path: root/logs/local_gpu3_act_ablation_retry_20260624_102233.log

[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
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Extracting /home/yurenh2/rrog-gnn-runner/data/ogb/bbbp.zip
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/home/yurenh2/miniconda3/lib/python3.13/site-packages/ogb/graphproppred/dataset_pyg.py:156: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:213.)
  g.y = torch.from_numpy(graph_label[i]).view(1,-1).to(torch.long)
Done!
Saving...
ep10 val_rocauc=0.89356 val_adapt_rocauc=0.92960 adapt_steps=2.14 halt=0.41 train_steps=1.93
ep20 val_rocauc=0.84945 val_adapt_rocauc=0.83680 adapt_steps=2.08 halt=0.46 train_steps=1.71
ep30 val_rocauc=0.84815 val_adapt_rocauc=0.92940 adapt_steps=2.03 halt=0.46 train_steps=1.68
ep40 val_rocauc=0.91307 val_adapt_rocauc=0.92452 adapt_steps=2.04 halt=0.46 train_steps=1.64
ep50 val_rocauc=0.92821 val_adapt_rocauc=0.93647 adapt_steps=2.09 halt=0.47 train_steps=1.60
ep60 val_rocauc=0.88709 val_adapt_rocauc=0.91686 adapt_steps=2.06 halt=0.47 train_steps=1.60
ep70 val_rocauc=0.82187 val_adapt_rocauc=0.90979 adapt_steps=2.01 halt=0.47 train_steps=1.60
ep80 val_rocauc=0.86588 val_adapt_rocauc=0.91317 adapt_steps=2.02 halt=0.48 train_steps=1.57
ep90 val_rocauc=0.91586 val_adapt_rocauc=0.91596 adapt_steps=2.02 halt=0.48 train_steps=1.58
ep100 val_rocauc=0.90780 val_adapt_rocauc=0.91327 adapt_steps=2.01 halt=0.47 train_steps=1.60
[ogbg-molbbbp_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.9282087025789106} test={'rocauc': 0.6619405864197531} adaptive={'rocauc': 0.6692708333333333} steps=2.0833333333333335
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbbbp view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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=0.70039 val_adapt_rocauc=0.92542 adapt_steps=2.07 halt=0.46 train_steps=1.65
ep20 val_rocauc=0.88380 val_adapt_rocauc=0.92642 adapt_steps=2.02 halt=0.47 train_steps=1.62
ep30 val_rocauc=0.79638 val_adapt_rocauc=0.91417 adapt_steps=2.01 halt=0.47 train_steps=1.60
ep40 val_rocauc=0.94295 val_adapt_rocauc=0.95201 adapt_steps=2.01 halt=0.48 train_steps=1.58
ep50 val_rocauc=0.91327 val_adapt_rocauc=0.92164 adapt_steps=2.00 halt=0.48 train_steps=1.56
ep60 val_rocauc=0.91407 val_adapt_rocauc=0.93030 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep70 val_rocauc=0.91716 val_adapt_rocauc=0.92801 adapt_steps=2.00 halt=0.47 train_steps=1.59
ep80 val_rocauc=0.91407 val_adapt_rocauc=0.91825 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep90 val_rocauc=0.90959 val_adapt_rocauc=0.91138 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep100 val_rocauc=0.91228 val_adapt_rocauc=0.91566 adapt_steps=2.00 halt=0.48 train_steps=1.58
[ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.9429453350592453} test={'rocauc': 0.6137152777777778} adaptive={'rocauc': 0.675829475308642} steps=2.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbbbp view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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=0.87613 val_adapt_rocauc=0.92184 adapt_steps=2.00 halt=0.42 train_steps=1.95
ep20 val_rocauc=0.87285 val_adapt_rocauc=0.92134 adapt_steps=2.01 halt=0.46 train_steps=1.74
ep30 val_rocauc=0.87892 val_adapt_rocauc=0.93090 adapt_steps=2.02 halt=0.46 train_steps=1.66
ep40 val_rocauc=0.87315 val_adapt_rocauc=0.92920 adapt_steps=2.05 halt=0.47 train_steps=1.60
ep50 val_rocauc=0.87922 val_adapt_rocauc=0.92104 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep60 val_rocauc=0.89366 val_adapt_rocauc=0.92223 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep70 val_rocauc=0.93468 val_adapt_rocauc=0.94484 adapt_steps=2.00 halt=0.47 train_steps=1.57
ep80 val_rocauc=0.91945 val_adapt_rocauc=0.92811 adapt_steps=2.00 halt=0.48 train_steps=1.56
ep90 val_rocauc=0.92253 val_adapt_rocauc=0.93060 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep100 val_rocauc=0.91925 val_adapt_rocauc=0.92930 adapt_steps=2.00 halt=0.48 train_steps=1.58
[ogbg-molbbbp_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.9346808722493279} test={'rocauc': 0.6516203703703703} adaptive={'rocauc': 0.6385030864197532} steps=2.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbbbp view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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=0.78522 val_adapt_rocauc=0.83192 adapt_steps=2.08 halt=0.40 train_steps=2.07
ep20 val_rocauc=0.92472 val_adapt_rocauc=0.93388 adapt_steps=2.22 halt=0.44 train_steps=1.81
ep30 val_rocauc=0.94056 val_adapt_rocauc=0.94852 adapt_steps=2.01 halt=0.46 train_steps=1.66
ep40 val_rocauc=0.89077 val_adapt_rocauc=0.92691 adapt_steps=2.01 halt=0.47 train_steps=1.61
ep50 val_rocauc=0.89605 val_adapt_rocauc=0.92423 adapt_steps=2.03 halt=0.48 train_steps=1.57
ep60 val_rocauc=0.90571 val_adapt_rocauc=0.93647 adapt_steps=2.03 halt=0.47 train_steps=1.60
ep70 val_rocauc=0.91337 val_adapt_rocauc=0.93179 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep80 val_rocauc=0.92512 val_adapt_rocauc=0.93866 adapt_steps=2.01 halt=0.48 train_steps=1.56
ep90 val_rocauc=0.92194 val_adapt_rocauc=0.93418 adapt_steps=2.01 halt=0.48 train_steps=1.58
ep100 val_rocauc=0.92134 val_adapt_rocauc=0.93259 adapt_steps=2.01 halt=0.47 train_steps=1.58
[ogbg-molbbbp_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.9405556108732449} test={'rocauc': 0.635030864197531} adaptive={'rocauc': 0.6146797839506173} steps=2.014705882352941
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbbbp view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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=0.72269 val_adapt_rocauc=0.93777 adapt_steps=2.29 halt=0.42 train_steps=2.02
ep20 val_rocauc=0.86110 val_adapt_rocauc=0.88460 adapt_steps=2.14 halt=0.47 train_steps=1.61
ep30 val_rocauc=0.88181 val_adapt_rocauc=0.91278 adapt_steps=2.00 halt=0.47 train_steps=1.63
ep40 val_rocauc=0.82027 val_adapt_rocauc=0.88151 adapt_steps=2.06 halt=0.46 train_steps=1.67
ep50 val_rocauc=0.90561 val_adapt_rocauc=0.92393 adapt_steps=2.00 halt=0.47 train_steps=1.57
ep60 val_rocauc=0.86339 val_adapt_rocauc=0.89804 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep70 val_rocauc=0.84397 val_adapt_rocauc=0.90242 adapt_steps=2.00 halt=0.47 train_steps=1.57
ep80 val_rocauc=0.86578 val_adapt_rocauc=0.91955 adapt_steps=2.00 halt=0.48 train_steps=1.56
ep90 val_rocauc=0.84049 val_adapt_rocauc=0.91019 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep100 val_rocauc=0.84556 val_adapt_rocauc=0.91248 adapt_steps=2.00 halt=0.47 train_steps=1.59
[ogbg-molbbbp_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.9056058946529921} test={'rocauc': 0.6368634259259259} adaptive={'rocauc': 0.6415895061728395} steps=2.1176470588235294
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbbbp view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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=0.76730 val_adapt_rocauc=0.88778 adapt_steps=2.00 halt=0.47 train_steps=1.59
ep20 val_rocauc=0.87454 val_adapt_rocauc=0.90780 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep30 val_rocauc=0.80006 val_adapt_rocauc=0.87334 adapt_steps=2.00 halt=0.47 train_steps=1.60
ep40 val_rocauc=0.86010 val_adapt_rocauc=0.90411 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep50 val_rocauc=0.87972 val_adapt_rocauc=0.90810 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep60 val_rocauc=0.83292 val_adapt_rocauc=0.88918 adapt_steps=2.01 halt=0.47 train_steps=1.59
ep70 val_rocauc=0.84706 val_adapt_rocauc=0.89893 adapt_steps=2.00 halt=0.47 train_steps=1.59
ep80 val_rocauc=0.83740 val_adapt_rocauc=0.90232 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep90 val_rocauc=0.83670 val_adapt_rocauc=0.90222 adapt_steps=2.00 halt=0.48 train_steps=1.59
ep100 val_rocauc=0.84357 val_adapt_rocauc=0.90252 adapt_steps=2.00 halt=0.47 train_steps=1.60
[ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.8797172159713232} test={'rocauc': 0.5456211419753086} adaptive={'rocauc': 0.5880594135802469} steps=2.0098039215686274
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbbbp view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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=0.92482 val_adapt_rocauc=0.93149 adapt_steps=2.24 halt=0.44 train_steps=1.79
/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=0.50592 val_adapt_rocauc=0.89495 adapt_steps=2.03 halt=0.45 train_steps=1.73
/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=0.93797 val_adapt_rocauc=0.94275 adapt_steps=2.20 halt=0.44 train_steps=1.75
/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=0.85004 val_adapt_rocauc=0.90750 adapt_steps=2.00 halt=0.44 train_steps=1.77
/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=0.88719 val_adapt_rocauc=0.89734 adapt_steps=2.01 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(
ep60 val_rocauc=0.92024 val_adapt_rocauc=0.92930 adapt_steps=2.03 halt=0.46 train_steps=1.65
/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=0.91278 val_adapt_rocauc=0.91975 adapt_steps=2.01 halt=0.47 train_steps=1.62
/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=0.88728 val_adapt_rocauc=0.89485 adapt_steps=2.01 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(
ep90 val_rocauc=0.89605 val_adapt_rocauc=0.89157 adapt_steps=2.00 halt=0.48 train_steps=1.59
/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=0.89704 val_adapt_rocauc=0.89196 adapt_steps=2.00 halt=0.47 train_steps=1.59
[ogbg-molbbbp_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.9379667430050782} test={'rocauc': 0.6539351851851851} adaptive={'rocauc': 0.6563464506172839} steps=2.3137254901960786
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbbbp view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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=0.80335 val_adapt_rocauc=0.89714 adapt_steps=2.00 halt=0.43 train_steps=1.80
ep20 val_rocauc=0.94992 val_adapt_rocauc=0.95589 adapt_steps=2.15 halt=0.46 train_steps=1.65
ep30 val_rocauc=0.89844 val_adapt_rocauc=0.92413 adapt_steps=2.31 halt=0.46 train_steps=1.60
ep40 val_rocauc=0.88499 val_adapt_rocauc=0.92303 adapt_steps=2.03 halt=0.47 train_steps=1.61
ep50 val_rocauc=0.87145 val_adapt_rocauc=0.91118 adapt_steps=2.02 halt=0.47 train_steps=1.58
ep60 val_rocauc=0.83670 val_adapt_rocauc=0.89266 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep70 val_rocauc=0.83142 val_adapt_rocauc=0.89963 adapt_steps=2.01 halt=0.47 train_steps=1.58
ep80 val_rocauc=0.85273 val_adapt_rocauc=0.90859 adapt_steps=2.00 halt=0.48 train_steps=1.56
ep90 val_rocauc=0.82246 val_adapt_rocauc=0.89346 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep100 val_rocauc=0.83471 val_adapt_rocauc=0.90033 adapt_steps=2.00 halt=0.48 train_steps=1.58
[ogbg-molbbbp_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=20 val={'rocauc': 0.9499153639350792} test={'rocauc': 0.6603973765432098} adaptive={'rocauc': 0.6677276234567902} steps=2.343137254901961
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[task] ogbg-molsider on cuda:3
[run] ogbg-molsider view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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
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ep10 val_rocauc=0.51600 val_adapt_rocauc=0.51600 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.54994 val_adapt_rocauc=0.54994 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.53576 val_adapt_rocauc=0.53552 adapt_steps=7.83 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.55033 val_adapt_rocauc=0.55033 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.55437 val_adapt_rocauc=0.55437 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.60254 val_adapt_rocauc=0.60254 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep70 val_rocauc=0.58756 val_adapt_rocauc=0.58756 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep80 val_rocauc=0.60754 val_adapt_rocauc=0.60754 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep90 val_rocauc=0.59698 val_adapt_rocauc=0.59698 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep100 val_rocauc=0.59673 val_adapt_rocauc=0.59673 adapt_steps=8.00 halt=0.12 train_steps=4.50
[ogbg-molsider_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.6075447846476244} test={'rocauc': 0.5810477512085702} adaptive={'rocauc': 0.5810477512085702} steps=8.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molsider view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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=0.54584 val_adapt_rocauc=0.54577 adapt_steps=7.98 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.58611 val_adapt_rocauc=0.58611 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.59127 val_adapt_rocauc=0.59127 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.57511 val_adapt_rocauc=0.57438 adapt_steps=7.84 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.58186 val_adapt_rocauc=0.58186 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.56772 val_adapt_rocauc=0.56772 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep70 val_rocauc=0.59297 val_adapt_rocauc=0.59297 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep80 val_rocauc=0.62339 val_adapt_rocauc=0.62339 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep90 val_rocauc=0.62819 val_adapt_rocauc=0.62813 adapt_steps=7.90 halt=0.12 train_steps=4.50
ep100 val_rocauc=0.63343 val_adapt_rocauc=0.63420 adapt_steps=7.97 halt=0.12 train_steps=4.50
[ogbg-molsider_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.6334288171779305} test={'rocauc': 0.6299766632454395} adaptive={'rocauc': 0.6305843217920319} steps=7.909090909090909
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molsider view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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=0.50898 val_adapt_rocauc=0.50898 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.53439 val_adapt_rocauc=0.53439 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.55399 val_adapt_rocauc=0.55399 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.51743 val_adapt_rocauc=0.51743 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.56124 val_adapt_rocauc=0.56124 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.58333 val_adapt_rocauc=0.58333 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep70 val_rocauc=0.58471 val_adapt_rocauc=0.58471 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep80 val_rocauc=0.59340 val_adapt_rocauc=0.59340 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep90 val_rocauc=0.59796 val_adapt_rocauc=0.59796 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep100 val_rocauc=0.59492 val_adapt_rocauc=0.59492 adapt_steps=8.00 halt=0.12 train_steps=4.49
[ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.5979570667859507} test={'rocauc': 0.6336766486024191} adaptive={'rocauc': 0.6336766486024191} steps=8.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molsider view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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=0.52583 val_adapt_rocauc=0.52583 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.57520 val_adapt_rocauc=0.57520 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.52761 val_adapt_rocauc=0.52761 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.53501 val_adapt_rocauc=0.53501 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.54257 val_adapt_rocauc=0.54257 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.53427 val_adapt_rocauc=0.53427 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep70 val_rocauc=0.57027 val_adapt_rocauc=0.57027 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep80 val_rocauc=0.57984 val_adapt_rocauc=0.57984 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep90 val_rocauc=0.59046 val_adapt_rocauc=0.59046 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep100 val_rocauc=0.58588 val_adapt_rocauc=0.58588 adapt_steps=8.00 halt=0.12 train_steps=4.50
[ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.5904624057788478} test={'rocauc': 0.621622401806624} adaptive={'rocauc': 0.621622401806624} steps=8.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molsider view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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=0.52148 val_adapt_rocauc=0.52148 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.53383 val_adapt_rocauc=0.53359 adapt_steps=7.96 halt=0.12 train_steps=4.49
