[run] ogbg-molclintox view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.77209 val_adapt_rocauc=0.80519 adapt_steps=2.72 halt=0.34 train_steps=2.51
ep20 val_rocauc=0.78183 val_adapt_rocauc=0.80016 adapt_steps=2.06 halt=0.37 train_steps=2.64
ep30 val_rocauc=0.78255 val_adapt_rocauc=0.76576 adapt_steps=4.13 halt=0.34 train_steps=2.65
ep40 val_rocauc=0.94888 val_adapt_rocauc=0.93689 adapt_steps=2.55 halt=0.37 train_steps=2.28
ep50 val_rocauc=0.88011 val_adapt_rocauc=0.87381 adapt_steps=2.15 halt=0.38 train_steps=2.23
ep60 val_rocauc=0.95997 val_adapt_rocauc=0.96159 adapt_steps=2.24 halt=0.37 train_steps=2.55
ep70 val_rocauc=0.92487 val_adapt_rocauc=0.91931 adapt_steps=2.11 halt=0.39 train_steps=2.34
ep80 val_rocauc=0.93713 val_adapt_rocauc=0.92883 adapt_steps=2.45 halt=0.42 train_steps=2.15
ep90 val_rocauc=0.94286 val_adapt_rocauc=0.93582 adapt_steps=2.32 halt=0.41 train_steps=2.08
ep100 val_rocauc=0.93878 val_adapt_rocauc=0.92695 adapt_steps=2.21 halt=0.40 train_steps=2.15
[ogbg-molclintox_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.9599674972914409} test={'rocauc': 0.8033521009279533} adaptive={'rocauc': 0.8111476036562055} steps=2.7094594594594597
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view gine --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.76383 val_adapt_rocauc=0.77994 adapt_steps=2.01 halt=0.36 train_steps=2.43
ep20 val_rocauc=0.80870 val_adapt_rocauc=0.86788 adapt_steps=3.20 halt=0.36 train_steps=2.52
ep30 val_rocauc=0.75884 val_adapt_rocauc=0.80281 adapt_steps=2.47 halt=0.35 train_steps=2.59
ep40 val_rocauc=0.86243 val_adapt_rocauc=0.89579 adapt_steps=2.90 halt=0.34 train_steps=2.62
ep50 val_rocauc=0.89135 val_adapt_rocauc=0.86760 adapt_steps=2.41 halt=0.38 train_steps=2.29
ep60 val_rocauc=0.90485 val_adapt_rocauc=0.88818 adapt_steps=2.26 halt=0.40 train_steps=2.20
ep70 val_rocauc=0.93950 val_adapt_rocauc=0.93379 adapt_steps=2.16 halt=0.39 train_steps=2.27
ep80 val_rocauc=0.94562 val_adapt_rocauc=0.91967 adapt_steps=2.22 halt=0.40 train_steps=2.25
ep90 val_rocauc=0.93472 val_adapt_rocauc=0.91171 adapt_steps=2.22 halt=0.41 train_steps=2.02
ep100 val_rocauc=0.93612 val_adapt_rocauc=0.91308 adapt_steps=2.22 halt=0.41 train_steps=2.14
[ogbg-molclintox_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.9456195213237466} test={'rocauc': 0.9048100649914852} adaptive={'rocauc': 0.9068831891008932} steps=2.2972972972972974
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1
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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.85640 val_adapt_rocauc=0.82455 adapt_steps=2.11 halt=0.38 train_steps=2.49
ep20 val_rocauc=0.82161 val_adapt_rocauc=0.86794 adapt_steps=2.25 halt=0.42 train_steps=1.95
ep30 val_rocauc=0.90791 val_adapt_rocauc=0.90606 adapt_steps=2.48 halt=0.40 train_steps=2.22
ep40 val_rocauc=0.87426 val_adapt_rocauc=0.86053 adapt_steps=2.28 halt=0.39 train_steps=2.23
ep50 val_rocauc=0.90999 val_adapt_rocauc=0.93044 adapt_steps=2.48 halt=0.40 train_steps=2.19
ep60 val_rocauc=0.92425 val_adapt_rocauc=0.92174 adapt_steps=2.33 halt=0.43 train_steps=1.93
