1 | 4.4468 (-1.1508) | 3.7405 (-0.5963) | | | +| ogbg-molfreesolv | graphconv | fixed-rrog-T1-ns3 | rmse | 1 | 2.9106 (-0.3792) | 3.1429 (-0.3476) | | | +| ogbg-molfreesolv | graphsage | fixed-rrog-T1-ns3 | rmse | 1 | 3.7380 (-0.2358) | 2.1931 (0.1046) | | | +| ogbg-molfreesolv | mf | fixed-rrog-T1-ns3 | rmse | 1 | 2.5060 (0.2313) | 3.1892 (-0.3007) | | | +| ogbg-molfreesolv | pna | fixed-rrog-T1-ns3 | rmse | 1 | 3.3334 (-0.9708) | 2.4279 (-0.1669) | | | +| ogbg-molfreesolv | resgated | fixed-rrog-T1-ns3 | rmse | 1 | 3.0920 (-0.6148) | 2.0244 (-0.0203) | | | +| ogbg-molfreesolv | sgc | fixed-rrog-T1-ns3 | rmse | 1 | 3.9261 (-0.0114) | 2.4887 (-0.0741) | | | +| ogbg-molfreesolv | tag | fixed-rrog-T1-ns3 | rmse | 1 | 2.7359 (-0.0486) | 2.0588 (0.3237) | | | +| ogbg-molfreesolv | transformer | fixed-rrog-T1-ns3 | rmse | 1 | 4.4180 (-0.3237) | 2.4325 (-0.1120) | | | +| ogbg-molhiv | appnp | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7568 (0.0294) | 0.7303 (0.0321) | | | +| ogbg-molhiv | appnp | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7203 (-0.0471) | 0.6825 (-0.0175) | | | +| ogbg-molhiv | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7379 (-0.0296) | 0.6883 (-0.0117) | 0.7291 (0.0291) | 2.10 | +| ogbg-molhiv | arma | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7823 (0.0023) | 0.7120 (-0.0276) | | | +| ogbg-molhiv | arma | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7926 (0.0054) | 0.7318 (0.0021) | | | +| ogbg-molhiv | arma | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7861 (-0.0011) | 0.7307 (0.0011) | 0.7379 (0.0082) | 2.09 | +| ogbg-molhiv | cheb | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7898 (0.0099) | 0.7347 (0.0083) | | | +| ogbg-molhiv | cheb | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7735 (-0.0096) | 0.7426 (0.0144) | | | +| ogbg-molhiv | cheb | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7825 (-0.0006) | 0.7206 (-0.0076) | 0.7219 (-0.0063) | 2.29 | +| ogbg-molhiv | film | fixed-rrog-T1-ns3 | rocauc | 3 | 0.8070 (0.0230) | 0.7523 (0.0018) | | | +| ogbg-molhiv | film | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7633 (-0.0288) | 0.7728 (-0.0114) | | | +| ogbg-molhiv | film | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8150 (0.0229) | 0.7415 (-0.0427) | 0.7292 (-0.0551) | 2.21 | +| ogbg-molhiv | gatv2 | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7734 (-0.0106) | 0.7269 (-0.0023) | | | +| ogbg-molhiv | gatv2 | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7835 (0.0001) | 0.7466 (-0.0096) | | | +| ogbg-molhiv | gatv2 | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7722 (-0.0112) | 0.7005 (-0.0557) | 0.7210 (-0.0353) | 2.16 | +| ogbg-molhiv | gcn | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7829 (0.0078) | 0.7386 (0.0026) | | | +| ogbg-molhiv | gcn | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7455 (-0.0300) | 0.7483 (0.0285) | | | +| ogbg-molhiv | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7652 (-0.0102) | 0.7280 (0.0082) | 0.7195 (-0.0003) | 2.14 | +| ogbg-molhiv | gen | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7664 (0.0038) | 0.7487 (0.0049) | | | +| ogbg-molhiv | gen | fixed-rrog-T3-ns3 | rocauc | 1 | 0.8128 (0.0598) | 0.7631 (0.0318) | | | +| ogbg-molhiv | gen | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7690 (0.0160) | 0.7434 (0.0121) | 0.7427 (0.0113) | 2.18 | +| ogbg-molhiv | gin | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7710 (-0.0342) | 0.7548 (-0.0052) | | | +| ogbg-molhiv | gin | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7524 (-0.0644) | 0.7324 (-0.0400) | | | +| ogbg-molhiv | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7623 (-0.0545) | 0.7285 (-0.0439) | 0.7415 (-0.0309) | 2.18 | +| ogbg-molhiv | gine | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7646 (-0.0140) | 0.7352 (-0.0153) | | | +| ogbg-molhiv | gine | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7575 (-0.0368) | 0.7401 (-0.0044) | | | +| ogbg-molhiv | gine | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7427 (-0.0515) | 0.7217 (-0.0228) | 0.7220 (-0.0226) | 2.19 | +| ogbg-molhiv | graphconv | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7755 (0.0099) | 0.7305 (-0.0025) | | | +| ogbg-molhiv | graphconv | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7713 (0.0006) | 0.6979 (-0.0129) | | | +| ogbg-molhiv | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7791 (0.0084) | 0.7511 (0.0403) | 0.7493 (0.0385) | 2.23 | +| ogbg-molhiv | graphsage | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7860 (-0.0005) | 0.7290 (-0.0216) | | | +| ogbg-molhiv | graphsage | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7587 (-0.0382) | 0.7641 (0.0016) | | | +| ogbg-molhiv | graphsage | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7724 (-0.0244) | 0.7541 (-0.0084) | 0.7493 (-0.0132) | 2.23 | +| ogbg-molhiv | mf | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7826 (0.0109) | 0.7127 (-0.0225) | | | +| ogbg-molhiv | mf | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7931 (0.0085) | 0.7217 (0.0143) | | | +| ogbg-molhiv | mf | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8047 (0.0201) | 0.7416 (0.0343) | 0.7333 (0.0260) | 2.20 | +| ogbg-molhiv | pna | fixed-rrog-T1-ns3 | rocauc | 3 | 0.8141 (0.0198) | 0.7503 (-0.0018) | | | +| ogbg-molhiv | pna | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7890 (0.0111) | 0.7630 (-0.0018) | | | +| ogbg-molhiv | pna | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7488 (-0.0292) | 0.6730 (-0.0918) | 0.6877 (-0.0771) | 2.06 | +| ogbg-molhiv | resgated | fixed-rrog-T1-ns3 | rocauc | 3 | 0.8020 (0.0057) | 0.7383 (0.0066) | | | +| ogbg-molhiv | resgated | fixed-rrog-T3-ns3 | rocauc | 1 | 0.8174 (0.0030) | 0.7055 (-0.0187) | | | +| ogbg-molhiv | resgated | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8031 (-0.0113) | 0.7503 (0.0261) | 0.7567 (0.0325) | 2.22 | +| ogbg-molhiv | sgc | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7643 (-0.0056) | 0.7105 (0.0067) | | | +| ogbg-molhiv | sgc | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7482 (0.0003) | 0.7177 (0.0158) | | | +| ogbg-molhiv | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7353 (-0.0126) | 0.6962 (-0.0057) | 0.7017 (-0.0002) | 2.08 | +| ogbg-molhiv | tag | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7554 (0.0066) | 0.7339 (-0.0093) | | | +| ogbg-molhiv | tag | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7804 (0.0276) | 0.7352 (0.0096) | | | +| ogbg-molhiv | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7568 (0.0040) | 0.7481 (0.0225) | 0.7477 (0.0222) | 2.23 | +| ogbg-molhiv | transformer | fixed-rrog-T1-ns3 | rocauc | 3 | 0.7844 (0.0177) | 0.7637 (-0.0077) | | | +| ogbg-molhiv | transformer | fixed-rrog-T3-ns3 | rocauc | 1 | 0.8088 (0.0471) | 0.7413 (-0.0134) | | | +| ogbg-molhiv | transformer | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7813 (0.0196) | 0.7294 (-0.0253) | 0.7396 (-0.0151) | 2.22 | +| ogbg-mollipo | appnp | fixed-rrog-T1-ns3 | rmse | 1 | 0.8393 (0.0622) | 0.9174 (-0.0104) | | | +| ogbg-mollipo | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.1389 (-0.2374) | 1.0733 (-0.1663) | 0.8332 (0.0738) | 2.24 | +| ogbg-mollipo | arma | fixed-rrog-T1-ns3 | rmse | 1 | 0.7173 (0.0152) | 0.7548 (-0.0253) | | | +| ogbg-mollipo | arma | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 108.3475 (-107.6151) | 1.5815 (-0.8520) | 1.2715 (-0.5420) | 6.02 | +| ogbg-mollipo | cheb | fixed-rrog-T1-ns3 | rmse | 1 | 0.6990 (0.0198) | 0.7132 (0.0048) | | | +| ogbg-mollipo | cheb | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.7459 (-0.0271) | 0.8055 (-0.0875) | 0.7405 (-0.0225) | 2.03 | +| ogbg-mollipo | film | fixed-rrog-T1-ns3 | rmse | 1 | 0.8122 (-0.0502) | 0.7353 (0.0018) | | | +| ogbg-mollipo | film | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.9864 (-0.2243) | 0.9712 (-0.2341) | 0.8345 (-0.0974) | 3.21 | +| ogbg-mollipo | gatv2 | fixed-rrog-T1-ns3 | rmse | 1 | 0.7080 (-0.0215) | 0.7334 (-0.0026) | | | +| ogbg-mollipo | gatv2 | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.8837 (-0.1973) | 0.9251 (-0.1943) | 0.7936 (-0.0628) | 2.29 | +| ogbg-mollipo | gcn | fixed-rrog-T1-ns3 | rmse | 1 | 0.7730 (-0.0351) | 0.7759 (0.0069) | | | +| ogbg-mollipo | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.9104 (-0.1725) | 0.9299 (-0.1471) | 0.8010 (-0.0181) | 2.48 | +| ogbg-mollipo | gen | fixed-rrog-T1-ns3 | rmse | 1 | 0.6594 (0.0452) | 0.7456 (-0.0077) | | | +| ogbg-mollipo | gen | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.9300 (-0.2254) | 0.9386 (-0.2007) | 0.9375 (-0.1996) | 4.25 | +| ogbg-mollipo | gin | fixed-rrog-T1-ns3 | rmse | 1 | 0.6749 (0.0105) | 0.7073 (0.0317) | | | +| ogbg-mollipo | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.8873 (-0.2019) | 1.0246 (-0.2856) | 0.8619 (-0.1229) | 2.54 | +| ogbg-mollipo | gine | fixed-rrog-T1-ns3 | rmse | 1 | 0.7168 (-0.0553) | 0.7316 (0.0025) | | | +| ogbg-mollipo | gine | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.8773 (-0.2159) | 0.9710 (-0.2369) | 0.8221 (-0.0880) | 2.40 | +| ogbg-mollipo | graphconv | fixed-rrog-T1-ns3 | rmse | 1 | 0.7372 (-0.0195) | 0.7396 (-0.0099) | | | +| ogbg-mollipo | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.9624 (-0.2446) | 0.9986 (-0.2689) | 0.7662 (-0.0366) | 2.12 | +| ogbg-mollipo | graphsage | fixed-rrog-T1-ns3 | rmse | 1 | 0.7184 (0.0055) | 0.7720 (0.0063) | | | +| ogbg-mollipo | graphsage | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0742 (-0.3503) | 1.1165 (-0.3382) | 0.9748 (-0.1965) | 5.46 | +| ogbg-mollipo | mf | fixed-rrog-T1-ns3 | rmse | 1 | 0.7050 (0.0080) | 0.7101 (0.0304) | | | +| ogbg-mollipo | mf | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 