ep30 val_rocauc=0.54880 val_adapt_rocauc=0.54880 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.59286 val_adapt_rocauc=0.59286 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.59415 val_adapt_rocauc=0.59415 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.60132 val_adapt_rocauc=0.60132 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep70 val_rocauc=0.58871 val_adapt_rocauc=0.58871 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep80 val_rocauc=0.60004 val_adapt_rocauc=0.60006 adapt_steps=7.99 halt=0.12 train_steps=4.49
ep90 val_rocauc=0.61690 val_adapt_rocauc=0.61690 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep100 val_rocauc=0.62234 val_adapt_rocauc=0.62234 adapt_steps=8.00 halt=0.12 train_steps=4.50
[ogbg-molsider_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.6223441276640819} test={'rocauc': 0.622244619371397} adaptive={'rocauc': 0.622244619371397} steps=8.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molsider view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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=0.50469 val_adapt_rocauc=0.50469 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.55043 val_adapt_rocauc=0.55043 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.56343 val_adapt_rocauc=0.56343 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep40 val_rocauc=0.56853 val_adapt_rocauc=0.56838 adapt_steps=7.95 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.56311 val_adapt_rocauc=0.56311 adapt_steps=8.00 halt=0.12 train_steps=4.48
ep60 val_rocauc=0.57671 val_adapt_rocauc=0.57673 adapt_steps=7.99 halt=0.12 train_steps=4.49
ep70 val_rocauc=0.58004 val_adapt_rocauc=0.57740 adapt_steps=7.78 halt=0.12 train_steps=4.49
ep80 val_rocauc=0.59036 val_adapt_rocauc=0.58962 adapt_steps=7.92 halt=0.12 train_steps=4.48
ep90 val_rocauc=0.59131 val_adapt_rocauc=0.59135 adapt_steps=7.94 halt=0.12 train_steps=4.48
ep100 val_rocauc=0.59335 val_adapt_rocauc=0.59096 adapt_steps=7.85 halt=0.13 train_steps=4.48
[ogbg-molsider_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.593345692093345} test={'rocauc': 0.5966615384995925} adaptive={'rocauc': 0.5964163493356076} steps=7.888111888111888
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molsider view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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=0.51332 val_adapt_rocauc=0.51332 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.49872 val_adapt_rocauc=0.49872 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.52439 val_adapt_rocauc=0.52439 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.51652 val_adapt_rocauc=0.51652 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.54453 val_adapt_rocauc=0.54453 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.56613 val_adapt_rocauc=0.56613 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.58698 val_adapt_rocauc=0.58698 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.56911 val_adapt_rocauc=0.56911 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.57175 val_adapt_rocauc=0.57175 adapt_steps=8.00 halt=0.12 train_steps=4.50
/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=0.58106 val_adapt_rocauc=0.58106 adapt_steps=8.00 halt=0.12 train_steps=4.50
[ogbg-molsider_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.5869831648034167} test={'rocauc': 0.5961753244813196} adaptive={'rocauc': 0.5962142801036087} steps=7.958041958041958
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molsider view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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=0.51655 val_adapt_rocauc=0.51655 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.53764 val_adapt_rocauc=0.53764 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep30 val_rocauc=0.58175 val_adapt_rocauc=0.58175 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.57301 val_adapt_rocauc=0.57301 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.56615 val_adapt_rocauc=0.56615 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.58257 val_adapt_rocauc=0.58257 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep70 val_rocauc=0.59759 val_adapt_rocauc=0.59759 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep80 val_rocauc=0.62601 val_adapt_rocauc=0.62601 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep90 val_rocauc=0.61042 val_adapt_rocauc=0.61042 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep100 val_rocauc=0.61180 val_adapt_rocauc=0.61180 adapt_steps=8.00 halt=0.12 train_steps=4.50
[ogbg-molsider_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.6260140078552355} test={'rocauc': 0.6259436225287444} adaptive={'rocauc': 0.6259436225287444} steps=8.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[task] ogbg-molbace on cuda:3
[run] ogbg-molbace view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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
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Processing...
Extracting /home/yurenh2/rrog-gnn-runner/data/ogb/bace.zip
Loading necessary files...
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/home/yurenh2/miniconda3/lib/python3.13/site-packages/ogb/graphproppred/dataset_pyg.py:156: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:213.)
  g.y = torch.from_numpy(graph_label[i]).view(1,-1).to(torch.long)
Done!
Saving...
ep10 val_rocauc=0.52894 val_adapt_rocauc=0.53736 adapt_steps=2.04 halt=0.34 train_steps=2.42
ep20 val_rocauc=0.61941 val_adapt_rocauc=0.62161 adapt_steps=2.00 halt=0.46 train_steps=1.68
ep30 val_rocauc=0.53260 val_adapt_rocauc=0.65385 adapt_steps=2.09 halt=0.44 train_steps=1.75
ep40 val_rocauc=0.61319 val_adapt_rocauc=0.66703 adapt_steps=2.00 halt=0.47 train_steps=1.66
ep50 val_rocauc=0.59048 val_adapt_rocauc=0.58315 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep60 val_rocauc=0.66300 val_adapt_rocauc=0.69487 adapt_steps=2.09 halt=0.47 train_steps=1.60
ep70 val_rocauc=0.59011 val_adapt_rocauc=0.62601 adapt_steps=2.00 halt=0.48 train_steps=1.55
ep80 val_rocauc=0.62308 val_adapt_rocauc=0.64579 adapt_steps=2.00 halt=0.47 train_steps=1.59
ep90 val_rocauc=0.60000 val_adapt_rocauc=0.61868 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep100 val_rocauc=0.60549 val_adapt_rocauc=0.61355 adapt_steps=2.01 halt=0.47 train_steps=1.57
[ogbg-molbace_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.6630036630036631} test={'rocauc': 0.7275256477134411} adaptive={'rocauc': 0.7369153190749435} steps=2.0526315789473686
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbace_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbace view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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=0.66154 val_adapt_rocauc=0.68828 adapt_steps=2.16 halt=0.45 train_steps=1.71
ep20 val_rocauc=0.65604 val_adapt_rocauc=0.70476 adapt_steps=2.08 halt=0.47 train_steps=1.66
ep30 val_rocauc=0.57875 val_adapt_rocauc=0.62674 adapt_steps=2.04 halt=0.44 train_steps=1.81
ep40 val_rocauc=0.56337 val_adapt_rocauc=0.58608 adapt_steps=2.02 halt=0.47 train_steps=1.59
ep50 val_rocauc=0.59084 val_adapt_rocauc=0.62527 adapt_steps=2.01 halt=0.46 train_steps=1.60
ep60 val_rocauc=0.57289 val_adapt_rocauc=0.62161 adapt_steps=2.01 halt=0.48 train_steps=1.58
ep70 val_rocauc=0.57399 val_adapt_rocauc=0.60659 adapt_steps=2.01 halt=0.48 train_steps=1.55
ep80 val_rocauc=0.54762 val_adapt_rocauc=0.59560 adapt_steps=2.01 halt=0.48 train_steps=1.59
ep90 val_rocauc=0.55861 val_adapt_rocauc=0.59634 adapt_steps=2.01 halt=0.48 train_steps=1.57
ep100 val_rocauc=0.56264 val_adapt_rocauc=0.60403 adapt_steps=2.00 halt=0.47 train_steps=1.57
[ogbg-molbace_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=10 val={'rocauc': 0.6615384615384615} test={'rocauc': 0.4418362023995827} adaptive={'rocauc': 0.5362545644235784} steps=2.8421052631578947
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbace_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbace view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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=0.54505 val_adapt_rocauc=0.57875 adapt_steps=2.06 halt=0.44 train_steps=1.70
ep20 val_rocauc=0.58388 val_adapt_rocauc=0.63223 adapt_steps=2.44 halt=0.47 train_steps=1.62
ep30 val_rocauc=0.58168 val_adapt_rocauc=0.58205 adapt_steps=2.07 halt=0.47 train_steps=1.58
ep40 val_rocauc=0.56923 val_adapt_rocauc=0.66410 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep50 val_rocauc=0.59011 val_adapt_rocauc=0.58022 adapt_steps=2.07 halt=0.47 train_steps=1.57
ep60 val_rocauc=0.60037 val_adapt_rocauc=0.59194 adapt_steps=2.03 halt=0.48 train_steps=1.60
ep70 val_rocauc=0.64396 val_adapt_rocauc=0.62271 adapt_steps=2.00 halt=0.48 train_steps=1.55
ep80 val_rocauc=0.63993 val_adapt_rocauc=0.62711 adapt_steps=2.00 halt=0.48 train_steps=1.59
ep90 val_rocauc=0.63883 val_adapt_rocauc=0.62967 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep100 val_rocauc=0.64322 val_adapt_rocauc=0.62491 adapt_steps=2.00 halt=0.47 train_steps=1.57
[ogbg-molbace_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.643956043956044} test={'rocauc': 0.7117023126412798} adaptive={'rocauc': 0.7499565292992523} steps=2.013157894736842
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbace_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbace view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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=0.64799 val_adapt_rocauc=0.66227 adapt_steps=2.66 halt=0.44 train_steps=1.78
ep20 val_rocauc=0.64579 val_adapt_rocauc=0.62674 adapt_steps=2.08 halt=0.43 train_steps=1.80
ep30 val_rocauc=0.65458 val_adapt_rocauc=0.66300 adapt_steps=2.01 halt=0.47 train_steps=1.62
ep40 val_rocauc=0.61941 val_adapt_rocauc=0.60806 adapt_steps=2.01 halt=0.46 train_steps=1.67
ep50 val_rocauc=0.58645 val_adapt_rocauc=0.64908 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep60 val_rocauc=0.57399 val_adapt_rocauc=0.57363 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep70 val_rocauc=0.62161 val_adapt_rocauc=0.63114 adapt_steps=2.00 halt=0.48 train_steps=1.55
ep80 val_rocauc=0.62930 val_adapt_rocauc=0.64286 adapt_steps=2.00 halt=0.48 train_steps=1.59
ep90 val_rocauc=0.63553 val_adapt_rocauc=0.63223 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep100 val_rocauc=0.63736 val_adapt_rocauc=0.63480 adapt_steps=2.00 halt=0.47 train_steps=1.57
[ogbg-molbace_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.6545787545787546} test={'rocauc': 0.8191618848895844} adaptive={'rocauc': 0.8142931664058426} steps=2.111842105263158
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbace_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbace view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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=0.67802 val_adapt_rocauc=0.70293 adapt_steps=2.01 halt=0.44 train_steps=1.78
ep20 val_rocauc=0.55751 val_adapt_rocauc=0.55348 adapt_steps=2.03 halt=0.47 train_steps=1.61
ep30 val_rocauc=0.66337 val_adapt_rocauc=0.66300 adapt_steps=2.01 halt=0.47 train_steps=1.61
ep40 val_rocauc=0.68901 val_adapt_rocauc=0.67766 adapt_steps=2.09 halt=0.46 train_steps=1.66
ep50 val_rocauc=0.62857 val_adapt_rocauc=0.71502 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep60 val_rocauc=0.66703 val_adapt_rocauc=0.67033 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep70 val_rocauc=0.69267 val_adapt_rocauc=0.69780 adapt_steps=2.00 halt=0.48 train_steps=1.55
ep80 val_rocauc=0.67766 val_adapt_rocauc=0.66374 adapt_steps=2.00 halt=0.48 train_steps=1.59
ep90 val_rocauc=0.67143 val_adapt_rocauc=0.65238 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep100 val_rocauc=0.68095 val_adapt_rocauc=0.65311 adapt_steps=2.00 halt=0.47 train_steps=1.57
[ogbg-molbace_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.6926739926739928} test={'rocauc': 0.6736219787862981} adaptive={'rocauc': 0.734828725439054} steps=2.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbace_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbace view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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=0.68022 val_adapt_rocauc=0.67143 adapt_steps=2.11 halt=0.48 train_steps=1.58
ep20 val_rocauc=0.64139 val_adapt_rocauc=0.67692 adapt_steps=2.05 halt=0.48 train_steps=1.60
ep30 val_rocauc=0.63516 val_adapt_rocauc=0.63077 adapt_steps=2.02 halt=0.47 train_steps=1.57
ep40 val_rocauc=0.59158 val_adapt_rocauc=0.65128 adapt_steps=2.00 halt=0.48 train_steps=1.59
ep50 val_rocauc=0.51758 val_adapt_rocauc=0.55788 adapt_steps=2.01 halt=0.47 train_steps=1.56
ep60 val_rocauc=0.63626 val_adapt_rocauc=0.63700 adapt_steps=2.00 halt=0.48 train_steps=1.58
ep70 val_rocauc=0.56300 val_adapt_rocauc=0.62271 adapt_steps=2.00 halt=0.48 train_steps=1.55
ep80 val_rocauc=0.55751 val_adapt_rocauc=0.62967 adapt_steps=2.00 halt=0.48 train_steps=1.59
ep90 val_rocauc=0.55495 val_adapt_rocauc=0.61795 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep100 val_rocauc=0.54652 val_adapt_rocauc=0.61722 adapt_steps=2.00 halt=0.47 train_steps=1.57
[ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=10 val={'rocauc': 0.6802197802197802} test={'rocauc': 0.6833594157537818} adaptive={'rocauc': 0.7826464962615197} steps=2.0921052631578947
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbace view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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=0.56447 val_adapt_rocauc=0.56557 adapt_steps=2.00 halt=0.35 train_steps=2.27
/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=0.65751 val_adapt_rocauc=0.67289 adapt_steps=2.16 halt=0.38 train_steps=2.12
/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=0.65897 val_adapt_rocauc=0.65018 adapt_steps=2.56 halt=0.40 train_steps=1.88
/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=0.45604 val_adapt_rocauc=0.66996 adapt_steps=2.13 halt=0.46 train_steps=1.68
/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=0.49560 val_adapt_rocauc=0.68791 adapt_steps=2.13 halt=0.44 train_steps=1.75
/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=0.46227 val_adapt_rocauc=0.68132 adapt_steps=2.05 halt=0.47 train_steps=1.65
/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=0.64432 val_adapt_rocauc=0.67912 adapt_steps=2.00 halt=0.47 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=0.60220 val_adapt_rocauc=0.64359 adapt_steps=2.04 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(
ep90 val_rocauc=0.61136 val_adapt_rocauc=0.68535 adapt_steps=2.01 halt=0.47 train_steps=1.62
/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=0.61978 val_adapt_rocauc=0.68974 adapt_steps=2.01 halt=0.46 train_steps=1.61
[ogbg-molbace_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.658974358974359} test={'rocauc': 0.7480438184663536} adaptive={'rocauc': 0.7546513649800034} steps=2.6315789473684212
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbace_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molbace view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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=0.61282 val_adapt_rocauc=0.59304 adapt_steps=2.04 halt=0.43 train_steps=1.89
ep20 val_rocauc=0.68938 val_adapt_rocauc=0.61062 adapt_steps=2.04 halt=0.46 train_steps=1.69
ep30 val_rocauc=0.66740 val_adapt_rocauc=0.70366 adapt_steps=2.12 halt=0.47 train_steps=1.61
ep40 val_rocauc=0.64212 val_adapt_rocauc=0.67582 adapt_steps=2.01 halt=0.47 train_steps=1.67
ep50 val_rocauc=0.55604 val_adapt_rocauc=0.57802 adapt_steps=2.00 halt=0.46 train_steps=1.61
ep60 val_rocauc=0.69414 val_adapt_rocauc=0.69597 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep70 val_rocauc=0.61026 val_adapt_rocauc=0.63590 adapt_steps=2.00 halt=0.48 train_steps=1.55
ep80 val_rocauc=0.66410 val_adapt_rocauc=0.66300 adapt_steps=2.00 halt=0.48 train_steps=1.59
ep90 val_rocauc=0.65934 val_adapt_rocauc=0.64835 adapt_steps=2.00 halt=0.48 train_steps=1.57
ep100 val_rocauc=0.66850 val_adapt_rocauc=0.65128 adapt_steps=2.00 halt=0.47 train_steps=1.57
[ogbg-molbace_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.6941391941391942} test={'rocauc': 0.7231785776386715} adaptive={'rocauc': 0.7640410363415059} steps=2.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbace_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[task] ogbg-moltox21 on cuda:3
[run] ogbg-moltox21 view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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
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Saving...