ep70 val_rocauc=0.91453 val_adapt_rocauc=0.92876 adapt_steps=2.26 halt=0.42 train_steps=2.06
ep80 val_rocauc=0.94111 val_adapt_rocauc=0.92515 adapt_steps=2.18 halt=0.44 train_steps=1.91
ep90 val_rocauc=0.94603 val_adapt_rocauc=0.94386 adapt_steps=2.16 halt=0.43 train_steps=1.97
ep100 val_rocauc=0.93669 val_adapt_rocauc=0.93404 adapt_steps=2.24 halt=0.42 train_steps=1.93
[ogbg-molclintox_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.9460307298335469} test={'rocauc': 0.8712221527126125} adaptive={'rocauc': 0.8801906301046121} steps=2.2027027027027026
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view graphsage --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.79462 val_adapt_rocauc=0.82656 adapt_steps=2.22 halt=0.34 train_steps=2.52
ep20 val_rocauc=0.84462 val_adapt_rocauc=0.87055 adapt_steps=2.30 halt=0.38 train_steps=2.43
ep30 val_rocauc=0.75120 val_adapt_rocauc=0.82551 adapt_steps=2.07 halt=0.40 train_steps=2.12
ep40 val_rocauc=0.93718 val_adapt_rocauc=0.93679 adapt_steps=2.45 halt=0.39 train_steps=2.33
ep50 val_rocauc=0.94727 val_adapt_rocauc=0.94822 adapt_steps=2.40 halt=0.40 train_steps=2.11
ep60 val_rocauc=0.95164 val_adapt_rocauc=0.94490 adapt_steps=2.51 halt=0.40 train_steps=2.18
ep70 val_rocauc=0.87261 val_adapt_rocauc=0.87261 adapt_steps=2.23 halt=0.40 train_steps=2.12
ep80 val_rocauc=0.89686 val_adapt_rocauc=0.89115 adapt_steps=2.20 halt=0.42 train_steps=2.05
ep90 val_rocauc=0.88179 val_adapt_rocauc=0.87664 adapt_steps=2.16 halt=0.41 train_steps=2.02
ep100 val_rocauc=0.89555 val_adapt_rocauc=0.89160 adapt_steps=2.14 halt=0.41 train_steps=2.08
[ogbg-molclintox_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.9516390886109196} test={'rocauc': 0.88216296527995} adaptive={'rocauc': 0.8780280123727106} steps=2.4324324324324325
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view gatv2 --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.70967 val_adapt_rocauc=0.85199 adapt_steps=2.37 halt=0.37 train_steps=2.39
ep20 val_rocauc=0.89092 val_adapt_rocauc=0.92549 adapt_steps=2.22 halt=0.44 train_steps=1.89
ep30 val_rocauc=0.81332 val_adapt_rocauc=0.83200 adapt_steps=2.01 halt=0.45 train_steps=1.79
ep40 val_rocauc=0.80582 val_adapt_rocauc=0.83143 adapt_steps=2.14 halt=0.40 train_steps=2.12
ep50 val_rocauc=0.92910 val_adapt_rocauc=0.93248 adapt_steps=2.32 halt=0.41 train_steps=2.22
ep60 val_rocauc=0.92482 val_adapt_rocauc=0.93468 adapt_steps=2.32 halt=0.41 train_steps=2.17
ep70 val_rocauc=0.92105 val_adapt_rocauc=0.93623 adapt_steps=2.38 halt=0.41 train_steps=2.15
ep80 val_rocauc=0.92617 val_adapt_rocauc=0.93959 adapt_steps=2.31 halt=0.41 train_steps=2.12
ep90 val_rocauc=0.94562 val_adapt_rocauc=0.95085 adapt_steps=2.28 halt=0.41 train_steps=2.20
ep100 val_rocauc=0.95068 val_adapt_rocauc=0.95672 adapt_steps=2.28 halt=0.40 train_steps=2.14
[ogbg-molclintox_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.9506763189861781} test={'rocauc': 0.8617905675459633} adaptive={'rocauc': 0.834407256803253} steps=2.3378378378378377
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1
