path: root/logs/ogbg-molbbbp_0.log

[run] ogbg-molbbbp view=gin compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gin --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
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Extracting /orion/u/oscarwan/rrog-gnn-runner/data/ogb/bbbp.zip
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/orion/u/oscarwan/rrog-gnn-runner/.venv/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:203.)
  g.y = torch.from_numpy(graph_label[i]).view(1,-1).to(torch.long)
Done!
Saving...
ep10 val_rocauc=0.92512 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.89933 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.88519 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.91098 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.88191 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.88041 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.89565 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.89933 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.90172 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.90202 halt=0.00 train_steps=1.00
[ogbg-molbbbp_gin_classic_T0_ns1_h128_e100_s0] best_ep=10 val={'rocauc': 0.925121975505327} test={'rocauc': 0.5670331790123456} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gin_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=gin compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gin --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.95260 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.93299 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.92502 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.88410 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.91736 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.92522 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.92801 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.92373 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.92243 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.92512 halt=0.00 train_steps=3.00
[ogbg-molbbbp_gin_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=10 val={'rocauc': 0.9526038036443294} test={'rocauc': 0.5931712962962963} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gin_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=gine compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gine --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.82535 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.88788 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.91138 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.93239 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.91825 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.90810 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.89137 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.90959 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.90441 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.90690 halt=0.00 train_steps=1.00
[ogbg-molbbbp_gine_classic_T0_ns1_h128_e100_s0] best_ep=40 val={'rocauc': 0.932390719904411} test={'rocauc': 0.6160300925925926} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gine_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=gine compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gine --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.91397 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.90710 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.85363 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.94215 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.90471 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.90909 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.90043 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.90252 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.90103 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.90441 halt=0.00 train_steps=3.00
[ogbg-molbbbp_gine_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=40 val={'rocauc': 0.9421487603305785} test={'rocauc': 0.6976273148148147} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gine_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=gcn compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gcn --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.91297 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.92891 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.92940 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.93856 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.92164 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.92881 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.93110 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.93269 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.93080 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.93299 halt=0.00 train_steps=1.00
[ogbg-molbbbp_gcn_classic_T0_ns1_h128_e100_s0] best_ep=40 val={'rocauc': 0.9385641740515782} test={'rocauc': 0.667920524691358} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gcn_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=gcn compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gcn --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.94165 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.92293 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.90919 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.92632 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.92940 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.91546 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.92642 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.92811 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.92701 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.92592 halt=0.00 train_steps=3.00
[ogbg-molbbbp_gcn_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=10 val={'rocauc': 0.9416509011251619} test={'rocauc': 0.601658950617284} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gcn_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=graphsage compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view graphsage --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.94832 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.92034 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.93498 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.91576 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.91945 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.91477 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.90999 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.90750 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.90481 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.90232 halt=0.00 train_steps=1.00
[ogbg-molbbbp_graphsage_classic_T0_ns1_h128_e100_s0] best_ep=10 val={'rocauc': 0.9483222144777457} test={'rocauc': 0.628761574074074} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_graphsage_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=graphsage compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view graphsage --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.87882 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.95021 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.92104 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.92144 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.93488 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.93777 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.93199 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.93528 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.93269 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.93468 halt=0.00 train_steps=3.00