ep10 val_rocauc=0.71371 val_adapt_rocauc=0.69966 adapt_steps=3.11 halt=0.29 train_steps=2.95
ep20 val_rocauc=0.63487 val_adapt_rocauc=0.60317 adapt_steps=2.49 halt=0.29 train_steps=2.93
ep30 val_rocauc=0.71755 val_adapt_rocauc=0.70846 adapt_steps=3.98 halt=0.28 train_steps=2.98
ep40 val_rocauc=0.71255 val_adapt_rocauc=0.68936 adapt_steps=3.00 halt=0.29 train_steps=2.94
ep50 val_rocauc=0.72362 val_adapt_rocauc=0.72481 adapt_steps=3.24 halt=0.28 train_steps=3.16
ep60 val_rocauc=0.71946 val_adapt_rocauc=0.72876 adapt_steps=3.93 halt=0.28 train_steps=3.08
ep70 val_rocauc=0.72799 val_adapt_rocauc=0.73083 adapt_steps=3.71 halt=0.28 train_steps=3.13
ep80 val_rocauc=0.75666 val_adapt_rocauc=0.76164 adapt_steps=4.28 halt=0.29 train_steps=3.06
ep90 val_rocauc=0.75393 val_adapt_rocauc=0.76254 adapt_steps=3.78 halt=0.29 train_steps=3.06
ep100 val_rocauc=0.76113 val_adapt_rocauc=0.76936 adapt_steps=3.90 halt=0.29 train_steps=3.04
[ogbg-moltox21_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.7611296131897838} test={'rocauc': 0.7089667909334546} adaptive={'rocauc': 0.7126552901719999} steps=3.826530612244898
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-moltox21_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-moltox21 view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.59058 val_adapt_rocauc=0.61606 adapt_steps=2.60 halt=0.29 train_steps=2.95
ep20 val_rocauc=0.73407 val_adapt_rocauc=0.73772 adapt_steps=4.45 halt=0.28 train_steps=3.03
ep30 val_rocauc=0.66805 val_adapt_rocauc=0.67628 adapt_steps=2.39 halt=0.31 train_steps=2.83
ep40 val_rocauc=0.75097 val_adapt_rocauc=0.75197 adapt_steps=3.77 halt=0.30 train_steps=2.93
ep50 val_rocauc=0.75364 val_adapt_rocauc=0.75297 adapt_steps=2.95 halt=0.32 train_steps=2.68
ep60 val_rocauc=0.76552 val_adapt_rocauc=0.77043 adapt_steps=3.76 halt=0.31 train_steps=2.86
ep70 val_rocauc=0.75776 val_adapt_rocauc=0.75709 adapt_steps=3.80 halt=0.34 train_steps=2.62
ep80 val_rocauc=0.75257 val_adapt_rocauc=0.76572 adapt_steps=2.98 halt=0.35 train_steps=2.57
ep90 val_rocauc=0.75894 val_adapt_rocauc=0.76629 adapt_steps=2.81 halt=0.37 train_steps=2.40
ep100 val_rocauc=0.75414 val_adapt_rocauc=0.76330 adapt_steps=2.75 halt=0.37 train_steps=2.36
[ogbg-moltox21_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.7655200134252199} test={'rocauc': 0.7134396419831454} adaptive={'rocauc': 0.7234036772214454} steps=3.764030612244898
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-moltox21_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-moltox21 view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.66429 val_adapt_rocauc=0.65320 adapt_steps=3.43 halt=0.30 train_steps=2.88
ep20 val_rocauc=0.68343 val_adapt_rocauc=0.70058 adapt_steps=2.30 halt=0.28 train_steps=3.01
ep30 val_rocauc=0.74431 val_adapt_rocauc=0.74038 adapt_steps=3.91 halt=0.28 train_steps=3.06
ep40 val_rocauc=0.77575 val_adapt_rocauc=0.78093 adapt_steps=3.57 halt=0.29 train_steps=3.01
ep50 val_rocauc=0.76411 val_adapt_rocauc=0.76469 adapt_steps=3.98 halt=0.28 train_steps=3.10
ep60 val_rocauc=0.74714 val_adapt_rocauc=0.75263 adapt_steps=4.61 halt=0.29 train_steps=2.98
ep70 val_rocauc=0.76848 val_adapt_rocauc=0.77476 adapt_steps=3.52 halt=0.31 train_steps=2.93
ep80 val_rocauc=0.77621 val_adapt_rocauc=0.77758 adapt_steps=3.50 halt=0.30 train_steps=2.90
ep90 val_rocauc=0.77792 val_adapt_rocauc=0.77851 adapt_steps=3.40 halt=0.32 train_steps=2.79
ep100 val_rocauc=0.77758 val_adapt_rocauc=0.77971 adapt_steps=3.31 halt=0.32 train_steps=2.76
[ogbg-moltox21_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.7779156296831152} test={'rocauc': 0.7359551442188313} adaptive={'rocauc': 0.7477856114096909} steps=3.485969387755102
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-moltox21_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-moltox21 view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.65297 val_adapt_rocauc=0.67456 adapt_steps=3.02 halt=0.29 train_steps=2.89
ep20 val_rocauc=0.58464 val_adapt_rocauc=0.57802 adapt_steps=2.47 halt=0.28 train_steps=3.08
ep30 val_rocauc=0.67479 val_adapt_rocauc=0.66288 adapt_steps=2.71 halt=0.28 train_steps=3.03
ep40 val_rocauc=0.73567 val_adapt_rocauc=0.72464 adapt_steps=4.40 halt=0.29 train_steps=2.94
ep50 val_rocauc=0.74825 val_adapt_rocauc=0.74753 adapt_steps=3.90 halt=0.30 train_steps=2.89
ep60 val_rocauc=0.74074 val_adapt_rocauc=0.74859 adapt_steps=3.41 halt=0.29 train_steps=3.03
ep70 val_rocauc=0.76016 val_adapt_rocauc=0.76365 adapt_steps=3.69 halt=0.32 train_steps=2.78
ep80 val_rocauc=0.76849 val_adapt_rocauc=0.77008 adapt_steps=3.87 halt=0.32 train_steps=2.79
ep90 val_rocauc=0.76637 val_adapt_rocauc=0.76973 adapt_steps=3.59 halt=0.31 train_steps=2.86
ep100 val_rocauc=0.77008 val_adapt_rocauc=0.77327 adapt_steps=3.50 halt=0.32 train_steps=2.79
[ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.7700778158549199} test={'rocauc': 0.7162575064186166} adaptive={'rocauc': 0.7254468026027986} steps=3.506377551020408
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-moltox21 view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.67403 val_adapt_rocauc=0.66074 adapt_steps=5.50 halt=0.30 train_steps=2.85
ep20 val_rocauc=0.72382 val_adapt_rocauc=0.72638 adapt_steps=4.50 halt=0.29 train_steps=2.98
ep30 val_rocauc=0.74375 val_adapt_rocauc=0.74426 adapt_steps=4.91 halt=0.30 train_steps=2.93
ep40 val_rocauc=0.76136 val_adapt_rocauc=0.75836 adapt_steps=4.87 halt=0.30 train_steps=2.95
ep50 val_rocauc=0.77110 val_adapt_rocauc=0.76887 adapt_steps=3.39 halt=0.31 train_steps=2.88
ep60 val_rocauc=0.76514 val_adapt_rocauc=0.76428 adapt_steps=3.77 halt=0.30 train_steps=2.93
ep70 val_rocauc=0.77659 val_adapt_rocauc=0.78194 adapt_steps=3.61 halt=0.33 train_steps=2.73
ep80 val_rocauc=0.78163 val_adapt_rocauc=0.78200 adapt_steps=3.14 halt=0.32 train_steps=2.79
ep90 val_rocauc=0.77395 val_adapt_rocauc=0.77600 adapt_steps=3.46 halt=0.34 train_steps=2.63
ep100 val_rocauc=0.77629 val_adapt_rocauc=0.78067 adapt_steps=3.51 halt=0.34 train_steps=2.67
[ogbg-moltox21_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7816268997660386} test={'rocauc': 0.7115162457844392} adaptive={'rocauc': 0.7190898385325345} steps=3.205357142857143
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-moltox21_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-moltox21 view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.67337 val_adapt_rocauc=0.68763 adapt_steps=3.64 halt=0.31 train_steps=2.73
ep20 val_rocauc=0.70783 val_adapt_rocauc=0.71959 adapt_steps=3.12 halt=0.30 train_steps=2.88
ep30 val_rocauc=0.70171 val_adapt_rocauc=0.71441 adapt_steps=3.00 halt=0.30 train_steps=2.88
ep40 val_rocauc=0.71979 val_adapt_rocauc=0.72206 adapt_steps=3.04 halt=0.31 train_steps=2.84
ep50 val_rocauc=0.71376 val_adapt_rocauc=0.72112 adapt_steps=2.58 halt=0.32 train_steps=2.70
ep60 val_rocauc=0.71062 val_adapt_rocauc=0.72892 adapt_steps=2.53 halt=0.37 train_steps=2.29
ep70 val_rocauc=0.72376 val_adapt_rocauc=0.73807 adapt_steps=2.52 halt=0.38 train_steps=2.29
ep80 val_rocauc=0.71834 val_adapt_rocauc=0.74502 adapt_steps=2.27 halt=0.38 train_steps=2.25
ep90 val_rocauc=0.71743 val_adapt_rocauc=0.73867 adapt_steps=2.35 halt=0.40 train_steps=2.13
ep100 val_rocauc=0.72314 val_adapt_rocauc=0.74270 adapt_steps=2.30 halt=0.39 train_steps=2.20
[ogbg-moltox21_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.7237576716525247} test={'rocauc': 0.6822930471359431} adaptive={'rocauc': 0.7137838364459371} steps=2.63265306122449
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-moltox21_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-moltox21 view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.67622 val_adapt_rocauc=0.68638 adapt_steps=2.73 halt=0.29 train_steps=2.84
/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=0.70913 val_adapt_rocauc=0.71306 adapt_steps=3.51 halt=0.30 train_steps=2.87
/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=0.72224 val_adapt_rocauc=0.71267 adapt_steps=3.47 halt=0.29 train_steps=2.94
/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=0.72374 val_adapt_rocauc=0.72731 adapt_steps=2.78 halt=0.30 train_steps=2.99
/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=0.68200 val_adapt_rocauc=0.67391 adapt_steps=2.33 halt=0.29 train_steps=2.98
/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=0.67336 val_adapt_rocauc=0.67501 adapt_steps=6.05 halt=0.31 train_steps=2.84
/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=0.73655 val_adapt_rocauc=0.74091 adapt_steps=3.35 halt=0.30 train_steps=2.92
/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=0.74975 val_adapt_rocauc=0.75746 adapt_steps=4.96 halt=0.29 train_steps=3.02
/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=0.75471 val_adapt_rocauc=0.76064 adapt_steps=4.10 halt=0.29 train_steps=3.02
/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=0.75208 val_adapt_rocauc=0.76070 adapt_steps=3.94 halt=0.30 train_steps=2.96
[ogbg-moltox21_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.7547109180572619} test={'rocauc': 0.6948890646179361} adaptive={'rocauc': 0.7075025478713003} steps=4.220663265306122
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-moltox21_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-moltox21 view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.70487 val_adapt_rocauc=0.70394 adapt_steps=5.69 halt=0.30 train_steps=2.83
ep20 val_rocauc=0.69675 val_adapt_rocauc=0.69557 adapt_steps=4.74 halt=0.29 train_steps=2.99
ep30 val_rocauc=0.66699 val_adapt_rocauc=0.63127 adapt_steps=5.03 halt=0.28 train_steps=3.06
ep40 val_rocauc=0.74485 val_adapt_rocauc=0.75016 adapt_steps=3.17 halt=0.29 train_steps=2.99
ep50 val_rocauc=0.76238 val_adapt_rocauc=0.76296 adapt_steps=3.47 halt=0.30 train_steps=2.94
ep60 val_rocauc=0.75613 val_adapt_rocauc=0.75760 adapt_steps=3.12 halt=0.30 train_steps=2.92
ep70 val_rocauc=0.75660 val_adapt_rocauc=0.75749 adapt_steps=3.60 halt=0.33 train_steps=2.70
ep80 val_rocauc=0.77965 val_adapt_rocauc=0.78270 adapt_steps=3.04 halt=0.33 train_steps=2.71
ep90 val_rocauc=0.77346 val_adapt_rocauc=0.77623 adapt_steps=3.25 halt=0.35 train_steps=2.54
ep100 val_rocauc=0.77053 val_adapt_rocauc=0.77614 adapt_steps=3.10 halt=0.36 train_steps=2.49
[ogbg-moltox21_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7796493691111651} test={'rocauc': 0.7201514791915015} adaptive={'rocauc': 0.7223894069034307} steps=3.0778061224489797
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-moltox21_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[task] ogbg-molclintox on cuda:3
[run] ogbg-molclintox view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --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
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Saving...