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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.69917 val_adapt_rocauc=0.72403 adapt_steps=2.24 halt=0.39 train_steps=2.26
ep20 val_rocauc=0.81950 val_adapt_rocauc=0.82965 adapt_steps=2.00 halt=0.34 train_steps=2.75
ep30 val_rocauc=0.80323 val_adapt_rocauc=0.78038 adapt_steps=2.73 halt=0.34 train_steps=2.70
ep40 val_rocauc=0.89633 val_adapt_rocauc=0.85819 adapt_steps=2.17 halt=0.37 train_steps=2.38
ep50 val_rocauc=0.93302 val_adapt_rocauc=0.93985 adapt_steps=2.71 halt=0.38 train_steps=2.37
ep60 val_rocauc=0.94116 val_adapt_rocauc=0.94729 adapt_steps=2.39 halt=0.41 train_steps=2.13
ep70 val_rocauc=0.95746 val_adapt_rocauc=0.93137 adapt_steps=2.28 halt=0.41 train_steps=2.12
ep80 val_rocauc=0.94965 val_adapt_rocauc=0.93652 adapt_steps=2.24 halt=0.41 train_steps=2.13
ep90 val_rocauc=0.95186 val_adapt_rocauc=0.93864 adapt_steps=2.24 halt=0.41 train_steps=2.05
ep100 val_rocauc=0.95550 val_adapt_rocauc=0.93900 adapt_steps=2.28 halt=0.41 train_steps=2.03
[ogbg-molclintox_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.9574583866837387} test={'rocauc': 0.881274111145866} adaptive={'rocauc': 0.8484968546901609} steps=2.4121621621621623
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view transformer --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.66344 val_adapt_rocauc=0.75035 adapt_steps=2.91 halt=0.33 train_steps=2.69
ep20 val_rocauc=0.67594 val_adapt_rocauc=0.72203 adapt_steps=2.06 halt=0.39 train_steps=2.32
ep30 val_rocauc=0.85214 val_adapt_rocauc=0.88626 adapt_steps=2.31 halt=0.40 train_steps=2.06
ep40 val_rocauc=0.76707 val_adapt_rocauc=0.81695 adapt_steps=2.36 halt=0.38 train_steps=2.22
ep50 val_rocauc=0.76833 val_adapt_rocauc=0.77783 adapt_steps=2.26 halt=0.40 train_steps=2.13
ep60 val_rocauc=0.79067 val_adapt_rocauc=0.78862 adapt_steps=2.30 halt=0.43 train_steps=2.04
ep70 val_rocauc=0.79816 val_adapt_rocauc=0.79690 adapt_steps=2.20 halt=0.41 train_steps=1.99
ep80 val_rocauc=0.78835 val_adapt_rocauc=0.78999 adapt_steps=2.22 halt=0.41 train_steps=2.03
ep90 val_rocauc=0.78740 val_adapt_rocauc=0.78532 adapt_steps=2.21 halt=0.43 train_steps=1.98
ep100 val_rocauc=0.78905 val_adapt_rocauc=0.78792 adapt_steps=2.24 halt=0.42 train_steps=1.98
[ogbg-molclintox_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.8521414031977412} test={'rocauc': 0.7332707746846001} adaptive={'rocauc': 0.7908464532721649} steps=3.2567567567567566
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1
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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep10 val_rocauc=0.68589 val_adapt_rocauc=0.92664 adapt_steps=2.16 halt=0.41 train_steps=1.91
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep20 val_rocauc=0.85293 val_adapt_rocauc=0.85189 adapt_steps=2.44 halt=0.35 train_steps=2.56
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep30 val_rocauc=0.77476 val_adapt_rocauc=0.82179 adapt_steps=2.44 halt=0.28 train_steps=3.08
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep40 val_rocauc=0.87414 val_adapt_rocauc=0.89831 adapt_steps=2.53 halt=0.30 train_steps=2.83