1.0056 (-0.2927) | 0.9820 (-0.2415) | 0.9414 (-0.2009) | 4.32 | +| ogbg-mollipo | pna | fixed-rrog-T1-ns3 | rmse | 1 | 0.7466 (-0.0287) | 0.7908 (-0.0159) | | | +| ogbg-mollipo | pna | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.9147 (-0.1968) | 0.9267 (-0.1517) | 0.8750 (-0.1001) | 4.61 | +| ogbg-mollipo | resgated | fixed-rrog-T1-ns3 | rmse | 1 | 0.6766 (-0.0046) | 0.7144 (0.0126) | | | +| ogbg-mollipo | resgated | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.8307 (-0.1587) | 0.8825 (-0.1554) | 0.7250 (0.0020) | 2.12 | +| ogbg-mollipo | sgc | fixed-rrog-T1-ns3 | rmse | 1 | 0.7537 (-0.0032) | 0.7490 (0.0685) | | | +| ogbg-mollipo | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.9196 (-0.1692) | 1.0145 (-0.1969) | 0.8478 (-0.0303) | 2.35 | +| ogbg-mollipo | tag | fixed-rrog-T1-ns3 | rmse | 1 | 0.6743 (-0.0052) | 0.7201 (0.0026) | | | +| ogbg-mollipo | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.8615 (-0.1924) | 0.9196 (-0.1969) | 0.8038 (-0.0812) | 2.35 | +| ogbg-mollipo | transformer | fixed-rrog-T1-ns3 | rmse | 1 | 0.6688 (0.0121) | 0.7396 (-0.0050) | | | +| ogbg-mollipo | transformer | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rmse | 1 | 0.8666 (-0.1856) | 0.8930 (-0.1583) | 0.7886 (-0.0540) | 2.32 | +| ogbg-molsider | appnp | fixed-rrog-T1-ns3 | rocauc | 1 | 0.5938 (0.0051) | 0.5905 (-0.0099) | | | +| ogbg-molsider | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5801 (-0.0085) | 0.6009 (0.0005) | 0.5959 (-0.0045) | 7.28 | +| ogbg-molsider | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6344 (0.0071) | 0.6141 (-0.0018) | | | +| ogbg-molsider | arma | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6605 (0.0332) | 0.5590 (-0.0569) | 0.5581 (-0.0578) | 7.90 | +| ogbg-molsider | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6263 (0.0026) | 0.6096 (0.0062) | | | +| ogbg-molsider | cheb | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6409 (0.0172) | 0.6150 (0.0116) | 0.6145 (0.0111) | 7.87 | +| ogbg-molsider | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.5862 (-0.0162) | 0.5974 (0.0076) | | | +| ogbg-molsider | film | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5408 (-0.0616) | 0.5825 (-0.0073) | 0.5825 (-0.0073) | 8.00 | +| ogbg-molsider | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6462 (0.0391) | 0.6000 (-0.0013) | | | +| ogbg-molsider | gatv2 | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5778 (-0.0294) | 0.6337 (0.0324) | 0.6340 (0.0326) | 7.96 | +| ogbg-molsider | gcn | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6256 (-0.0037) | 0.6117 (0.0031) | | | +| ogbg-molsider | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6346 (0.0053) | 0.6445 (0.0359) | 0.6445 (0.0359) | 7.93 | +| ogbg-molsider | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6345 (-0.0175) | 0.6053 (0.0199) | | | +| ogbg-molsider | gen | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6114 (-0.0405) | 0.6071 (0.0218) | 0.6071 (0.0218) | 8.00 | +| ogbg-molsider | gin | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6046 (-0.0179) | 0.6022 (0.0274) | | | +| ogbg-molsider | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5942 (-0.0283) | 0.5949 (0.0201) | 0.5949 (0.0201) | 8.00 | +| ogbg-molsider | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6151 (-0.0176) | 0.6150 (0.0655) | | | +| ogbg-molsider | gine | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6117 (-0.0209) | 0.6143 (0.0648) | 0.6148 (0.0653) | 7.96 | +| ogbg-molsider | graphconv | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6010 (0.0089) | 0.5963 (-0.0188) | | | +| ogbg-molsider | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6140 (0.0219) | 0.6069 (-0.0082) | 0.6064 (-0.0087) | 7.92 | +| ogbg-molsider | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6232 (0.0015) | 0.5861 (0.0053) | | | +| ogbg-molsider | graphsage | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6150 (-0.0068) | 0.6082 (0.0275) | 0.6073 (0.0265) | 7.92 | +| ogbg-molsider | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6190 (-0.0012) | 0.5983 (0.0122) | | | +| ogbg-molsider | mf | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6300 (0.0098) | 0.5843 (-0.0017) | 0.5856 (-0.0005) | 7.87 | +| ogbg-molsider | pna | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6058 (-0.0161) | 0.5721 (-0.0243) | | | +| ogbg-molsider | pna | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5810 (-0.0408) | 0.5398 (-0.0567) | 0.5398 (-0.0567) | 8.00 | +| ogbg-molsider | resgated | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6205 (-0.0005) | 0.5960 (0.0050) | | | +| ogbg-molsider | resgated | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6097 (-0.0112) | 0.6246 (0.0335) | 0.6247 (0.0336) | 7.95 | +| ogbg-molsider | sgc | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6151 (-0.0022) | 0.6417 (0.0375) | | | +| ogbg-molsider | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5866 (-0.0308) | 0.6246 (0.0203) | 0.6242 (0.0199) | 7.88 | +| ogbg-molsider | tag | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6410 (-0.0028) | 0.6102 (-0.0041) | | | +| ogbg-molsider | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6329 (-0.0109) | 0.6061 (-0.0082) | 0.6067 (-0.0076) | 7.91 | +| ogbg-molsider | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6315 (0.0156) | 0.6190 (0.0210) | | | +| ogbg-molsider | transformer | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6288 (0.0128) | 0.6215 (0.0235) | 0.6212 (0.0232) | 7.95 | +| ogbg-moltox21 | appnp | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7280 (0.0025) | 0.7154 (-0.0005) | | | +| ogbg-moltox21 | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7171 (-0.0083) | 0.7197 (0.0039) | 0.7332 (0.0173) | 2.59 | +| ogbg-moltox21 | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7771 (-0.0028) | 0.7209 (-0.0014) | | | +| ogbg-moltox21 | arma | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7575 (-0.0224) | 0.7162 (-0.0061) | 0.7237 (0.0014) | 2.87 | +| ogbg-moltox21 | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7710 (-0.0125) | 0.7286 (-0.0015) | | | +| ogbg-moltox21 | cheb | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7824 (-0.0010) | 0.7195 (-0.0105) | 0.7203 (-0.0098) | 3.01 | +| ogbg-moltox21 | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7727 (0.0025) | 0.7369 (0.0209) | | | +| ogbg-moltox21 | film | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7513 (-0.0189) | 0.6885 (-0.0275) | 0.6897 (-0.0263) | 