ep10 val_rocauc=0.60624 val_adapt_rocauc=0.74118 adapt_steps=2.01 halt=0.40 train_steps=2.12
ep20 val_rocauc=0.78931 val_adapt_rocauc=0.78193 adapt_steps=2.51 halt=0.46 train_steps=1.67
ep30 val_rocauc=0.87347 val_adapt_rocauc=0.88131 adapt_steps=2.23 halt=0.43 train_steps=1.76
ep40 val_rocauc=0.90655 val_adapt_rocauc=0.89215 adapt_steps=2.11 halt=0.43 train_steps=1.90
ep50 val_rocauc=0.90059 val_adapt_rocauc=0.89949 adapt_steps=2.04 halt=0.45 train_steps=1.68
ep60 val_rocauc=0.92569 val_adapt_rocauc=0.91470 adapt_steps=2.04 halt=0.46 train_steps=1.73
ep70 val_rocauc=0.85343 val_adapt_rocauc=0.84051 adapt_steps=2.00 halt=0.47 train_steps=1.58
ep80 val_rocauc=0.90430 val_adapt_rocauc=0.88959 adapt_steps=2.00 halt=0.47 train_steps=1.61
ep90 val_rocauc=0.91698 val_adapt_rocauc=0.90556 adapt_steps=2.01 halt=0.47 train_steps=1.59
ep100 val_rocauc=0.89472 val_adapt_rocauc=0.88990 adapt_steps=2.01 halt=0.46 train_steps=1.67
[ogbg-molclintox_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.925691092944614} test={'rocauc': 0.880287943558197} adaptive={'rocauc': 0.8739417161922636} steps=2.0675675675675675
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molclintox_gin_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --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=0.82183 val_adapt_rocauc=0.86297 adapt_steps=2.22 halt=0.43 train_steps=1.73
ep20 val_rocauc=0.76252 val_adapt_rocauc=0.86505 adapt_steps=2.26 halt=0.47 train_steps=1.63
ep30 val_rocauc=0.83688 val_adapt_rocauc=0.89876 adapt_steps=2.09 halt=0.45 train_steps=1.62
ep40 val_rocauc=0.81513 val_adapt_rocauc=0.86423 adapt_steps=2.01 halt=0.46 train_steps=1.65
ep50 val_rocauc=0.93016 val_adapt_rocauc=0.95113 adapt_steps=2.00 halt=0.47 train_steps=1.62
ep60 val_rocauc=0.96179 val_adapt_rocauc=0.96556 adapt_steps=2.00 halt=0.47 train_steps=1.64
ep70 val_rocauc=0.94241 val_adapt_rocauc=0.94934 adapt_steps=2.00 halt=0.47 train_steps=1.64
ep80 val_rocauc=0.97166 val_adapt_rocauc=0.96956 adapt_steps=2.00 halt=0.46 train_steps=1.63
ep90 val_rocauc=0.97588 val_adapt_rocauc=0.97344 adapt_steps=2.00 halt=0.46 train_steps=1.62
ep100 val_rocauc=0.97353 val_adapt_rocauc=0.96875 adapt_steps=2.00 halt=0.45 train_steps=1.63
[ogbg-molclintox_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.9758757674250633} test={'rocauc': 0.8739825530879644} adaptive={'rocauc': 0.8682749452611824} steps=2.054054054054054
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molclintox_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --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=0.68124 val_adapt_rocauc=0.73447 adapt_steps=2.00 halt=0.43 train_steps=1.98
ep20 val_rocauc=0.74983 val_adapt_rocauc=0.82573 adapt_steps=2.00 halt=0.45 train_steps=1.75
ep30 val_rocauc=0.83839 val_adapt_rocauc=0.86462 adapt_steps=2.07 halt=0.45 train_steps=1.69
ep40 val_rocauc=0.85645 val_adapt_rocauc=0.90685 adapt_steps=2.11 halt=0.47 train_steps=1.61
ep50 val_rocauc=0.82385 val_adapt_rocauc=0.82321 adapt_steps=2.01 halt=0.47 train_steps=1.56
ep60 val_rocauc=0.87257 val_adapt_rocauc=0.89450 adapt_steps=2.02 halt=0.47 train_steps=1.61
ep70 val_rocauc=0.93091 val_adapt_rocauc=0.93933 adapt_steps=2.01 halt=0.47 train_steps=1.61
ep80 val_rocauc=0.91830 val_adapt_rocauc=0.92507 adapt_steps=2.03 halt=0.47 train_steps=1.67
ep90 val_rocauc=0.91036 val_adapt_rocauc=0.91478 adapt_steps=2.01 halt=0.47 train_steps=1.67
ep100 val_rocauc=0.91573 val_adapt_rocauc=0.91911 adapt_steps=2.01 halt=0.47 train_steps=1.63
[ogbg-molclintox_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.9309095833743721} test={'rocauc': 0.8809821707851111} adaptive={'rocauc': 0.9033008375907969} steps=2.0878378378378377
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molclintox_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --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=0.64072 val_adapt_rocauc=0.74493 adapt_steps=2.03 halt=0.41 train_steps=2.16
ep20 val_rocauc=0.69510 val_adapt_rocauc=0.88005 adapt_steps=2.13 halt=0.47 train_steps=1.63
ep30 val_rocauc=0.86787 val_adapt_rocauc=0.86841 adapt_steps=2.00 halt=0.46 train_steps=1.64
ep40 val_rocauc=0.79619 val_adapt_rocauc=0.83481 adapt_steps=2.00 halt=0.46 train_steps=1.68
ep50 val_rocauc=0.81643 val_adapt_rocauc=0.85514 adapt_steps=2.04 halt=0.44 train_steps=1.79
ep60 val_rocauc=0.85361 val_adapt_rocauc=0.91327 adapt_steps=2.00 halt=0.48 train_steps=1.59
ep70 val_rocauc=0.85772 val_adapt_rocauc=0.91744 adapt_steps=2.00 halt=0.47 train_steps=1.59
ep80 val_rocauc=0.84607 val_adapt_rocauc=0.91703 adapt_steps=2.00 halt=0.46 train_steps=1.63
ep90 val_rocauc=0.86604 val_adapt_rocauc=0.92838 adapt_steps=2.00 halt=0.47 train_steps=1.61
ep100 val_rocauc=0.85561 val_adapt_rocauc=0.91784 adapt_steps=2.00 halt=0.46 train_steps=1.62
[ogbg-molclintox_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.8678740273810697} test={'rocauc': 0.8432636499496056} adaptive={'rocauc': 0.8344932749452612} steps=2.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molclintox_tag_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --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=0.71091 val_adapt_rocauc=0.73332 adapt_steps=2.07 halt=0.42 train_steps=1.94
ep20 val_rocauc=0.77725 val_adapt_rocauc=0.79820 adapt_steps=2.14 halt=0.46 train_steps=1.73
ep30 val_rocauc=0.85712 val_adapt_rocauc=0.83995 adapt_steps=2.12 halt=0.44 train_steps=1.69
ep40 val_rocauc=0.86597 val_adapt_rocauc=0.88025 adapt_steps=2.14 halt=0.45 train_steps=1.71
ep50 val_rocauc=0.83623 val_adapt_rocauc=0.85307 adapt_steps=2.01 halt=0.46 train_steps=1.61
ep60 val_rocauc=0.84827 val_adapt_rocauc=0.85414 adapt_steps=2.03 halt=0.47 train_steps=1.66
ep70 val_rocauc=0.86190 val_adapt_rocauc=0.88018 adapt_steps=2.00 halt=0.47 train_steps=1.62
ep80 val_rocauc=0.81287 val_adapt_rocauc=0.85623 adapt_steps=2.04 halt=0.45 train_steps=1.78
ep90 val_rocauc=0.81184 val_adapt_rocauc=0.85519 adapt_steps=2.03 halt=0.46 train_steps=1.73
ep100 val_rocauc=0.80130 val_adapt_rocauc=0.84348 adapt_steps=2.05 halt=0.45 train_steps=1.75
[ogbg-molclintox_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.8659657244164286} test={'rocauc': 0.805447815660515} adaptive={'rocauc': 0.8240981128140966} steps=2.2094594594594597
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molclintox_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --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=0.76585 val_adapt_rocauc=0.86739 adapt_steps=2.02 halt=0.45 train_steps=1.70
ep20 val_rocauc=0.86039 val_adapt_rocauc=0.86324 adapt_steps=2.00 halt=0.47 train_steps=1.62
ep30 val_rocauc=0.90459 val_adapt_rocauc=0.89663 adapt_steps=2.02 halt=0.47 train_steps=1.59
ep40 val_rocauc=0.90971 val_adapt_rocauc=0.88686 adapt_steps=2.00 halt=0.45 train_steps=1.69
ep50 val_rocauc=0.93832 val_adapt_rocauc=0.92655 adapt_steps=2.00 halt=0.46 train_steps=1.61
ep60 val_rocauc=0.89696 val_adapt_rocauc=0.91244 adapt_steps=2.03 halt=0.47 train_steps=1.65
ep70 val_rocauc=0.92770 val_adapt_rocauc=0.92621 adapt_steps=2.01 halt=0.47 train_steps=1.62
ep80 val_rocauc=0.93654 val_adapt_rocauc=0.94478 adapt_steps=2.01 halt=0.46 train_steps=1.69
ep90 val_rocauc=0.93512 val_adapt_rocauc=0.94803 adapt_steps=2.01 halt=0.46 train_steps=1.63
ep100 val_rocauc=0.93911 val_adapt_rocauc=0.94431 adapt_steps=2.00 halt=0.46 train_steps=1.64
[ogbg-molclintox_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.9391148757345941} test={'rocauc': 0.8412244117749279} adaptive={'rocauc': 0.9026361519480067} steps=2.0405405405405403
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molclintox_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --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=0.73449 val_adapt_rocauc=0.82290 adapt_steps=2.02 halt=0.44 train_steps=1.88
/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=0.72647 val_adapt_rocauc=0.81333 adapt_steps=2.02 halt=0.41 train_steps=1.96
/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=0.69121 val_adapt_rocauc=0.81663 adapt_steps=2.03 halt=0.45 train_steps=1.67
/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=0.68050 val_adapt_rocauc=0.79323 adapt_steps=2.05 halt=0.39 train_steps=2.17
/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=0.78235 val_adapt_rocauc=0.82074 adapt_steps=2.27 halt=0.42 train_steps=1.74
/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=0.77786 val_adapt_rocauc=0.80819 adapt_steps=2.03 halt=0.44 train_steps=1.77
/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=0.80327 val_adapt_rocauc=0.80844 adapt_steps=2.07 halt=0.45 train_steps=1.65
/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=0.82184 val_adapt_rocauc=0.81128 adapt_steps=2.07 halt=0.46 train_steps=1.66
/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=0.81683 val_adapt_rocauc=0.80189 adapt_steps=2.05 halt=0.47 train_steps=1.62
/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=0.82947 val_adapt_rocauc=0.80329 adapt_steps=2.05 halt=0.46 train_steps=1.66
[ogbg-molclintox_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.8294650185495256} test={'rocauc': 0.9034242171480207} adaptive={'rocauc': 0.9194748548986897} steps=2.22972972972973
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molclintox_pna_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --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=0.86017 val_adapt_rocauc=0.85805 adapt_steps=2.00 halt=0.44 train_steps=1.96
ep20 val_rocauc=0.81251 val_adapt_rocauc=0.81417 adapt_steps=2.05 halt=0.46 train_steps=1.74
ep30 val_rocauc=0.83266 val_adapt_rocauc=0.88528 adapt_steps=2.09 halt=0.44 train_steps=1.83
ep40 val_rocauc=0.89601 val_adapt_rocauc=0.90433 adapt_steps=2.14 halt=0.47 train_steps=1.62
ep50 val_rocauc=0.84727 val_adapt_rocauc=0.87116 adapt_steps=2.09 halt=0.46 train_steps=1.60
ep60 val_rocauc=0.85582 val_adapt_rocauc=0.90812 adapt_steps=2.07 halt=0.47 train_steps=1.67
ep70 val_rocauc=0.91150 val_adapt_rocauc=0.90620 adapt_steps=2.02 halt=0.46 train_steps=1.65
ep80 val_rocauc=0.91162 val_adapt_rocauc=0.89879 adapt_steps=2.03 halt=0.47 train_steps=1.61
ep90 val_rocauc=0.89291 val_adapt_rocauc=0.89228 adapt_steps=2.01 halt=0.47 train_steps=1.63
ep100 val_rocauc=0.89000 val_adapt_rocauc=0.88702 adapt_steps=2.02 halt=0.45 train_steps=1.68
[ogbg-molclintox_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.9116172559834532} test={'rocauc': 0.8402903763945366} adaptive={'rocauc': 0.8415754353039308} steps=2.0337837837837838
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molclintox_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_exact_lq0.1_hex0.1_qw0_h128_e100_s0.json
[done] collecting summaries

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) |

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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6802 (0.0238) | 0.6834 (-0.0589) | 0.7826 (0.0403) | 2.09 |
| ogbg-molbace | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7179 (0.0256) | 0.7672 (-0.0167) |  |  |
| ogbg-molbace | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7114 (-0.0154) | 0.7533 (-0.0436) |  |  |
| ogbg-molbace | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6652 (-0.0051) | 0.7242 (0.0000) |  |  |
| ogbg-molbace | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7026 (-0.0004) | 0.7519 (0.0118) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6615 (0.0234) | 0.4418 (-0.2975) | 0.5363 (-0.2031) | 2.84 |
| ogbg-molbace | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6894 (-0.0234) | 0.7449 (0.0123) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6630 (0.0110) | 0.7275 (-0.0061) | 0.7369 (0.0033) | 2.05 |
| ogbg-molbace | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6685 (0.0044) | 0.6994 (-0.0461) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6927 (-0.0385) | 0.6736 (-0.1299) | 0.7348 (-0.0687) | 2.00 |
| ogbg-molbace | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6703 (-0.0055) | 0.7119 (-0.0640) |  |  |
| ogbg-molbace | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7234 (-0.0187) | 0.7684 (-0.0077) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6590 (-0.0927) | 0.7480 (0.0569) | 0.7547 (0.0635) | 2.63 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6941 (-0.0231) | 0.7232 (-0.0645) | 0.7640 (-0.0236) | 2.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6440 (-0.0136) | 0.7117 (0.0151) | 0.7500 (0.0534) | 2.01 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6546 (-0.0538) | 0.8192 (0.0847) | 0.8143 (0.0798) | 2.11 |
| ogbg-molbace | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6982 (0.0319) | 0.7487 (0.0123) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8797 (-0.0349) | 0.5456 (-0.0932) | 0.5881 (-0.0507) | 2.01 |
| ogbg-molbbbp | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9415 (0.0048) | 0.6635 (-0.0016) |  |  |