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep50 val_rocauc=0.86257 val_adapt_rocauc=0.88010 adapt_steps=2.60 halt=0.32 train_steps=2.83
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep60 val_rocauc=0.71890 val_adapt_rocauc=0.77423 adapt_steps=3.07 halt=0.36 train_steps=2.45
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep70 val_rocauc=0.80193 val_adapt_rocauc=0.81742 adapt_steps=2.28 halt=0.37 train_steps=2.40
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep80 val_rocauc=0.82369 val_adapt_rocauc=0.84324 adapt_steps=2.29 halt=0.38 train_steps=2.34
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep90 val_rocauc=0.86654 val_adapt_rocauc=0.87053 adapt_steps=2.28 halt=0.41 train_steps=2.17
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found
  warnings.warn(
ep100 val_rocauc=0.86785 val_adapt_rocauc=0.86774 adapt_steps=2.23 halt=0.40 train_steps=2.14
[ogbg-molclintox_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.874143110410716} test={'rocauc': 0.8539203419872797} adaptive={'rocauc': 0.8613908872901679} steps=3.675675675675676
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view gen --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.84544 val_adapt_rocauc=0.85771 adapt_steps=2.57 halt=0.29 train_steps=2.87
ep20 val_rocauc=0.95110 val_adapt_rocauc=0.91548 adapt_steps=3.41 halt=0.33 train_steps=2.66
ep30 val_rocauc=0.83528 val_adapt_rocauc=0.89928 adapt_steps=2.29 halt=0.31 train_steps=2.91
ep40 val_rocauc=0.76843 val_adapt_rocauc=0.80352 adapt_steps=2.51 halt=0.34 train_steps=2.56
ep50 val_rocauc=0.80865 val_adapt_rocauc=0.85913 adapt_steps=2.77 halt=0.36 train_steps=2.47
ep60 val_rocauc=0.88044 val_adapt_rocauc=0.89659 adapt_steps=2.14 halt=0.42 train_steps=2.05
ep70 val_rocauc=0.92773 val_adapt_rocauc=0.93695 adapt_steps=2.28 halt=0.40 train_steps=2.12
ep80 val_rocauc=0.96265 val_adapt_rocauc=0.95789 adapt_steps=2.37 halt=0.39 train_steps=2.27
ep90 val_rocauc=0.95997 val_adapt_rocauc=0.95404 adapt_steps=2.19 halt=0.40 train_steps=2.22
ep100 val_rocauc=0.95236 val_adapt_rocauc=0.95381 adapt_steps=2.16 halt=0.40 train_steps=2.06
[ogbg-molclintox_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.962652253849437} test={'rocauc': 0.7993926597852152} adaptive={'rocauc': 0.8024780175859313} steps=2.52027027027027
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view film --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.85317 val_adapt_rocauc=0.88605 adapt_steps=2.39 halt=0.28 train_steps=3.00
ep20 val_rocauc=0.81828 val_adapt_rocauc=0.82320 adapt_steps=2.45 halt=0.27 train_steps=3.23
ep30 val_rocauc=0.84258 val_adapt_rocauc=0.95090 adapt_steps=2.46 halt=0.34 train_steps=2.48
ep40 val_rocauc=0.75162 val_adapt_rocauc=0.79277 adapt_steps=2.35 halt=0.29 train_steps=3.14
ep50 val_rocauc=0.78711 val_adapt_rocauc=0.87848 adapt_steps=2.74 halt=0.28 train_steps=3.02
ep60 val_rocauc=0.81069 val_adapt_rocauc=0.91211 adapt_steps=2.38 halt=0.33 train_steps=2.62
ep70 val_rocauc=0.81552 val_adapt_rocauc=0.90454 adapt_steps=2.36 halt=0.33 train_steps=2.65
ep80 val_rocauc=0.82161 val_adapt_rocauc=0.91004 adapt_steps=2.32 halt=0.35 train_steps=2.57