3.55 | +| ogbg-moltox21 | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7762 (0.0135) | 0.7303 (0.0143) | | | +| ogbg-moltox21 | gatv2 | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7674 (0.0046) | 0.7155 (-0.0004) | 0.7172 (0.0012) | 4.04 | +| ogbg-moltox21 | gcn | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7588 (0.0007) | 0.7230 (0.0059) | | | +| ogbg-moltox21 | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7677 (0.0097) | 0.7136 (-0.0035) | 0.7247 (0.0076) | 3.26 | +| ogbg-moltox21 | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7757 (-0.0077) | 0.7312 (-0.0132) | | | +| ogbg-moltox21 | gen | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7548 (-0.0286) | 0.7300 (-0.0144) | 0.7366 (-0.0078) | 3.43 | +| ogbg-moltox21 | gin | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7718 (0.0028) | 0.7237 (-0.0005) | | | +| ogbg-moltox21 | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7634 (-0.0056) | 0.7044 (-0.0198) | 0.7112 (-0.0130) | 4.17 | +| ogbg-moltox21 | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7622 (-0.0122) | 0.7193 (-0.0135) | | | +| ogbg-moltox21 | gine | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7616 (-0.0127) | 0.7120 (-0.0208) | 0.7177 (-0.0151) | 3.93 | +| ogbg-moltox21 | graphconv | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7820 (-0.0011) | 0.7313 (0.0166) | | | +| ogbg-moltox21 | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7641 (-0.0191) | 0.7210 (0.0063) | 0.7323 (0.0175) | 4.09 | +| ogbg-moltox21 | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7697 (-0.0012) | 0.7205 (0.0009) | | | +| ogbg-moltox21 | graphsage | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7792 (0.0083) | 0.7217 (0.0021) | 0.7282 (0.0087) | 3.39 | +| ogbg-moltox21 | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7695 (-0.0078) | 0.7279 (-0.0002) | | | +| ogbg-moltox21 | mf | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7656 (-0.0117) | 0.7236 (-0.0045) | 0.7314 (0.0034) | 2.96 | +| ogbg-moltox21 | pna | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7745 (0.0085) | 0.7349 (0.0403) | | | +| ogbg-moltox21 | pna | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7625 (-0.0035) | 0.7138 (0.0192) | 0.7200 (0.0254) | 4.06 | +| ogbg-moltox21 | resgated | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7887 (-0.0064) | 0.7380 (0.0104) | | | +| ogbg-moltox21 | resgated | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7737 (-0.0213) | 0.7454 (0.0179) | 0.7449 (0.0173) | 2.78 | +| ogbg-moltox21 | sgc | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7506 (-0.0105) | 0.7355 (0.0115) | | | +| ogbg-moltox21 | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7669 (0.0058) | 0.7262 (0.0022) | 0.7331 (0.0091) | 3.26 | +| ogbg-moltox21 | tag | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7839 (-0.0027) | 0.7342 (-0.0074) | | | +| ogbg-moltox21 | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7792 (-0.0074) | 0.7195 (-0.0221) | 0.7225 (-0.0190) | 3.32 | +| ogbg-moltox21 | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7761 (0.0105) | 0.7292 (-0.0018) | | | +| ogbg-moltox21 | transformer | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7840 (0.0184) | 0.7237 (-0.0072) | 0.7242 (-0.0068) | 4.33 | diff --git a/summaries/zinc_cycle56.md b/summaries/zinc_cycle56.md new file mode 100644 index 0000000..961f0b4 --- /dev/null +++ b/summaries/zinc_cycle56.md @@ -0,0 +1,42 @@ + +ZINC-cycle56 classic baseline +| task | backbone | n | val MAE-sum | test MAE-sum | +| --- | --- | --- | --- | --- | +| zinc-cycle56 | appnp | 1 | 1.0040 +/- 0.0000 | 1.0183 +/- 0.0000 | +| zinc-cycle56 | arma | 1 | 0.3456 +/- 0.0000 | 0.3406 +/- 0.0000 | +| zinc-cycle56 | cheb | 1 | 0.4038 +/- 0.0000 | 0.3887 +/- 0.0000 | +| zinc-cycle56 | film | 1 | 0.4906 +/- 0.0000 | 0.4998 +/- 0.0000 | +| zinc-cycle56 | gatv2 | 1 | 0.4084 +/- 0.0000 | 0.4012 +/- 0.0000 | +| zinc-cycle56 | gcn | 1 | 0.5821 +/- 0.0000 | 0.5854 +/- 0.0000 | +| zinc-cycle56 | gen | 1 | 0.3961 +/- 0.0000 | 0.3854 +/- 0.0000 | +| zinc-cycle56 | gin | 1 | 0.2981 +/- 0.0000 | 0.2725 +/- 0.0000 | +| zinc-cycle56 | gine | 1 | 0.2387 +/- 0.0000 | 0.2317 +/- 0.0000 | +| zinc-cycle56 | graphconv | 1 | 0.3507 +/- 0.0000 | 0.3462 +/- 0.0000 | +| zinc-cycle56 | graphsage | 1 | 0.4134 +/- 0.0000 | 0.4179 +/- 0.0000 | +| zinc-cycle56 | mf | 1 | 0.3051 +/- 0.0000 | 0.3031 +/- 0.0000 | +| zinc-cycle56 | pna | 1 | 0.1565 +/- 0.0000 | 0.1539 +/- 0.0000 | +| zinc-cycle56 | resgated | 1 | 0.3183 +/- 0.0000 | 0.3168 +/- 0.0000 | +| zinc-cycle56 | sgc | 1 | 0.6287 +/- 0.0000 | 0.6432 +/- 0.0000 | +| zinc-cycle56 | tag | 1 | 0.2889 +/- 0.0000 | 0.2831 +/- 0.0000 | +| zinc-cycle56 | transformer | 1 | 0.3837 +/- 0.0000 | 0.3760 +/- 0.0000 | + +ZINC-cycle56 delta vs matching classic +| task | backbone | compute | n | val score (improvement) | test score (improvement) | +| --- | --- | --- | --- | --- | --- | +| zinc-cycle56 | appnp | fixed-rrog-T1-ns3+trace | 1 | 0.9730 (0.0310) | 0.9845 (0.0338) | +| zinc-cycle56 | arma | fixed-rrog-T1-ns3+trace | 1 | 0.2414 (0.1042) | 0.2378 (0.1028) | +| zinc-cycle56 | cheb | fixed-rrog-T1-ns3+trace | 1 | 0.2896 (0.1143) | 0.2830 (0.1057) | +| zinc-cycle56 | film | fixed-rrog-T1-ns3+trace | 1 | 0.6898 (-0.1993) | 0.6643 (-0.1646) | +| zinc-cycle56 | gatv2 | fixed-rrog-T1-ns3+trace | 1 | 0.3155 (0.0929) | 0.3121 (0.0891) | +| zinc-cycle56 | gcn | fixed-rrog-T1-ns3+trace | 1 | 0.4380 (0.1441) | 0.4603 (0.1251) | +| zinc-cycle56 | gen | fixed-rrog-T1-ns3+trace | 1 | 0.3554 (0.0407) | 0.3405 (0.0450) | +| zinc-cycle56 | gin | fixed-rrog-T1-ns3+trace | 1 | 0.2269 (0.0711) | 0.2222 (0.0502) | +| zinc-cycle56 | gine | fixed-rrog-T1-ns3+trace | 1 | 0.1641 (0.0745) | 0.1509 (0.0808) | +| zinc-cycle56 | graphconv | fixed-rrog-T1-ns3+trace | 1 | 0.2091 (0.1416) | 0.2060 (0.1402) | +| zinc-cycle56 | graphsage | fixed-rrog-T1-ns3+trace | 1 | 0.3381 (0.0753) | 0.3407 (0.0772) | +| zinc-cycle56 | mf | fixed-rrog-T1-ns3+trace | 1 | 0.1987 (0.1065) | 0.1911 (0.1120) | +| zinc-cycle56 | pna | fixed-rrog-T1-ns3+trace | 1 | 0.1216 (0.0349) | 0.1056 (0.0483) | +| zinc-cycle56 | resgated | fixed-rrog-T1-ns3+trace | 1 | 0.1834 (0.1350) | 0.1765 (0.1403) | +| zinc-cycle56 | sgc | fixed-rrog-T1-ns3+trace | 1 | 0.5008 (0.1278) | 0.5066 (0.1366) | +| zinc-cycle56 | tag | fixed-rrog-T1-ns3+trace | 1 | 0.1410 (0.1479) | 0.1386 (0.1445) | +| zinc-cycle56 | transformer | fixed-rrog-T1-ns3+trace | 1 | 0.3092 (0.0744) | 0.3268 (0.0491) | -- cgit v1.2.3