| ogbg-molbbbp | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9278 (-0.0174) | 0.6659 (0.0145) |  |  |
| ogbg-molbbbp | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9400 (0.0115) | 0.6323 (0.0023) |  |  |
| ogbg-molbbbp | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9356 (0.0009) | 0.6560 (0.0235) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9429 (0.0044) | 0.6137 (-0.0542) | 0.6758 (0.0079) | 2.00 |
| ogbg-molbbbp | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9429 (-0.0119) | 0.6037 (-0.0738) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9282 (0.0031) | 0.6619 (0.0949) | 0.6693 (0.1022) | 2.08 |
| ogbg-molbbbp | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9421 (0.0098) | 0.6976 (0.0816) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9056 (-0.0212) | 0.6369 (0.0469) | 0.6416 (0.0516) | 2.12 |
| ogbg-molbbbp | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9502 (0.0019) | 0.5934 (-0.0354) |  |  |
| ogbg-molbbbp | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9488 (0.0094) | 0.6481 (0.0116) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9380 (-0.0174) | 0.6539 (0.0122) | 0.6563 (0.0146) | 2.31 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9499 (0.0317) | 0.6604 (-0.0022) | 0.6677 (0.0051) | 2.34 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9347 (0.0047) | 0.6516 (0.0277) | 0.6385 (0.0146) | 2.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9406 (-0.0071) | 0.6350 (0.0251) | 0.6147 (0.0047) | 2.01 |
| ogbg-molbbbp | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9355 (-0.0140) | 0.6221 (0.0065) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9391 (0.0875) | 0.8412 (-0.0772) | 0.9026 (-0.0158) | 2.04 |
| ogbg-molclintox | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9135 (-0.0328) | 0.8863 (0.0185) |  |  |
| ogbg-molclintox | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.8816 (-0.0112) | 0.8982 (-0.0170) |  |  |
| ogbg-molclintox | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9454 (0.0406) | 0.8430 (0.0699) |  |  |
| ogbg-molclintox | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9351 (-0.0164) | 0.8328 (-0.0164) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9759 (0.0440) | 0.8740 (-0.0192) | 0.8683 (-0.0249) | 2.05 |
| ogbg-molclintox | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9399 (-0.0421) | 0.8194 (0.0066) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9257 (-0.0290) | 0.8803 (0.0216) | 0.8739 (0.0153) | 2.07 |
| ogbg-molclintox | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9225 (-0.0127) | 0.8840 (-0.0030) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8660 (-0.0258) | 0.8054 (-0.0447) | 0.8241 (-0.0260) | 2.21 |
| ogbg-molclintox | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9579 (0.0436) | 0.8664 (-0.0217) |  |  |
| ogbg-molclintox | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9147 (-0.0104) | 0.8047 (-0.0323) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8295 (-0.0991) | 0.9034 (0.0431) | 0.9195 (0.0592) | 2.23 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9116 (-0.0128) | 0.8403 (-0.0781) | 0.8416 (-0.0768) | 2.03 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9309 (0.0114) | 0.8810 (-0.0176) | 0.9033 (0.0047) | 2.09 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8679 (-0.0558) | 0.8433 (0.0434) | 0.8345 (0.0347) | 2.00 |
| ogbg-molclintox | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9322 (0.0051) | 0.8522 (-0.0242) |  |  |
| ogbg-molesol | appnp | fixed-rrog-T1-ns3 | rmse | 1 | 1.4196 (0.1887) | 1.4929 (0.0284) |  |  |
| ogbg-molesol | arma | fixed-rrog-T1-ns3 | rmse | 1 | 1.0034 (0.0160) | 1.1272 (-0.0606) |  |  |
| ogbg-molesol | cheb | fixed-rrog-T1-ns3 | rmse | 1 | 0.9199 (0.0451) | 0.8841 (-0.0118) |  |  |
| ogbg-molesol | film | fixed-rrog-T1-ns3 | rmse | 1 | 1.0196 (0.0521) | 1.0849 (0.2047) |  |  |
| ogbg-molesol | gatv2 | fixed-rrog-T1-ns3 | rmse | 1 | 1.0018 (0.0350) | 0.9780 (0.0098) |  |  |
| ogbg-molesol | gcn | fixed-rrog-T1-ns3 | rmse | 1 | 0.9591 (0.0818) | 0.9305 (0.1856) |  |  |
| ogbg-molesol | gen | fixed-rrog-T1-ns3 | rmse | 1 | 1.0027 (0.0062) | 0.9206 (-0.0444) |  |  |
| ogbg-molesol | gin | fixed-rrog-T1-ns3 | rmse | 1 | 0.9647 (0.0540) | 1.0798 (-0.0899) |  |  |
| ogbg-molesol | gine | fixed-rrog-T1-ns3 | rmse | 1 | 1.0581 (-0.0295) | 1.0951 (-0.0144) |  |  |
| ogbg-molesol | graphconv | fixed-rrog-T1-ns3 | rmse | 1 | 1.0048 (-0.0307) | 0.9968 (-0.0236) |  |  |
| ogbg-molesol | graphsage | fixed-rrog-T1-ns3 | rmse | 1 | 0.9934 (-0.0254) | 1.0794 (-0.0757) |  |  |
| ogbg-molesol | mf | fixed-rrog-T1-ns3 | rmse | 1 | 1.0553 (0.0942) | 1.0368 (0.0271) |  |  |
| ogbg-molesol | pna | fixed-rrog-T1-ns3 | rmse | 1 | 0.9841 (-0.0725) | 0.9092 (0.0060) |  |  |
| ogbg-molesol | resgated | fixed-rrog-T1-ns3 | rmse | 1 | 0.9873 (-0.0382) | 0.8825 (0.0083) |  |  |
| ogbg-molesol | sgc | fixed-rrog-T1-ns3 | rmse | 1 | 1.0129 (0.0488) | 0.9373 (0.0407) |  |  |
| ogbg-molesol | tag | fixed-rrog-T1-ns3 | rmse | 1 | 0.9036 (0.0288) | 0.9462 (0.0215) |  |  |
| ogbg-molesol | transformer | fixed-rrog-T1-ns3 | rmse | 1 | 0.9841 (-0.0443) | 1.0004 (-0.0512) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7324 (-0.0351) | 0.7487 (0.0487) | 0.7287 (0.0287) | 2.01 |
| 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 | 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 | 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 | 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 | 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7713 (-0.0042) | 0.7476 (0.0278) | 0.7388 (0.0190) | 2.01 |
| 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 | 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7412 (-0.0755) | 0.7254 (-0.0470) | 0.7567 (-0.0157) | 2.00 |
| 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 | 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7485 (-0.0222) | 0.7221 (0.0113) | 0.7285 (0.0177) | 2.00 |
| 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 | 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 | 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7385 (-0.0395) | 0.7185 (-0.0463) | 0.7421 (-0.0227) | 2.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8010 (-0.0134) | 0.7787 (0.0545) | 0.7876 (0.0634) | 2.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7378 (-0.0100) | 0.7036 (0.0017) | 0.7244 (0.0225) | 2.03 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7326 (-0.0202) | 0.7596 (0.0341) | 0.7786 (0.0531) | 2.00 |
| 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-mollipo | appnp | fixed-rrog-T1-ns3 | rmse | 1 | 0.8393 (0.0622) | 0.9174 (-0.0104) |  |  |
| ogbg-mollipo | arma | fixed-rrog-T1-ns3 | rmse | 1 | 0.7173 (0.0152) | 0.7548 (-0.0253) |  |  |
| ogbg-mollipo | cheb | fixed-rrog-T1-ns3 | rmse | 1 | 0.6990 (0.0198) | 0.7132 (0.0048) |  |  |
| ogbg-mollipo | film | fixed-rrog-T1-ns3 | rmse | 1 | 0.8122 (-0.0502) | 0.7353 (0.0018) |  |  |
| ogbg-mollipo | gatv2 | fixed-rrog-T1-ns3 | rmse | 1 | 0.7080 (-0.0215) | 0.7334 (-0.0026) |  |  |
| ogbg-mollipo | gcn | fixed-rrog-T1-ns3 | rmse | 1 | 0.7730 (-0.0351) | 0.7759 (0.0069) |  |  |
| ogbg-mollipo | gen | fixed-rrog-T1-ns3 | rmse | 1 | 0.6594 (0.0452) | 0.7456 (-0.0077) |  |  |
| ogbg-mollipo | gin | fixed-rrog-T1-ns3 | rmse | 1 | 0.6749 (0.0105) | 0.7073 (0.0317) |  |  |
| ogbg-mollipo | gine | fixed-rrog-T1-ns3 | rmse | 1 | 0.7168 (-0.0553) | 0.7316 (0.0025) |  |  |
| ogbg-mollipo | graphconv | fixed-rrog-T1-ns3 | rmse | 1 | 0.7372 (-0.0195) | 0.7396 (-0.0099) |  |  |
| ogbg-mollipo | graphsage | fixed-rrog-T1-ns3 | rmse | 1 | 0.7184 (0.0055) | 0.7720 (0.0063) |  |  |
| ogbg-mollipo | mf | fixed-rrog-T1-ns3 | rmse | 1 | 0.7050 (0.0080) | 0.7101 (0.0304) |  |  |
| ogbg-mollipo | pna | fixed-rrog-T1-ns3 | rmse | 1 | 0.7466 (-0.0287) | 0.7908 (-0.0159) |  |  |
| ogbg-mollipo | resgated | fixed-rrog-T1-ns3 | rmse | 1 | 0.6766 (-0.0046) | 0.7144 (0.0126) |  |  |
| ogbg-mollipo | sgc | fixed-rrog-T1-ns3 | rmse | 1 | 0.7537 (-0.0032) | 0.7490 (0.0685) |  |  |
| ogbg-mollipo | tag | fixed-rrog-T1-ns3 | rmse | 1 | 0.6743 (-0.0052) | 0.7201 (0.0026) |  |  |
| ogbg-mollipo | transformer | fixed-rrog-T1-ns3 | rmse | 1 | 0.6688 (0.0121) | 0.7396 (-0.0050) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5933 (0.0047) | 0.5967 (-0.0037) | 0.5964 (-0.0040) | 7.89 |
| ogbg-molsider | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6344 (0.0071) | 0.6141 (-0.0018) |  |  |
| ogbg-molsider | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6263 (0.0026) | 0.6096 (0.0062) |  |  |
| ogbg-molsider | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.5862 (-0.0162) | 0.5974 (0.0076) |  |  |
| ogbg-molsider | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6462 (0.0391) | 0.6000 (-0.0013) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6334 (0.0041) | 0.6300 (0.0213) | 0.6306 (0.0219) | 7.91 |
| ogbg-molsider | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6345 (-0.0175) | 0.6053 (0.0199) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6075 (-0.0150) | 0.5810 (0.0062) | 0.5810 (0.0062) | 8.00 |
| ogbg-molsider | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6151 (-0.0176) | 0.6150 (0.0655) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6223 (0.0303) | 0.6222 (0.0071) | 0.6222 (0.0071) | 8.00 |
| ogbg-molsider | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6232 (0.0015) | 0.5861 (0.0053) |  |  |
| ogbg-molsider | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6190 (-0.0012) | 0.5983 (0.0122) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5870 (-0.0349) | 0.5962 (-0.0003) | 0.5962 (-0.0003) | 7.96 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6260 (0.0051) | 0.6259 (0.0349) | 0.6259 (0.0349) | 8.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5980 (-0.0194) | 0.6337 (0.0294) | 0.6337 (0.0294) | 8.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5905 (-0.0534) | 0.6216 (0.0073) | 0.6216 (0.0073) | 8.00 |
| ogbg-molsider | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6315 (0.0156) | 0.6190 (0.0210) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7238 (-0.0017) | 0.6823 (-0.0336) | 0.7138 (-0.0021) | 2.63 |
| ogbg-moltox21 | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7771 (-0.0028) | 0.7209 (-0.0014) |  |  |
| ogbg-moltox21 | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7710 (-0.0125) | 0.7286 (-0.0015) |  |  |
| ogbg-moltox21 | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7727 (0.0025) | 0.7369 (0.0209) |  |  |
| ogbg-moltox21 | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7762 (0.0135) | 0.7303 (0.0143) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7655 (0.0075) | 0.7134 (-0.0037) | 0.7234 (0.0063) | 3.76 |
| ogbg-moltox21 | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7757 (-0.0077) | 0.7312 (-0.0132) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7611 (-0.0079) | 0.7090 (-0.0152) | 0.7127 (-0.0115) | 3.83 |
| ogbg-moltox21 | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7622 (-0.0122) | 0.7193 (-0.0135) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7816 (-0.0015) | 0.7115 (-0.0032) | 0.7191 (0.0043) | 3.21 |
| ogbg-moltox21 | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7697 (-0.0012) | 0.7205 (0.0009) |  |  |
| ogbg-moltox21 | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7695 (-0.0078) | 0.7279 (-0.0002) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7547 (-0.0113) | 0.6949 (0.0003) | 0.7075 (0.0129) | 4.22 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7796 (-0.0154) | 0.7202 (-0.0074) | 0.7224 (-0.0052) | 3.08 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7779 (0.0168) | 0.7360 (0.0120) | 0.7478 (0.0238) | 3.49 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7701 (-0.0165) | 0.7163 (-0.0253) | 0.7254 (-0.0161) | 3.51 |
| ogbg-moltox21 | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7761 (0.0105) | 0.7292 (-0.0018) |  |  |
[gpu3-ablation] phase2 loss target with q_warmup=30, smaller check
[launch] cuda:3: ogbg-molhiv ogbg-molbbbp ogbg-molsider
[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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.37199 val_adapt_rocauc=0.37199 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep20 val_rocauc=0.52284 val_adapt_rocauc=0.52284 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.50000 val_adapt_rocauc=0.50000 adapt_steps=8.00 halt=0.12 train_steps=4.51
ep40 val_rocauc=0.73429 val_adapt_rocauc=0.74357 adapt_steps=2.21 halt=0.46 train_steps=1.66
ep50 val_rocauc=0.74990 val_adapt_rocauc=0.74007 adapt_steps=2.03 halt=0.45 train_steps=1.79
ep60 val_rocauc=0.73691 val_adapt_rocauc=0.72381 adapt_steps=2.07 halt=0.45 train_steps=1.77
ep70 val_rocauc=0.77428 val_adapt_rocauc=0.77133 adapt_steps=2.06 halt=0.45 train_steps=1.83