ep90 val_rocauc=0.81750 val_adapt_rocauc=0.88712 adapt_steps=2.42 halt=0.34 train_steps=2.62
ep100 val_rocauc=0.82991 val_adapt_rocauc=0.90417 adapt_steps=2.39 halt=0.32 train_steps=2.82
[ogbg-molclintox_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=10 val={'rocauc': 0.8531673725335697} test={'rocauc': 0.8229512042539882} adaptive={'rocauc': 0.8409142251416258} steps=3.5675675675675675
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1
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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.74252 val_adapt_rocauc=0.79094 adapt_steps=2.14 halt=0.36 train_steps=2.48
ep20 val_rocauc=0.81568 val_adapt_rocauc=0.85910 adapt_steps=2.39 halt=0.35 train_steps=2.46
ep30 val_rocauc=0.84840 val_adapt_rocauc=0.92310 adapt_steps=2.11 halt=0.41 train_steps=2.09
ep40 val_rocauc=0.95769 val_adapt_rocauc=0.94539 adapt_steps=2.16 halt=0.43 train_steps=1.87
ep50 val_rocauc=0.92392 val_adapt_rocauc=0.94729 adapt_steps=2.65 halt=0.37 train_steps=2.31
ep60 val_rocauc=0.92694 val_adapt_rocauc=0.91922 adapt_steps=2.72 halt=0.37 train_steps=2.49
ep70 val_rocauc=0.90361 val_adapt_rocauc=0.89307 adapt_steps=2.32 halt=0.43 train_steps=1.98
ep80 val_rocauc=0.91214 val_adapt_rocauc=0.90406 adapt_steps=2.36 halt=0.41 train_steps=2.09
ep90 val_rocauc=0.90185 val_adapt_rocauc=0.89822 adapt_steps=2.32 halt=0.42 train_steps=2.04
ep100 val_rocauc=0.89869 val_adapt_rocauc=0.89844 adapt_steps=2.29 halt=0.42 train_steps=1.99
[ogbg-molclintox_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.957693949243245} test={'rocauc': 0.8777291210509853} adaptive={'rocauc': 0.8950795885031105} steps=2.2567567567567566
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1
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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.82868 val_adapt_rocauc=0.84050 adapt_steps=2.43 halt=0.39 train_steps=2.17
ep20 val_rocauc=0.68167 val_adapt_rocauc=0.82555 adapt_steps=2.24 halt=0.39 train_steps=2.29
ep30 val_rocauc=0.90011 val_adapt_rocauc=0.87969 adapt_steps=2.48 halt=0.35 train_steps=2.43
ep40 val_rocauc=0.87408 val_adapt_rocauc=0.90534 adapt_steps=2.23 halt=0.38 train_steps=2.23
ep50 val_rocauc=0.86302 val_adapt_rocauc=0.87087 adapt_steps=2.50 halt=0.42 train_steps=2.01
ep60 val_rocauc=0.88360 val_adapt_rocauc=0.90039 adapt_steps=2.14 halt=0.41 train_steps=2.16
ep70 val_rocauc=0.86734 val_adapt_rocauc=0.88072 adapt_steps=2.36 halt=0.42 train_steps=1.95
ep80 val_rocauc=0.87492 val_adapt_rocauc=0.87176 adapt_steps=2.22 halt=0.42 train_steps=1.94
ep90 val_rocauc=0.87822 val_adapt_rocauc=0.87936 adapt_steps=2.20 halt=0.42 train_steps=2.04
ep100 val_rocauc=0.87463 val_adapt_rocauc=0.87752 adapt_steps=2.26 halt=0.42 train_steps=1.91
[ogbg-molclintox_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.9001050592599888} test={'rocauc': 0.8008871163938415} adaptive={'rocauc': 0.8083576616967296} steps=2.5945945945945947
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1
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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.75045 val_adapt_rocauc=0.76256 adapt_steps=2.63 halt=0.35 train_steps=2.42