[ogbg-molbbbp_graphsage_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=20 val={'rocauc': 0.9502140794583291} test={'rocauc': 0.5933641975308641} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_graphsage_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=gatv2 compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gatv2 --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.92393 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.93349 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.91238 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.93468 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.91507 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.92990 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.92960 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.93000 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.92901 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.92851 halt=0.00 train_steps=1.00
[ogbg-molbbbp_gatv2_classic_T0_ns1_h128_e100_s0] best_ep=40 val={'rocauc': 0.9346808722493279} test={'rocauc': 0.6324266975308642} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gatv2_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=gatv2 compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gatv2 --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.88251 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.90780 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.93558 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.93528 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.92154 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.92632 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.92442 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.92592 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.92482 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.92263 halt=0.00 train_steps=3.00
[ogbg-molbbbp_gatv2_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=30 val={'rocauc': 0.935577018819078} test={'rocauc': 0.6559606481481481} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gatv2_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=graphconv compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view graphconv --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.92204 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.92681 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.89087 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.89625 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.92034 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.92024 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.91377 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.91745 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.91676 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.91686 halt=0.00 train_steps=1.00
[ogbg-molbbbp_graphconv_classic_T0_ns1_h128_e100_s0] best_ep=20 val={'rocauc': 0.9268146968037438} test={'rocauc': 0.5899884259259258} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_graphconv_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=graphconv compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view graphconv --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.93369 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.93279 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.91566 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.92204 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.92891 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.91805 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.92363 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.91795 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.91536 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.91307 halt=0.00 train_steps=3.00
[ogbg-molbbbp_graphconv_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=10 val={'rocauc': 0.9336851538384945} test={'rocauc': 0.6518132716049383} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_graphconv_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=transformer compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view transformer --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.94952 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.93538 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.94613 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.94553 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.93259 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.93657 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.93458 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.93428 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.93339 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.93299 halt=0.00 train_steps=1.00
[ogbg-molbbbp_transformer_classic_T0_ns1_h128_e100_s0] best_ep=10 val={'rocauc': 0.9495170765707458} test={'rocauc': 0.6156442901234568} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_transformer_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=transformer compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view transformer --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.93548 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.91516 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.92582 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.91775 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.92174 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.92871 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.92164 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.92134 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.92004 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.92024 halt=0.00 train_steps=3.00
[ogbg-molbbbp_transformer_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=10 val={'rocauc': 0.9354774469779946} test={'rocauc': 0.6221064814814815} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_transformer_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=pna compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view pna --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
/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=0.91188 halt=0.00 train_steps=1.00
/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=0.88977 halt=0.00 train_steps=1.00
/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=0.90929 halt=0.00 train_steps=1.00
/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=0.92134 halt=0.00 train_steps=1.00
/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=0.90869 halt=0.00 train_steps=1.00
/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=0.95539 halt=0.00 train_steps=1.00
/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=0.93130 halt=0.00 train_steps=1.00
/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=0.92213 halt=0.00 train_steps=1.00
/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=0.91795 halt=0.00 train_steps=1.00
/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=0.92174 halt=0.00 train_steps=1.00
[ogbg-molbbbp_pna_classic_T0_ns1_h128_e100_s0] best_ep=60 val={'rocauc': 0.955391815194663} test={'rocauc': 0.6417824074074073} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_pna_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=pna compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view pna --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