ep80 val_rocauc=0.76305 val_adapt_rocauc=0.78219 adapt_steps=2.08 halt=0.45 train_steps=1.83
ep90 val_rocauc=0.75803 val_adapt_rocauc=0.74196 adapt_steps=2.08 halt=0.45 train_steps=1.81
ep100 val_rocauc=0.75552 val_adapt_rocauc=0.75433 adapt_steps=2.07 halt=0.45 train_steps=1.83
[ogbg-molhiv_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=70 val={'rocauc': 0.774284122085048} test={'rocauc': 0.6994457212383399} adaptive={'rocauc': 0.6907394889820196} steps=2.0816921954777534
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.61849 val_adapt_rocauc=0.61849 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep20 val_rocauc=0.67236 val_adapt_rocauc=0.67236 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.55443 val_adapt_rocauc=0.55443 adapt_steps=8.00 halt=0.12 train_steps=4.51
ep40 val_rocauc=0.67669 val_adapt_rocauc=0.68572 adapt_steps=2.04 halt=0.45 train_steps=1.71
ep50 val_rocauc=0.71379 val_adapt_rocauc=0.74036 adapt_steps=2.05 halt=0.45 train_steps=1.81
ep60 val_rocauc=0.68323 val_adapt_rocauc=0.73792 adapt_steps=2.07 halt=0.44 train_steps=1.83
ep70 val_rocauc=0.68205 val_adapt_rocauc=0.70493 adapt_steps=2.07 halt=0.44 train_steps=1.87
ep80 val_rocauc=0.74377 val_adapt_rocauc=0.75284 adapt_steps=2.09 halt=0.44 train_steps=1.90
ep90 val_rocauc=0.70841 val_adapt_rocauc=0.73329 adapt_steps=2.08 halt=0.44 train_steps=1.88
ep100 val_rocauc=0.72274 val_adapt_rocauc=0.73310 adapt_steps=2.10 halt=0.44 train_steps=1.90
[ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=80 val={'rocauc': 0.7437720458553793} test={'rocauc': 0.7537553834566137} adaptive={'rocauc': 0.7804708472546787} steps=2.135910527595429
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.58438 val_adapt_rocauc=0.58438 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep20 val_rocauc=0.61779 val_adapt_rocauc=0.61779 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.50074 val_adapt_rocauc=0.50074 adapt_steps=8.00 halt=0.12 train_steps=4.51
ep40 val_rocauc=0.54256 val_adapt_rocauc=0.63047 adapt_steps=2.04 halt=0.46 train_steps=1.69
ep50 val_rocauc=0.72845 val_adapt_rocauc=0.69057 adapt_steps=2.09 halt=0.45 train_steps=1.76
ep60 val_rocauc=0.65977 val_adapt_rocauc=0.67932 adapt_steps=2.10 halt=0.45 train_steps=1.79
ep70 val_rocauc=0.70633 val_adapt_rocauc=0.71830 adapt_steps=2.06 halt=0.44 train_steps=1.83
ep80 val_rocauc=0.67811 val_adapt_rocauc=0.73880 adapt_steps=2.06 halt=0.45 train_steps=1.81
ep90 val_rocauc=0.73965 val_adapt_rocauc=0.75724 adapt_steps=2.10 halt=0.45 train_steps=1.83
ep100 val_rocauc=0.72724 val_adapt_rocauc=0.75658 adapt_steps=2.08 halt=0.45 train_steps=1.82
[ogbg-molhiv_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=90 val={'rocauc': 0.7396537575935725} test={'rocauc': 0.7500666293284923} adaptive={'rocauc': 0.7314046234960119} steps=2.136883053732069
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.56478 val_adapt_rocauc=0.56478 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep20 val_rocauc=0.54631 val_adapt_rocauc=0.54631 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.50000 val_adapt_rocauc=0.50000 adapt_steps=8.00 halt=0.12 train_steps=4.51
ep40 val_rocauc=0.67990 val_adapt_rocauc=0.67585 adapt_steps=2.01 halt=0.47 train_steps=1.63
ep50 val_rocauc=0.65561 val_adapt_rocauc=0.69113 adapt_steps=2.15 halt=0.44 train_steps=1.89
ep60 val_rocauc=0.72984 val_adapt_rocauc=0.71413 adapt_steps=2.29 halt=0.44 train_steps=1.90
ep70 val_rocauc=0.70342 val_adapt_rocauc=0.72345 adapt_steps=2.11 halt=0.44 train_steps=1.90
ep80 val_rocauc=0.71017 val_adapt_rocauc=0.70042 adapt_steps=2.07 halt=0.44 train_steps=1.84
ep90 val_rocauc=0.71672 val_adapt_rocauc=0.71984 adapt_steps=2.12 halt=0.44 train_steps=1.83
ep100 val_rocauc=0.71364 val_adapt_rocauc=0.71268 adapt_steps=2.08 halt=0.44 train_steps=1.84
[ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=60 val={'rocauc': 0.7298433519498334} test={'rocauc': 0.6791286042604143} adaptive={'rocauc': 0.7162469340852469} steps=2.4831023583758816
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.67715 val_adapt_rocauc=0.67715 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep20 val_rocauc=0.50236 val_adapt_rocauc=0.50236 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.50000 val_adapt_rocauc=0.50000 adapt_steps=8.00 halt=0.12 train_steps=4.51
ep40 val_rocauc=0.73049 val_adapt_rocauc=0.72163 adapt_steps=2.04 halt=0.45 train_steps=1.72
ep50 val_rocauc=0.70399 val_adapt_rocauc=0.70432 adapt_steps=2.04 halt=0.44 train_steps=1.84
ep60 val_rocauc=0.74930 val_adapt_rocauc=0.75474 adapt_steps=2.05 halt=0.44 train_steps=1.83
ep70 val_rocauc=0.73212 val_adapt_rocauc=0.76013 adapt_steps=2.09 halt=0.44 train_steps=1.83
ep80 val_rocauc=0.75377 val_adapt_rocauc=0.76654 adapt_steps=2.07 halt=0.45 train_steps=1.81
ep90 val_rocauc=0.75301 val_adapt_rocauc=0.77432 adapt_steps=2.10 halt=0.45 train_steps=1.82
ep100 val_rocauc=0.73251 val_adapt_rocauc=0.78027 adapt_steps=2.07 halt=0.45 train_steps=1.82
[ogbg-molhiv_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=80 val={'rocauc': 0.7537722908093278} test={'rocauc': 0.7703277390447865} adaptive={'rocauc': 0.764460495567701} steps=2.0678336980306344
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.67201 val_adapt_rocauc=0.67201 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep20 val_rocauc=0.62233 val_adapt_rocauc=0.62233 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.65638 val_adapt_rocauc=0.65638 adapt_steps=8.00 halt=0.12 train_steps=4.51
ep40 val_rocauc=0.72057 val_adapt_rocauc=0.68850 adapt_steps=2.16 halt=0.44 train_steps=1.89
ep50 val_rocauc=0.70843 val_adapt_rocauc=0.70940 adapt_steps=2.15 halt=0.44 train_steps=1.85
ep60 val_rocauc=0.64904 val_adapt_rocauc=0.64008 adapt_steps=2.15 halt=0.44 train_steps=1.90
ep70 val_rocauc=0.65729 val_adapt_rocauc=0.64703 adapt_steps=2.09 halt=0.44 train_steps=1.85
ep80 val_rocauc=0.68292 val_adapt_rocauc=0.68777 adapt_steps=2.09 halt=0.44 train_steps=1.85
ep90 val_rocauc=0.69379 val_adapt_rocauc=0.68351 adapt_steps=2.09 halt=0.44 train_steps=1.84
ep100 val_rocauc=0.68502 val_adapt_rocauc=0.67506 adapt_steps=2.09 halt=0.45 train_steps=1.81
[ogbg-molhiv_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=40 val={'rocauc': 0.720568783068783} test={'rocauc': 0.7274165202108962} adaptive={'rocauc': 0.747511539427181} steps=2.2569900316070997
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molhiv_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.44429 val_adapt_rocauc=0.44429 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep20 val_rocauc=0.86896 val_adapt_rocauc=0.86896 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep30 val_rocauc=0.85911 val_adapt_rocauc=0.85911 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep40 val_rocauc=0.90103 val_adapt_rocauc=0.93627 adapt_steps=3.02 halt=0.35 train_steps=2.59
ep50 val_rocauc=0.85224 val_adapt_rocauc=0.91536 adapt_steps=3.34 halt=0.30 train_steps=2.99
ep60 val_rocauc=0.94265 val_adapt_rocauc=0.94404 adapt_steps=3.14 halt=0.36 train_steps=2.40
ep70 val_rocauc=0.93976 val_adapt_rocauc=0.93936 adapt_steps=2.47 halt=0.36 train_steps=2.46
ep80 val_rocauc=0.91945 val_adapt_rocauc=0.91546 adapt_steps=2.47 halt=0.37 train_steps=2.42
ep90 val_rocauc=0.92034 val_adapt_rocauc=0.92194 adapt_steps=2.34 halt=0.38 train_steps=2.37
ep100 val_rocauc=0.91835 val_adapt_rocauc=0.91855 adapt_steps=2.29 halt=0.37 train_steps=2.31
[ogbg-molbbbp_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=60 val={'rocauc': 0.9426466195359953} test={'rocauc': 0.6331018518518519} adaptive={'rocauc': 0.638406635802469} steps=3.2058823529411766
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molbbbp view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.66982 val_adapt_rocauc=0.66982 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep20 val_rocauc=0.83013 val_adapt_rocauc=0.83013 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep30 val_rocauc=0.91039 val_adapt_rocauc=0.91039 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep40 val_rocauc=0.91805 val_adapt_rocauc=0.92472 adapt_steps=3.05 halt=0.33 train_steps=2.69
ep50 val_rocauc=0.90451 val_adapt_rocauc=0.92761 adapt_steps=2.40 halt=0.33 train_steps=2.70
ep60 val_rocauc=0.86080 val_adapt_rocauc=0.91168 adapt_steps=2.52 halt=0.33 train_steps=2.74
ep70 val_rocauc=0.93438 val_adapt_rocauc=0.93637 adapt_steps=2.38 halt=0.39 train_steps=2.22
ep80 val_rocauc=0.92761 val_adapt_rocauc=0.93229 adapt_steps=2.22 halt=0.39 train_steps=2.17
ep90 val_rocauc=0.92462 val_adapt_rocauc=0.92731 adapt_steps=2.14 halt=0.42 train_steps=1.99
ep100 val_rocauc=0.92881 val_adapt_rocauc=0.93189 adapt_steps=2.14 halt=0.42 train_steps=1.97
[ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=70 val={'rocauc': 0.9343821567260779} test={'rocauc': 0.6946373456790124} adaptive={'rocauc': 0.6956983024691358} steps=3.0049019607843137
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molbbbp view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.73623 val_adapt_rocauc=0.73623 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep20 val_rocauc=0.90551 val_adapt_rocauc=0.90551 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep30 val_rocauc=0.93329 val_adapt_rocauc=0.93329 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep40 val_rocauc=0.95221 val_adapt_rocauc=0.94633 adapt_steps=2.30 halt=0.36 train_steps=2.50
ep50 val_rocauc=0.83879 val_adapt_rocauc=0.89077 adapt_steps=2.45 halt=0.38 train_steps=2.43
ep60 val_rocauc=0.93149 val_adapt_rocauc=0.93657 adapt_steps=2.44 halt=0.38 train_steps=2.33
ep70 val_rocauc=0.94842 val_adapt_rocauc=0.94982 adapt_steps=2.18 halt=0.41 train_steps=1.99
ep80 val_rocauc=0.92452 val_adapt_rocauc=0.92960 adapt_steps=2.18 halt=0.43 train_steps=1.93
ep90 val_rocauc=0.93100 val_adapt_rocauc=0.93269 adapt_steps=2.17 halt=0.44 train_steps=1.85
ep100 val_rocauc=0.92502 val_adapt_rocauc=0.92522 adapt_steps=2.18 halt=0.44 train_steps=1.84
[ogbg-molbbbp_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=40 val={'rocauc': 0.9522055162799961} test={'rocauc': 0.6266396604938272} adaptive={'rocauc': 0.6264467592592592} steps=2.7892156862745097
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molbbbp view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.35647 val_adapt_rocauc=0.35647 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep20 val_rocauc=0.80783 val_adapt_rocauc=0.80783 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep30 val_rocauc=0.83362 val_adapt_rocauc=0.83362 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep40 val_rocauc=0.90670 val_adapt_rocauc=0.90869 adapt_steps=3.12 halt=0.30 train_steps=2.90
ep50 val_rocauc=0.91915 val_adapt_rocauc=0.92751 adapt_steps=2.87 halt=0.34 train_steps=2.55
ep60 val_rocauc=0.93627 val_adapt_rocauc=0.93707 adapt_steps=2.55 halt=0.37 train_steps=2.44
ep70 val_rocauc=0.95350 val_adapt_rocauc=0.94932 adapt_steps=2.43 halt=0.37 train_steps=2.44
ep80 val_rocauc=0.92582 val_adapt_rocauc=0.92721 adapt_steps=2.32 halt=0.39 train_steps=2.31
ep90 val_rocauc=0.92662 val_adapt_rocauc=0.92662 adapt_steps=2.21 halt=0.41 train_steps=2.10
ep100 val_rocauc=0.94155 val_adapt_rocauc=0.94175 adapt_steps=2.19 halt=0.41 train_steps=2.06
[ogbg-molbbbp_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=70 val={'rocauc': 0.9534999502140795} test={'rocauc': 0.6597222222222222} adaptive={'rocauc': 0.6678240740740741} steps=3.2450980392156863
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molbbbp view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.84039 val_adapt_rocauc=0.84039 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep20 val_rocauc=0.75326 val_adapt_rocauc=0.75326 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep30 val_rocauc=0.87265 val_adapt_rocauc=0.87265 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep40 val_rocauc=0.93976 val_adapt_rocauc=0.93886 adapt_steps=2.80 halt=0.32 train_steps=2.66
ep50 val_rocauc=0.91805 val_adapt_rocauc=0.93149 adapt_steps=2.47 halt=0.40 train_steps=2.15
ep60 val_rocauc=0.88619 val_adapt_rocauc=0.89923 adapt_steps=2.45 halt=0.36 train_steps=2.35
ep70 val_rocauc=0.94324 val_adapt_rocauc=0.94324 adapt_steps=2.54 halt=0.39 train_steps=2.18
ep80 val_rocauc=0.94952 val_adapt_rocauc=0.95021 adapt_steps=2.11 halt=0.42 train_steps=2.05
ep90 val_rocauc=0.94623 val_adapt_rocauc=0.95330 adapt_steps=2.09 halt=0.43 train_steps=1.95
ep100 val_rocauc=0.94524 val_adapt_rocauc=0.95081 adapt_steps=2.14 halt=0.42 train_steps=1.96
[ogbg-molbbbp_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=80 val={'rocauc': 0.9495170765707459} test={'rocauc': 0.6861496913580247} adaptive={'rocauc': 0.6808449074074074} steps=2.7058823529411766