ep20 val_rocauc=0.84107 val_adapt_rocauc=0.82692 adapt_steps=2.05 halt=0.39 train_steps=2.28
ep30 val_rocauc=0.82797 val_adapt_rocauc=0.80820 adapt_steps=2.16 halt=0.40 train_steps=2.17
ep40 val_rocauc=0.91055 val_adapt_rocauc=0.89387 adapt_steps=2.19 halt=0.43 train_steps=1.88
ep50 val_rocauc=0.89428 val_adapt_rocauc=0.87914 adapt_steps=2.42 halt=0.38 train_steps=2.22
ep60 val_rocauc=0.89904 val_adapt_rocauc=0.88187 adapt_steps=2.34 halt=0.43 train_steps=1.92
ep70 val_rocauc=0.91524 val_adapt_rocauc=0.90461 adapt_steps=2.33 halt=0.43 train_steps=1.88
ep80 val_rocauc=0.91526 val_adapt_rocauc=0.89527 adapt_steps=2.31 halt=0.43 train_steps=1.99
ep90 val_rocauc=0.91339 val_adapt_rocauc=0.90184 adapt_steps=2.32 halt=0.44 train_steps=1.94
ep100 val_rocauc=0.91057 val_adapt_rocauc=0.90055 adapt_steps=2.30 halt=0.42 train_steps=2.02
[ogbg-molclintox_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.9152647821661906} test={'rocauc': 0.8882589580509506} adaptive={'rocauc': 0.8904589371980676} steps=2.25
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view cheb --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.78798 val_adapt_rocauc=0.83382 adapt_steps=2.20 halt=0.39 train_steps=2.27
ep20 val_rocauc=0.71633 val_adapt_rocauc=0.74377 adapt_steps=2.78 halt=0.42 train_steps=1.99
ep30 val_rocauc=0.89270 val_adapt_rocauc=0.90791 adapt_steps=2.54 halt=0.41 train_steps=1.95
ep40 val_rocauc=0.91721 val_adapt_rocauc=0.93704 adapt_steps=2.25 halt=0.42 train_steps=1.89
ep50 val_rocauc=0.88995 val_adapt_rocauc=0.88075 adapt_steps=2.22 halt=0.40 train_steps=2.14
ep60 val_rocauc=0.87245 val_adapt_rocauc=0.86085 adapt_steps=2.17 halt=0.44 train_steps=1.96
ep70 val_rocauc=0.89380 val_adapt_rocauc=0.88259 adapt_steps=2.09 halt=0.42 train_steps=1.94
ep80 val_rocauc=0.89714 val_adapt_rocauc=0.89109 adapt_steps=2.17 halt=0.44 train_steps=1.92
ep90 val_rocauc=0.90792 val_adapt_rocauc=0.89461 adapt_steps=2.18 halt=0.43 train_steps=1.91
ep100 val_rocauc=0.91072 val_adapt_rocauc=0.90068 adapt_steps=2.14 halt=0.41 train_steps=1.96
[ogbg-molclintox_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.9172116615778587} test={'rocauc': 0.906584297779168} adaptive={'rocauc': 0.9058335939943698} steps=2.97972972972973
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view arma --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.81318 val_adapt_rocauc=0.80930 adapt_steps=2.37 halt=0.35 train_steps=2.35
ep20 val_rocauc=0.69804 val_adapt_rocauc=0.82638 adapt_steps=2.15 halt=0.31 train_steps=2.87
ep30 val_rocauc=0.94232 val_adapt_rocauc=0.92281 adapt_steps=2.83 halt=0.39 train_steps=2.09
ep40 val_rocauc=0.86469 val_adapt_rocauc=0.88327 adapt_steps=2.67 halt=0.36 train_steps=2.54
ep50 val_rocauc=0.89535 val_adapt_rocauc=0.90887 adapt_steps=2.19 halt=0.37 train_steps=2.46
ep60 val_rocauc=0.92823 val_adapt_rocauc=0.93065 adapt_steps=2.24 halt=0.41 train_steps=2.09
ep70 val_rocauc=0.93024 val_adapt_rocauc=0.93498 adapt_steps=2.20 halt=0.43 train_steps=1.91
ep80 val_rocauc=0.92742 val_adapt_rocauc=0.93392 adapt_steps=2.17 halt=0.42 train_steps=2.07