/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=0.88579 halt=0.00 train_steps=3.00
/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=0.90571 halt=0.00 train_steps=3.00
/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=0.80783 halt=0.00 train_steps=3.00
/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=0.95848 halt=0.00 train_steps=3.00
/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=0.93478 halt=0.00 train_steps=3.00
/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=0.94474 halt=0.00 train_steps=3.00
/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=0.92841 halt=0.00 train_steps=3.00
/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=0.92413 halt=0.00 train_steps=3.00
/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=0.91487 halt=0.00 train_steps=3.00
/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=0.91875 halt=0.00 train_steps=3.00
[ogbg-molbbbp_pna_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=40 val={'rocauc': 0.9584785422682465} test={'rocauc': 0.6682098765432098} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_pna_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=gen compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gen --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.89943 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.92104 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.92502 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.95489 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.92213 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.93408 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.93717 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.93777 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.93797 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.93777 halt=0.00 train_steps=1.00
[ogbg-molbbbp_gen_classic_T0_ns1_h128_e100_s0] best_ep=40 val={'rocauc': 0.9548939559892462} test={'rocauc': 0.677469135802469} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gen_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=gen compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view gen --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.93657 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.92353 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.92452 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.94295 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.92174 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.93578 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.94036 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.93976 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.93856 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.93737 halt=0.00 train_steps=3.00
[ogbg-molbbbp_gen_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=40 val={'rocauc': 0.9429453350592453} test={'rocauc': 0.6036844135802468} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gen_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=film compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view film --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.83919 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.85024 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.89167 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.91128 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.92851 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.92303 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.91616 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.91387 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.91407 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.91596 halt=0.00 train_steps=1.00
[ogbg-molbbbp_film_classic_T0_ns1_h128_e100_s0] best_ep=50 val={'rocauc': 0.9285074181021606} test={'rocauc': 0.6300154320987654} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_film_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=film compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view film --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.90122 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.93996 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.91477 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.90312 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.90252 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.90630 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.90959 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.90282 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.90182 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.90252 halt=0.00 train_steps=3.00
[ogbg-molbbbp_film_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=20 val={'rocauc': 0.939958179826745} test={'rocauc': 0.6323302469135803} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_film_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=resgated compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view resgated --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.88957 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.91477 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.87743 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.88967 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.91825 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.91158 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.90630 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.91238 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.91078 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.91317 halt=0.00 train_steps=1.00
[ogbg-molbbbp_resgated_classic_T0_ns1_h128_e100_s0] best_ep=50 val={'rocauc': 0.9182515184705764} test={'rocauc': 0.6626157407407406} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_resgated_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=resgated compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view resgated --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.93807 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.95350 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.92034 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.92124 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.89057 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.89893 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.90401 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.90620 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.90531 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.90381 halt=0.00 train_steps=3.00
[ogbg-molbbbp_resgated_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=20 val={'rocauc': 0.9534999502140794} test={'rocauc': 0.583912037037037} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_resgated_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=tag compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view tag --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.93369 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.92253 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.93607 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.94763 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.92801 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.93677 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.93617 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.93299 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.93319 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.93329 halt=0.00 train_steps=1.00