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molbbbp view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.84487 val_adapt_rocauc=0.84487 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep20 val_rocauc=0.83471 val_adapt_rocauc=0.83471 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep30 val_rocauc=0.89664 val_adapt_rocauc=0.89664 adapt_steps=8.00 halt=0.17 train_steps=5.17
ep40 val_rocauc=0.87255 val_adapt_rocauc=0.91128 adapt_steps=2.08 halt=0.46 train_steps=1.69
ep50 val_rocauc=0.81778 val_adapt_rocauc=0.90391 adapt_steps=2.08 halt=0.44 train_steps=1.83
ep60 val_rocauc=0.86707 val_adapt_rocauc=0.90909 adapt_steps=2.05 halt=0.45 train_steps=1.73
ep70 val_rocauc=0.86588 val_adapt_rocauc=0.90282 adapt_steps=2.05 halt=0.45 train_steps=1.71
ep80 val_rocauc=0.89664 val_adapt_rocauc=0.92423 adapt_steps=2.01 halt=0.47 train_steps=1.61
ep90 val_rocauc=0.87175 val_adapt_rocauc=0.90750 adapt_steps=2.02 halt=0.47 train_steps=1.67
ep100 val_rocauc=0.86787 val_adapt_rocauc=0.90670 adapt_steps=2.04 halt=0.47 train_steps=1.62
[ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=80 val={'rocauc': 0.8966444289554915} test={'rocauc': 0.6170910493827161} adaptive={'rocauc': 0.6361882716049383} steps=2.0049019607843137
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[task] ogbg-molsider on cuda:3
[run] ogbg-molsider view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.51835 val_adapt_rocauc=0.51835 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.55881 val_adapt_rocauc=0.55881 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.52823 val_adapt_rocauc=0.52823 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.52164 val_adapt_rocauc=0.52164 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.55790 val_adapt_rocauc=0.55790 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.57934 val_adapt_rocauc=0.57937 adapt_steps=7.83 halt=0.12 train_steps=4.46
ep70 val_rocauc=0.57559 val_adapt_rocauc=0.57449 adapt_steps=7.95 halt=0.12 train_steps=4.50
ep80 val_rocauc=0.60248 val_adapt_rocauc=0.60248 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep90 val_rocauc=0.58266 val_adapt_rocauc=0.58280 adapt_steps=7.99 halt=0.12 train_steps=4.50
ep100 val_rocauc=0.59116 val_adapt_rocauc=0.59116 adapt_steps=8.00 halt=0.12 train_steps=4.50
[ogbg-molsider_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=80 val={'rocauc': 0.6024836436339023} test={'rocauc': 0.5932734621249586} adaptive={'rocauc': 0.5932734621249586} steps=8.0
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molsider view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.56195 val_adapt_rocauc=0.56195 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.59090 val_adapt_rocauc=0.59090 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.56785 val_adapt_rocauc=0.56785 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.55460 val_adapt_rocauc=0.55460 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep50 val_rocauc=0.59103 val_adapt_rocauc=0.59103 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.56623 val_adapt_rocauc=0.56623 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep70 val_rocauc=0.61162 val_adapt_rocauc=0.61169 adapt_steps=7.98 halt=0.12 train_steps=4.43
ep80 val_rocauc=0.62851 val_adapt_rocauc=0.62851 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep90 val_rocauc=0.63179 val_adapt_rocauc=0.63179 adapt_steps=7.99 halt=0.12 train_steps=4.47
ep100 val_rocauc=0.62571 val_adapt_rocauc=0.62571 adapt_steps=8.00 halt=0.13 train_steps=4.46
[ogbg-molsider_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=90 val={'rocauc': 0.6317896497739357} test={'rocauc': 0.640011295277304} adaptive={'rocauc': 0.6402407710265505} steps=7.937062937062937
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molsider view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.52921 val_adapt_rocauc=0.52921 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.51742 val_adapt_rocauc=0.51742 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.57194 val_adapt_rocauc=0.57194 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.57726 val_adapt_rocauc=0.57637 adapt_steps=7.68 halt=0.12 train_steps=4.40
ep50 val_rocauc=0.56214 val_adapt_rocauc=0.56238 adapt_steps=7.98 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.59428 val_adapt_rocauc=0.59428 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep70 val_rocauc=0.62022 val_adapt_rocauc=0.61898 adapt_steps=7.87 halt=0.12 train_steps=4.42
ep80 val_rocauc=0.61458 val_adapt_rocauc=0.61451 adapt_steps=7.99 halt=0.12 train_steps=4.50
ep90 val_rocauc=0.62914 val_adapt_rocauc=0.62914 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep100 val_rocauc=0.61681 val_adapt_rocauc=0.61660 adapt_steps=7.94 halt=0.13 train_steps=4.49
[ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=90 val={'rocauc': 0.6291378293840166} test={'rocauc': 0.622805287595805} adaptive={'rocauc': 0.6223183091184133} steps=7.916083916083916
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molsider view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.53256 val_adapt_rocauc=0.53256 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.54926 val_adapt_rocauc=0.54926 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.54957 val_adapt_rocauc=0.54957 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.51981 val_adapt_rocauc=0.52396 adapt_steps=7.78 halt=0.12 train_steps=4.44
ep50 val_rocauc=0.60657 val_adapt_rocauc=0.60657 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep60 val_rocauc=0.58438 val_adapt_rocauc=0.58438 adapt_steps=8.00 halt=0.12 train_steps=4.47
ep70 val_rocauc=0.57212 val_adapt_rocauc=0.57212 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep80 val_rocauc=0.58304 val_adapt_rocauc=0.58304 adapt_steps=8.00 halt=0.12 train_steps=4.49
ep90 val_rocauc=0.61059 val_adapt_rocauc=0.61099 adapt_steps=7.98 halt=0.12 train_steps=4.49
ep100 val_rocauc=0.60016 val_adapt_rocauc=0.60046 adapt_steps=7.99 halt=0.12 train_steps=4.48
[ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=90 val={'rocauc': 0.6105933624956364} test={'rocauc': 0.624320975867962} adaptive={'rocauc': 0.6243824341662988} steps=7.958041958041958
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molsider view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.53539 val_adapt_rocauc=0.53539 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.54274 val_adapt_rocauc=0.54274 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.56668 val_adapt_rocauc=0.56668 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.58346 val_adapt_rocauc=0.58251 adapt_steps=7.85 halt=0.12 train_steps=4.49
ep50 val_rocauc=0.57517 val_adapt_rocauc=0.57482 adapt_steps=7.76 halt=0.12 train_steps=4.49
ep60 val_rocauc=0.57520 val_adapt_rocauc=0.57520 adapt_steps=8.00 halt=0.13 train_steps=4.50
ep70 val_rocauc=0.58768 val_adapt_rocauc=0.58768 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep80 val_rocauc=0.60462 val_adapt_rocauc=0.60442 adapt_steps=7.89 halt=0.13 train_steps=4.46
ep90 val_rocauc=0.60757 val_adapt_rocauc=0.60786 adapt_steps=7.91 halt=0.12 train_steps=4.49
ep100 val_rocauc=0.61648 val_adapt_rocauc=0.61625 adapt_steps=7.95 halt=0.12 train_steps=4.49
[ogbg-molsider_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=100 val={'rocauc': 0.6164847255453625} test={'rocauc': 0.6344146740580251} adaptive={'rocauc': 0.6358083894071243} steps=7.916083916083916
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[run] ogbg-molsider view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:3
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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 30 --device cuda:3 --num_workers 0
ep10 val_rocauc=0.50415 val_adapt_rocauc=0.50415 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep20 val_rocauc=0.55422 val_adapt_rocauc=0.55422 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep30 val_rocauc=0.54565 val_adapt_rocauc=0.54565 adapt_steps=8.00 halt=0.12 train_steps=4.50
ep40 val_rocauc=0.56511 val_adapt_rocauc=0.56078 adapt_steps=7.85 halt=0.13 train_steps=4.44
ep50 val_rocauc=0.55631 val_adapt_rocauc=0.55109 adapt_steps=7.76 halt=0.13 train_steps=4.48
ep60 val_rocauc=0.57521 val_adapt_rocauc=0.56829 adapt_steps=7.38 halt=0.13 train_steps=4.46
ep70 val_rocauc=0.56234 val_adapt_rocauc=0.54971 adapt_steps=7.09 halt=0.13 train_steps=4.41
ep80 val_rocauc=0.58328 val_adapt_rocauc=0.57728 adapt_steps=7.38 halt=0.13 train_steps=4.44
ep90 val_rocauc=0.58378 val_adapt_rocauc=0.56802 adapt_steps=7.01 halt=0.13 train_steps=4.39
ep100 val_rocauc=0.58739 val_adapt_rocauc=0.57353 adapt_steps=7.03 halt=0.13 train_steps=4.38
[ogbg-molsider_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0] best_ep=100 val={'rocauc': 0.5873882396417854} test={'rocauc': 0.5819785573765826} adaptive={'rocauc': 0.5894161989454557} steps=7.13986013986014
  wrote /home/yurenh2/rrog-gnn-runner/runs/ogbg-molsider_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw30_h128_e100_s0.json
[done] collecting summaries

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) |

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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6802 (0.0238) | 0.6834 (-0.0589) | 0.7826 (0.0403) | 2.09 |
| ogbg-molbace | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7179 (0.0256) | 0.7672 (-0.0167) |  |  |
| ogbg-molbace | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7114 (-0.0154) | 0.7533 (-0.0436) |  |  |
| ogbg-molbace | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6652 (-0.0051) | 0.7242 (0.0000) |  |  |
| ogbg-molbace | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7026 (-0.0004) | 0.7519 (0.0118) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6615 (0.0234) | 0.4418 (-0.2975) | 0.5363 (-0.2031) | 2.84 |
| ogbg-molbace | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6894 (-0.0234) | 0.7449 (0.0123) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6630 (0.0110) | 0.7275 (-0.0061) | 0.7369 (0.0033) | 2.05 |
| ogbg-molbace | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6685 (0.0044) | 0.6994 (-0.0461) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6927 (-0.0385) | 0.6736 (-0.1299) | 0.7348 (-0.0687) | 2.00 |
| ogbg-molbace | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6703 (-0.0055) | 0.7119 (-0.0640) |  |  |
| ogbg-molbace | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7234 (-0.0187) | 0.7684 (-0.0077) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6590 (-0.0927) | 0.7480 (0.0569) | 0.7547 (0.0635) | 2.63 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6941 (-0.0231) | 0.7232 (-0.0645) | 0.7640 (-0.0236) | 2.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6440 (-0.0136) | 0.7117 (0.0151) | 0.7500 (0.0534) | 2.01 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6546 (-0.0538) | 0.8192 (0.0847) | 0.8143 (0.0798) | 2.11 |
| ogbg-molbace | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6982 (0.0319) | 0.7487 (0.0123) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8797 (-0.0349) | 0.5456 (-0.0932) | 0.5881 (-0.0507) | 2.01 |
| ogbg-molbbbp | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.8966 (-0.0180) | 0.6171 (-0.0217) | 0.6362 (-0.0026) | 2.00 |
| ogbg-molbbbp | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9415 (0.0048) | 0.6635 (-0.0016) |  |  |
| ogbg-molbbbp | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9278 (-0.0174) | 0.6659 (0.0145) |  |  |
| ogbg-molbbbp | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9400 (0.0115) | 0.6323 (0.0023) |  |  |
| ogbg-molbbbp | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9356 (0.0009) | 0.6560 (0.0235) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9429 (0.0044) | 0.6137 (-0.0542) | 0.6758 (0.0079) | 2.00 |
| ogbg-molbbbp | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.9344 (-0.0042) | 0.6946 (0.0267) | 0.6957 (0.0278) | 3.00 |
| ogbg-molbbbp | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9429 (-0.0119) | 0.6037 (-0.0738) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9282 (0.0031) | 0.6619 (0.0949) | 0.6693 (0.1022) | 2.08 |
| ogbg-molbbbp | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.9426 (0.0175) | 0.6331 (0.0661) | 0.6384 (0.0714) | 3.21 |
| ogbg-molbbbp | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9421 (0.0098) | 0.6976 (0.0816) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9056 (-0.0212) | 0.6369 (0.0469) | 0.6416 (0.0516) | 2.12 |
| ogbg-molbbbp | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.9495 (0.0227) | 0.6861 (0.0962) | 0.6808 (0.0909) | 2.71 |
| ogbg-molbbbp | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9502 (0.0019) | 0.5934 (-0.0354) |  |  |
| ogbg-molbbbp | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9488 (0.0094) | 0.6481 (0.0116) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9380 (-0.0174) | 0.6539 (0.0122) | 0.6563 (0.0146) | 2.31 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9499 (0.0317) | 0.6604 (-0.0022) | 0.6677 (0.0051) | 2.34 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9347 (0.0047) | 0.6516 (0.0277) | 0.6385 (0.0146) | 2.00 |