ep90 val_rocauc=0.93094 val_adapt_rocauc=0.94491 adapt_steps=2.17 halt=0.45 train_steps=1.81
ep100 val_rocauc=0.93728 val_adapt_rocauc=0.94060 adapt_steps=2.16 halt=0.41 train_steps=2.07
[ogbg-molclintox_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.942323287041597} test={'rocauc': 0.8458372432488792} adaptive={'rocauc': 0.8651226844611268} steps=2.722972972972973
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json
[run] ogbg-molclintox view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molclintox --view mf --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.93105 val_adapt_rocauc=0.89417 adapt_steps=2.82 halt=0.32 train_steps=2.64
ep20 val_rocauc=0.81868 val_adapt_rocauc=0.81868 adapt_steps=2.54 halt=0.35 train_steps=2.46
ep30 val_rocauc=0.80286 val_adapt_rocauc=0.78639 adapt_steps=2.11 halt=0.37 train_steps=2.59
ep40 val_rocauc=0.80906 val_adapt_rocauc=0.83030 adapt_steps=2.18 halt=0.36 train_steps=2.49
ep50 val_rocauc=0.85998 val_adapt_rocauc=0.83241 adapt_steps=2.39 halt=0.40 train_steps=2.20
ep60 val_rocauc=0.90338 val_adapt_rocauc=0.86791 adapt_steps=2.18 halt=0.42 train_steps=2.08
ep70 val_rocauc=0.94162 val_adapt_rocauc=0.91534 adapt_steps=2.16 halt=0.42 train_steps=2.04
ep80 val_rocauc=0.89972 val_adapt_rocauc=0.89221 adapt_steps=2.14 halt=0.43 train_steps=2.03
ep90 val_rocauc=0.91851 val_adapt_rocauc=0.90667 adapt_steps=2.11 halt=0.42 train_steps=2.01
ep100 val_rocauc=0.92030 val_adapt_rocauc=0.90645 adapt_steps=2.14 halt=0.41 train_steps=2.03
[ogbg-molclintox_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.9416239863422963} test={'rocauc': 0.852654398220554} adaptive={'rocauc': 0.8698067632850242} steps=2.5675675675675675
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1
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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0
ep10 val_rocauc=0.71982 val_adapt_rocauc=0.77487 adapt_steps=2.08 halt=0.44 train_steps=1.89
ep20 val_rocauc=0.74144 val_adapt_rocauc=0.75935 adapt_steps=2.03 halt=0.46 train_steps=1.69
ep30 val_rocauc=0.87530 val_adapt_rocauc=0.86698 adapt_steps=2.09 halt=0.45 train_steps=1.73
ep40 val_rocauc=0.85439 val_adapt_rocauc=0.85187 adapt_steps=2.16 halt=0.42 train_steps=1.92
ep50 val_rocauc=0.85586 val_adapt_rocauc=0.88542 adapt_steps=2.04 halt=0.44 train_steps=1.83
ep60 val_rocauc=0.91564 val_adapt_rocauc=0.92289 adapt_steps=2.16 halt=0.45 train_steps=1.84
ep70 val_rocauc=0.85864 val_adapt_rocauc=0.90628 adapt_steps=2.09 halt=0.45 train_steps=1.71
ep80 val_rocauc=0.85984 val_adapt_rocauc=0.91203 adapt_steps=2.01 halt=0.44 train_steps=1.90
ep90 val_rocauc=0.86275 val_adapt_rocauc=0.89833 adapt_steps=2.03 halt=0.44 train_steps=1.91
ep100 val_rocauc=0.84485 val_adapt_rocauc=0.89378 adapt_steps=2.02 halt=0.43 train_steps=1.93
[ogbg-molclintox_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.9156406973308382} test={'rocauc': 0.7779932575678588} adaptive={'rocauc': 0.886122406422688} steps=2.1621621621621623
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molclintox_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json