[ogbg-molbbbp_tag_classic_T0_ns1_h128_e100_s0] best_ep=40 val={'rocauc': 0.9476252115901622} test={'rocauc': 0.6099537037037036} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_tag_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=tag compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view tag --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.91367 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.94265 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.94593 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.92960 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.91915 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.91526 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.92064 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.91775 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.91895 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.91805 halt=0.00 train_steps=3.00
[ogbg-molbbbp_tag_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=30 val={'rocauc': 0.9459324902917455} test={'rocauc': 0.6419753086419753} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_tag_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=sgc compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view sgc --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.90381 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.92104 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.90272 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.91048 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.92313 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.93000 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.92044 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.91775 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.91566 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.91556 halt=0.00 train_steps=1.00
[ogbg-molbbbp_sgc_classic_T0_ns1_h128_e100_s0] best_ep=60 val={'rocauc': 0.9300009957184109} test={'rocauc': 0.6239390432098766} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_sgc_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=sgc compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view sgc --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.91736 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.88111 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.92831 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.91905 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.92851 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.91636 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.92004 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.91616 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.91526 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.91556 halt=0.00 train_steps=3.00
[ogbg-molbbbp_sgc_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=50 val={'rocauc': 0.9285074181021606} test={'rocauc': 0.6454475308641976} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_sgc_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=cheb compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view cheb --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.91925 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.94524 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.92084 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.91377 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.91497 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.92353 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.91925 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.91726 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.92114 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.92154 halt=0.00 train_steps=1.00
[ogbg-molbbbp_cheb_classic_T0_ns1_h128_e100_s0] best_ep=20 val={'rocauc': 0.9452354874041621} test={'rocauc': 0.6514274691358024} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_cheb_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=cheb compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view cheb --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.90152 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.91805 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.92313 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.92781 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.92423 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.92433 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.91975 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.91755 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.91835 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.91855 halt=0.00 train_steps=3.00
[ogbg-molbbbp_cheb_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=40 val={'rocauc': 0.9278104152145773} test={'rocauc': 0.665895061728395} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_cheb_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=arma compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view arma --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.93667 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.90013 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.91367 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.86598 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.88948 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.88997 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.88858 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.88997 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.88938 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.89057 halt=0.00 train_steps=1.00
[ogbg-molbbbp_arma_classic_T0_ns1_h128_e100_s0] best_ep=10 val={'rocauc': 0.9366723090709947} test={'rocauc': 0.6651234567901235} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_arma_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=arma compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view arma --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.94145 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.85263 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.91646 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.89485 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.93100 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.90919 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.91218 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.91367 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.91546 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.91427 halt=0.00 train_steps=3.00
[ogbg-molbbbp_arma_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=10 val={'rocauc': 0.941451757442995} test={'rocauc': 0.6634837962962963} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_arma_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=mf compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view mf --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.91048 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.91984 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.93090 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.93946 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.92323 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.92672 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.92333 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.92084 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.92004 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.91805 halt=0.00 train_steps=1.00