| ogbg-molbbbp | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.9522 (0.0222) | 0.6266 (0.0027) | 0.6264 (0.0025) | 2.79 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9406 (-0.0071) | 0.6350 (0.0251) | 0.6147 (0.0047) | 2.01 |
| ogbg-molbbbp | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.9535 (0.0059) | 0.6597 (0.0498) | 0.6678 (0.0579) | 3.25 |
| ogbg-molbbbp | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9355 (-0.0140) | 0.6221 (0.0065) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9391 (0.0875) | 0.8412 (-0.0772) | 0.9026 (-0.0158) | 2.04 |
| ogbg-molclintox | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9135 (-0.0328) | 0.8863 (0.0185) |  |  |
| ogbg-molclintox | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.8816 (-0.0112) | 0.8982 (-0.0170) |  |  |
| ogbg-molclintox | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9454 (0.0406) | 0.8430 (0.0699) |  |  |
| ogbg-molclintox | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9351 (-0.0164) | 0.8328 (-0.0164) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9759 (0.0440) | 0.8740 (-0.0192) | 0.8683 (-0.0249) | 2.05 |
| ogbg-molclintox | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9399 (-0.0421) | 0.8194 (0.0066) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9257 (-0.0290) | 0.8803 (0.0216) | 0.8739 (0.0153) | 2.07 |
| ogbg-molclintox | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9225 (-0.0127) | 0.8840 (-0.0030) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8660 (-0.0258) | 0.8054 (-0.0447) | 0.8241 (-0.0260) | 2.21 |
| ogbg-molclintox | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9579 (0.0436) | 0.8664 (-0.0217) |  |  |
| ogbg-molclintox | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9147 (-0.0104) | 0.8047 (-0.0323) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8295 (-0.0991) | 0.9034 (0.0431) | 0.9195 (0.0592) | 2.23 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9116 (-0.0128) | 0.8403 (-0.0781) | 0.8416 (-0.0768) | 2.03 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.9309 (0.0114) | 0.8810 (-0.0176) | 0.9033 (0.0047) | 2.09 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8679 (-0.0558) | 0.8433 (0.0434) | 0.8345 (0.0347) | 2.00 |
| ogbg-molclintox | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9322 (0.0051) | 0.8522 (-0.0242) |  |  |
| ogbg-molesol | appnp | fixed-rrog-T1-ns3 | rmse | 1 | 1.4196 (0.1887) | 1.4929 (0.0284) |  |  |
| ogbg-molesol | arma | fixed-rrog-T1-ns3 | rmse | 1 | 1.0034 (0.0160) | 1.1272 (-0.0606) |  |  |
| ogbg-molesol | cheb | fixed-rrog-T1-ns3 | rmse | 1 | 0.9199 (0.0451) | 0.8841 (-0.0118) |  |  |
| ogbg-molesol | film | fixed-rrog-T1-ns3 | rmse | 1 | 1.0196 (0.0521) | 1.0849 (0.2047) |  |  |
| ogbg-molesol | gatv2 | fixed-rrog-T1-ns3 | rmse | 1 | 1.0018 (0.0350) | 0.9780 (0.0098) |  |  |
| ogbg-molesol | gcn | fixed-rrog-T1-ns3 | rmse | 1 | 0.9591 (0.0818) | 0.9305 (0.1856) |  |  |
| ogbg-molesol | gen | fixed-rrog-T1-ns3 | rmse | 1 | 1.0027 (0.0062) | 0.9206 (-0.0444) |  |  |
| ogbg-molesol | gin | fixed-rrog-T1-ns3 | rmse | 1 | 0.9647 (0.0540) | 1.0798 (-0.0899) |  |  |
| ogbg-molesol | gine | fixed-rrog-T1-ns3 | rmse | 1 | 1.0581 (-0.0295) | 1.0951 (-0.0144) |  |  |
| ogbg-molesol | graphconv | fixed-rrog-T1-ns3 | rmse | 1 | 1.0048 (-0.0307) | 0.9968 (-0.0236) |  |  |
| ogbg-molesol | graphsage | fixed-rrog-T1-ns3 | rmse | 1 | 0.9934 (-0.0254) | 1.0794 (-0.0757) |  |  |
| ogbg-molesol | mf | fixed-rrog-T1-ns3 | rmse | 1 | 1.0553 (0.0942) | 1.0368 (0.0271) |  |  |
| ogbg-molesol | pna | fixed-rrog-T1-ns3 | rmse | 1 | 0.9841 (-0.0725) | 0.9092 (0.0060) |  |  |
| ogbg-molesol | resgated | fixed-rrog-T1-ns3 | rmse | 1 | 0.9873 (-0.0382) | 0.8825 (0.0083) |  |  |
| ogbg-molesol | sgc | fixed-rrog-T1-ns3 | rmse | 1 | 1.0129 (0.0488) | 0.9373 (0.0407) |  |  |
| ogbg-molesol | tag | fixed-rrog-T1-ns3 | rmse | 1 | 0.9036 (0.0288) | 0.9462 (0.0215) |  |  |
| ogbg-molesol | transformer | fixed-rrog-T1-ns3 | rmse | 1 | 0.9841 (-0.0443) | 1.0004 (-0.0512) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7324 (-0.0351) | 0.7487 (0.0487) | 0.7287 (0.0287) | 2.01 |
| ogbg-molhiv | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.7206 (-0.0469) | 0.7274 (0.0274) | 0.7475 (0.0475) | 2.26 |
| 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 | 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 | 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 | 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 | 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7713 (-0.0042) | 0.7476 (0.0278) | 0.7388 (0.0190) | 2.01 |
| ogbg-molhiv | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.7438 (-0.0317) | 0.7538 (0.0340) | 0.7805 (0.0607) | 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 | 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7412 (-0.0755) | 0.7254 (-0.0470) | 0.7567 (-0.0157) | 2.00 |
| ogbg-molhiv | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.7743 (-0.0425) | 0.6994 (-0.0730) | 0.6907 (-0.0817) | 2.08 |
| 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 | 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7485 (-0.0222) | 0.7221 (0.0113) | 0.7285 (0.0177) | 2.00 |
| ogbg-molhiv | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.7538 (-0.0169) | 0.7703 (0.0595) | 0.7645 (0.0536) | 2.07 |
| 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 | 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 | 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7385 (-0.0395) | 0.7185 (-0.0463) | 0.7421 (-0.0227) | 2.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.8010 (-0.0134) | 0.7787 (0.0545) | 0.7876 (0.0634) | 2.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7378 (-0.0100) | 0.7036 (0.0017) | 0.7244 (0.0225) | 2.03 |
| ogbg-molhiv | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.7397 (-0.0082) | 0.7501 (0.0482) | 0.7314 (0.0295) | 2.14 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7326 (-0.0202) | 0.7596 (0.0341) | 0.7786 (0.0531) | 2.00 |
| ogbg-molhiv | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.7298 (-0.0230) | 0.6791 (-0.0464) | 0.7162 (-0.0093) | 2.48 |
| 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-mollipo | appnp | fixed-rrog-T1-ns3 | rmse | 1 | 0.8393 (0.0622) | 0.9174 (-0.0104) |  |  |
| ogbg-mollipo | arma | fixed-rrog-T1-ns3 | rmse | 1 | 0.7173 (0.0152) | 0.7548 (-0.0253) |  |  |
| ogbg-mollipo | cheb | fixed-rrog-T1-ns3 | rmse | 1 | 0.6990 (0.0198) | 0.7132 (0.0048) |  |  |
| ogbg-mollipo | film | fixed-rrog-T1-ns3 | rmse | 1 | 0.8122 (-0.0502) | 0.7353 (0.0018) |  |  |
| ogbg-mollipo | gatv2 | fixed-rrog-T1-ns3 | rmse | 1 | 0.7080 (-0.0215) | 0.7334 (-0.0026) |  |  |
| ogbg-mollipo | gcn | fixed-rrog-T1-ns3 | rmse | 1 | 0.7730 (-0.0351) | 0.7759 (0.0069) |  |  |
| ogbg-mollipo | gen | fixed-rrog-T1-ns3 | rmse | 1 | 0.6594 (0.0452) | 0.7456 (-0.0077) |  |  |
| ogbg-mollipo | gin | fixed-rrog-T1-ns3 | rmse | 1 | 0.6749 (0.0105) | 0.7073 (0.0317) |  |  |
| ogbg-mollipo | gine | fixed-rrog-T1-ns3 | rmse | 1 | 0.7168 (-0.0553) | 0.7316 (0.0025) |  |  |
| ogbg-mollipo | graphconv | fixed-rrog-T1-ns3 | rmse | 1 | 0.7372 (-0.0195) | 0.7396 (-0.0099) |  |  |
| ogbg-mollipo | graphsage | fixed-rrog-T1-ns3 | rmse | 1 | 0.7184 (0.0055) | 0.7720 (0.0063) |  |  |
| ogbg-mollipo | mf | fixed-rrog-T1-ns3 | rmse | 1 | 0.7050 (0.0080) | 0.7101 (0.0304) |  |  |
| ogbg-mollipo | pna | fixed-rrog-T1-ns3 | rmse | 1 | 0.7466 (-0.0287) | 0.7908 (-0.0159) |  |  |
| ogbg-mollipo | resgated | fixed-rrog-T1-ns3 | rmse | 1 | 0.6766 (-0.0046) | 0.7144 (0.0126) |  |  |
| ogbg-mollipo | sgc | fixed-rrog-T1-ns3 | rmse | 1 | 0.7537 (-0.0032) | 0.7490 (0.0685) |  |  |
| ogbg-mollipo | tag | fixed-rrog-T1-ns3 | rmse | 1 | 0.6743 (-0.0052) | 0.7201 (0.0026) |  |  |
| ogbg-mollipo | transformer | fixed-rrog-T1-ns3 | rmse | 1 | 0.6688 (0.0121) | 0.7396 (-0.0050) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5933 (0.0047) | 0.5967 (-0.0037) | 0.5964 (-0.0040) | 7.89 |
| ogbg-molsider | appnp | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.5874 (-0.0012) | 0.5820 (-0.0184) | 0.5894 (-0.0110) | 7.14 |
| ogbg-molsider | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6344 (0.0071) | 0.6141 (-0.0018) |  |  |
| ogbg-molsider | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6263 (0.0026) | 0.6096 (0.0062) |  |  |
| ogbg-molsider | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.5862 (-0.0162) | 0.5974 (0.0076) |  |  |
| ogbg-molsider | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6462 (0.0391) | 0.6000 (-0.0013) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6334 (0.0041) | 0.6300 (0.0213) | 0.6306 (0.0219) | 7.91 |
| ogbg-molsider | gcn | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.6318 (0.0025) | 0.6400 (0.0314) | 0.6402 (0.0316) | 7.94 |
| ogbg-molsider | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6345 (-0.0175) | 0.6053 (0.0199) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6075 (-0.0150) | 0.5810 (0.0062) | 0.5810 (0.0062) | 8.00 |
| ogbg-molsider | gin | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.6025 (-0.0200) | 0.5933 (0.0184) | 0.5933 (0.0184) | 8.00 |
| ogbg-molsider | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6151 (-0.0176) | 0.6150 (0.0655) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6223 (0.0303) | 0.6222 (0.0071) | 0.6222 (0.0071) | 8.00 |
| ogbg-molsider | graphconv | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.6165 (0.0244) | 0.6344 (0.0193) | 0.6358 (0.0207) | 7.92 |
| ogbg-molsider | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6232 (0.0015) | 0.5861 (0.0053) |  |  |
| ogbg-molsider | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6190 (-0.0012) | 0.5983 (0.0122) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5870 (-0.0349) | 0.5962 (-0.0003) | 0.5962 (-0.0003) | 7.96 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.6260 (0.0051) | 0.6259 (0.0349) | 0.6259 (0.0349) | 8.00 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5980 (-0.0194) | 0.6337 (0.0294) | 0.6337 (0.0294) | 8.00 |
| ogbg-molsider | sgc | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.6291 (0.0118) | 0.6228 (0.0185) | 0.6223 (0.0181) | 7.92 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.5905 (-0.0534) | 0.6216 (0.0073) | 0.6216 (0.0073) | 8.00 |
| ogbg-molsider | tag | rrog-act-stream-T1-ns3-hm8-min2-loss0.2-lq0.1-hex0.1-qw30 | rocauc | 1 | 0.6106 (-0.0333) | 0.6243 (0.0100) | 0.6244 (0.0101) | 7.96 |
| ogbg-molsider | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.6315 (0.0156) | 0.6190 (0.0210) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7238 (-0.0017) | 0.6823 (-0.0336) | 0.7138 (-0.0021) | 2.63 |
| ogbg-moltox21 | arma | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7771 (-0.0028) | 0.7209 (-0.0014) |  |  |
| ogbg-moltox21 | cheb | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7710 (-0.0125) | 0.7286 (-0.0015) |  |  |
| ogbg-moltox21 | film | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7727 (0.0025) | 0.7369 (0.0209) |  |  |
| ogbg-moltox21 | gatv2 | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7762 (0.0135) | 0.7303 (0.0143) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7655 (0.0075) | 0.7134 (-0.0037) | 0.7234 (0.0063) | 3.76 |
| ogbg-moltox21 | gen | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7757 (-0.0077) | 0.7312 (-0.0132) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7611 (-0.0079) | 0.7090 (-0.0152) | 0.7127 (-0.0115) | 3.83 |
| ogbg-moltox21 | gine | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7622 (-0.0122) | 0.7193 (-0.0135) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7816 (-0.0015) | 0.7115 (-0.0032) | 0.7191 (0.0043) | 3.21 |
| ogbg-moltox21 | graphsage | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7697 (-0.0012) | 0.7205 (0.0009) |  |  |
| ogbg-moltox21 | mf | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7695 (-0.0078) | 0.7279 (-0.0002) |  |  |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7547 (-0.0113) | 0.6949 (0.0003) | 0.7075 (0.0129) | 4.22 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7796 (-0.0154) | 0.7202 (-0.0074) | 0.7224 (-0.0052) | 3.08 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7779 (0.0168) | 0.7360 (0.0120) | 0.7478 (0.0238) | 3.49 |
| 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-exact-lq0.1-hex0.1-qw0 | rocauc | 1 | 0.7701 (-0.0165) | 0.7163 (-0.0253) | 0.7254 (-0.0161) | 3.51 |
| ogbg-moltox21 | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.7761 (0.0105) | 0.7292 (-0.0018) |  |  |
[gpu3-ablation] done Wed Jun 24 14:55:07 CDT 2026