[ogbg-molbbbp_mf_classic_T0_ns1_h128_e100_s0] best_ep=40 val={'rocauc': 0.9394603206213283} test={'rocauc': 0.6364776234567902} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_mf_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=mf compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view mf --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.88619 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.94882 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.93797 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.91238 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.92522 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.93229 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.92930 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.92821 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.92811 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.92652 halt=0.00 train_steps=3.00
[ogbg-molbbbp_mf_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=20 val={'rocauc': 0.9488200736831625} test={'rocauc': 0.6480516975308641} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_mf_fixed-rrog_T1_ns3_h128_e100_s0.json
[run] ogbg-molbbbp view=appnp compute=classic T=0 ns=1 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view appnp --compute classic --T 0 --n_sup 1 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.90122 halt=0.00 train_steps=1.00
ep20 val_rocauc=0.91467 halt=0.00 train_steps=1.00
ep30 val_rocauc=0.88539 halt=0.00 train_steps=1.00
ep40 val_rocauc=0.89416 halt=0.00 train_steps=1.00
ep50 val_rocauc=0.88330 halt=0.00 train_steps=1.00
ep60 val_rocauc=0.89246 halt=0.00 train_steps=1.00
ep70 val_rocauc=0.88788 halt=0.00 train_steps=1.00
ep80 val_rocauc=0.88898 halt=0.00 train_steps=1.00
ep90 val_rocauc=0.89425 halt=0.00 train_steps=1.00
ep100 val_rocauc=0.89167 halt=0.00 train_steps=1.00
[ogbg-molbbbp_appnp_classic_T0_ns1_h128_e100_s0] best_ep=20 val={'rocauc': 0.9146669321915762} test={'rocauc': 0.6387924382716049} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_appnp_classic_T0_ns1_h128_e100_s0.json
[run] ogbg-molbbbp view=appnp compute=fixed-rrog T=1 ns=3 device=cuda:1
python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --view appnp --compute fixed-rrog --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --device cuda:1
ep10 val_rocauc=0.93598 halt=0.00 train_steps=3.00
ep20 val_rocauc=0.90202 halt=0.00 train_steps=3.00
ep30 val_rocauc=0.92014 halt=0.00 train_steps=3.00
ep40 val_rocauc=0.93189 halt=0.00 train_steps=3.00
ep50 val_rocauc=0.91188 halt=0.00 train_steps=3.00
ep60 val_rocauc=0.91248 halt=0.00 train_steps=3.00
ep70 val_rocauc=0.90272 halt=0.00 train_steps=3.00
ep80 val_rocauc=0.89844 halt=0.00 train_steps=3.00
ep90 val_rocauc=0.90680 halt=0.00 train_steps=3.00
ep100 val_rocauc=0.90620 halt=0.00 train_steps=3.00
[ogbg-molbbbp_appnp_fixed-rrog_T1_ns3_h128_e100_s0] best_ep=10 val={'rocauc': 0.9359753061834113} test={'rocauc': 0.6073495370370371} adaptive=None steps=None
  wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_appnp_fixed-rrog_T1_ns3_h128_e100_s0.json

Classic baseline: task x backbone
| task | backbone | metric | n | val | test |
| --- | --- | --- | --- | --- | --- |
| 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-molhiv | appnp | rocauc | 1 | 0.7675 +/- 0.0000 | 0.7000 +/- 0.0000 |
| ogbg-molhiv | arma | rocauc | 1 | 0.7872 +/- 0.0000 | 0.7296 +/- 0.0000 |
| ogbg-molhiv | cheb | rocauc | 1 | 0.7831 +/- 0.0000 | 0.7282 +/- 0.0000 |
| ogbg-molhiv | film | rocauc | 1 | 0.7922 +/- 0.0000 | 0.7842 +/- 0.0000 |
| ogbg-molhiv | gatv2 | rocauc | 1 | 0.7835 +/- 0.0000 | 0.7563 +/- 0.0000 |
| ogbg-molhiv | gcn | rocauc | 1 | 0.7754 +/- 0.0000 | 0.7198 +/- 0.0000 |
| ogbg-molhiv | gen | rocauc | 1 | 0.7530 +/- 0.0000 | 0.7314 +/- 0.0000 |
| ogbg-molhiv | gin | rocauc | 1 | 0.8167 +/- 0.0000 | 0.7724 +/- 0.0000 |
| ogbg-molhiv | gine | rocauc | 1 | 0.7942 +/- 0.0000 | 0.7445 +/- 0.0000 |
| ogbg-molhiv | graphconv | rocauc | 1 | 0.7707 +/- 0.0000 | 0.7108 +/- 0.0000 |
| ogbg-molhiv | graphsage | rocauc | 1 | 0.7969 +/- 0.0000 | 0.7625 +/- 0.0000 |
| ogbg-molhiv | mf | rocauc | 1 | 0.7845 +/- 0.0000 | 0.7074 +/- 0.0000 |
| ogbg-molhiv | pna | rocauc | 1 | 0.7780 +/- 0.0000 | 0.7648 +/- 0.0000 |
| ogbg-molhiv | resgated | rocauc | 1 | 0.8144 +/- 0.0000 | 0.7242 +/- 0.0000 |
| ogbg-molhiv | sgc | rocauc | 1 | 0.7479 +/- 0.0000 | 0.7019 +/- 0.0000 |
| ogbg-molhiv | tag | rocauc | 1 | 0.7528 +/- 0.0000 | 0.7255 +/- 0.0000 |
| ogbg-molhiv | transformer | rocauc | 1 | 0.7617 +/- 0.0000 | 0.7547 +/- 0.0000 |

Delta vs matching classic
| task | backbone | compute | metric | n | val score (delta) | test score (delta) | steps |
| --- | --- | --- | --- | --- | --- | --- | --- |
| ogbg-molbbbp | appnp | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9360 (0.0213) | 0.6073 (-0.0314) |  |
| 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 | 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 | 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 | 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 | resgated | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9535 (0.0352) | 0.5839 (-0.0787) |  |
| ogbg-molbbbp | sgc | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9285 (-0.0015) | 0.6454 (0.0215) |  |
| ogbg-molbbbp | tag | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9459 (-0.0017) | 0.6420 (0.0320) |  |
| ogbg-molbbbp | transformer | fixed-rrog-T1-ns3 | rocauc | 1 | 0.9355 (-0.0140) | 0.6221 (0.0065) |  |
| ogbg-molhiv | appnp | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7203 (-0.0471) | 0.6825 (-0.0175) |  |
| ogbg-molhiv | arma | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7926 (0.0054) | 0.7318 (0.0021) |  |
| ogbg-molhiv | cheb | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7735 (-0.0096) | 0.7426 (0.0144) |  |
| ogbg-molhiv | film | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7633 (-0.0288) | 0.7728 (-0.0114) |  |
| ogbg-molhiv | gatv2 | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7835 (0.0001) | 0.7466 (-0.0096) |  |
| ogbg-molhiv | gcn | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7455 (-0.0300) | 0.7483 (0.0285) |  |
| 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 | 1 | 0.7710 (-0.0457) | 0.7668 (-0.0056) |  |
| ogbg-molhiv | gin | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7524 (-0.0644) | 0.7324 (-0.0400) |  |
| ogbg-molhiv | gine | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7575 (-0.0368) | 0.7401 (-0.0044) |  |
| ogbg-molhiv | graphconv | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7713 (0.0006) | 0.6979 (-0.0129) |  |
| ogbg-molhiv | graphsage | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7587 (-0.0382) | 0.7641 (0.0016) |  |
| ogbg-molhiv | mf | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7931 (0.0085) | 0.7217 (0.0143) |  |
| ogbg-molhiv | pna | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7890 (0.0111) | 0.7630 (-0.0018) |  |
| ogbg-molhiv | resgated | fixed-rrog-T3-ns3 | rocauc | 1 | 0.8174 (0.0030) | 0.7055 (-0.0187) |  |
| ogbg-molhiv | sgc | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7482 (0.0003) | 0.7177 (0.0158) |  |
| ogbg-molhiv | tag | fixed-rrog-T3-ns3 | rocauc | 1 | 0.7804 (0.0276) | 0.7352 (0.0096) |  |
| ogbg-molhiv | transformer | fixed-rrog-T3-ns3 | rocauc | 1 | 0.8088 (0.0471) | 0.7413 (-0.0134) |  |