diff options
Diffstat (limited to 'logs')
8 files changed, 2152 insertions, 0 deletions
diff --git a/logs/ogbg-molbace_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-molbace_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..6fad787 --- /dev/null +++ b/logs/ogbg-molbace_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,278 @@ +[run] ogbg-molbace view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.62747 val_adapt_rocauc=0.63956 adapt_steps=5.64 halt=0.17 train_steps=4.09 +ep20 val_rocauc=0.40916 val_adapt_rocauc=0.38755 adapt_steps=2.62 halt=0.15 train_steps=4.15 +ep30 val_rocauc=0.45714 val_adapt_rocauc=0.49011 adapt_steps=5.73 halt=0.17 train_steps=4.04 +ep40 val_rocauc=0.56740 val_adapt_rocauc=0.60037 adapt_steps=3.81 halt=0.24 train_steps=3.51 +ep50 val_rocauc=0.43443 val_adapt_rocauc=0.43736 adapt_steps=4.63 halt=0.20 train_steps=3.57 +ep60 val_rocauc=0.66557 val_adapt_rocauc=0.67289 adapt_steps=4.50 halt=0.22 train_steps=3.60 +ep70 val_rocauc=0.65018 val_adapt_rocauc=0.65604 adapt_steps=4.30 halt=0.27 train_steps=3.14 +ep80 val_rocauc=0.68022 val_adapt_rocauc=0.66520 adapt_steps=4.40 halt=0.30 train_steps=2.85 +ep90 val_rocauc=0.67216 val_adapt_rocauc=0.67070 adapt_steps=4.48 halt=0.27 train_steps=3.13 +ep100 val_rocauc=0.67582 val_adapt_rocauc=0.66447 adapt_steps=4.34 halt=0.30 train_steps=2.93 +[ogbg-molbace_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.6802197802197802} test={'rocauc': 0.723526343244653} adaptive={'rocauc': 0.721961398017736} steps=3.473684210526316 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.58205 val_adapt_rocauc=0.58462 adapt_steps=7.00 halt=0.27 train_steps=3.01 +ep20 val_rocauc=0.54835 val_adapt_rocauc=0.55495 adapt_steps=7.38 halt=0.13 train_steps=4.38 +ep30 val_rocauc=0.64542 val_adapt_rocauc=0.57033 adapt_steps=4.30 halt=0.15 train_steps=4.25 +ep40 val_rocauc=0.47033 val_adapt_rocauc=0.49597 adapt_steps=4.36 halt=0.18 train_steps=3.89 +ep50 val_rocauc=0.57619 val_adapt_rocauc=0.55971 adapt_steps=4.50 halt=0.18 train_steps=3.77 +ep60 val_rocauc=0.56593 val_adapt_rocauc=0.57143 adapt_steps=4.76 halt=0.24 train_steps=3.54 +ep70 val_rocauc=0.68242 val_adapt_rocauc=0.69780 adapt_steps=3.98 halt=0.25 train_steps=3.42 +ep80 val_rocauc=0.65897 val_adapt_rocauc=0.66081 adapt_steps=4.22 halt=0.26 train_steps=3.37 +ep90 val_rocauc=0.63187 val_adapt_rocauc=0.63150 adapt_steps=4.58 halt=0.24 train_steps=3.38 +ep100 val_rocauc=0.62381 val_adapt_rocauc=0.62637 adapt_steps=4.89 halt=0.25 train_steps=3.32 +[ogbg-molbace_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.6824175824175824} test={'rocauc': 0.7718657624760911} adaptive={'rocauc': 0.7697791688402017} steps=3.1710526315789473 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.59927 val_adapt_rocauc=0.60696 adapt_steps=5.45 halt=0.21 train_steps=3.53 +ep20 val_rocauc=0.61245 val_adapt_rocauc=0.60147 adapt_steps=4.89 halt=0.21 train_steps=3.54 +ep30 val_rocauc=0.71941 val_adapt_rocauc=0.72015 adapt_steps=4.09 halt=0.24 train_steps=3.64 +ep40 val_rocauc=0.66923 val_adapt_rocauc=0.67692 adapt_steps=4.70 halt=0.21 train_steps=3.73 +ep50 val_rocauc=0.72015 val_adapt_rocauc=0.70220 adapt_steps=4.28 halt=0.27 train_steps=3.33 +ep60 val_rocauc=0.66264 val_adapt_rocauc=0.67546 adapt_steps=4.85 halt=0.30 train_steps=2.94 +ep70 val_rocauc=0.57619 val_adapt_rocauc=0.57766 adapt_steps=3.40 halt=0.29 train_steps=3.02 +ep80 val_rocauc=0.60147 val_adapt_rocauc=0.61648 adapt_steps=3.09 halt=0.34 train_steps=2.52 +ep90 val_rocauc=0.63480 val_adapt_rocauc=0.63773 adapt_steps=3.01 halt=0.37 train_steps=2.41 +ep100 val_rocauc=0.63810 val_adapt_rocauc=0.63883 adapt_steps=2.89 halt=0.39 train_steps=2.20 +[ogbg-molbace_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.7201465201465201} test={'rocauc': 0.7483915840723353} adaptive={'rocauc': 0.7450878108155105} steps=3.960526315789474 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.57070 val_adapt_rocauc=0.60293 adapt_steps=5.37 halt=0.30 train_steps=2.89 +ep20 val_rocauc=0.56520 val_adapt_rocauc=0.57692 adapt_steps=6.33 halt=0.20 train_steps=3.67 +ep30 val_rocauc=0.59670 val_adapt_rocauc=0.60916 adapt_steps=3.97 halt=0.25 train_steps=3.37 +ep40 val_rocauc=0.62564 val_adapt_rocauc=0.62454 adapt_steps=2.83 halt=0.30 train_steps=3.03 +ep50 val_rocauc=0.69634 val_adapt_rocauc=0.69597 adapt_steps=4.89 halt=0.23 train_steps=3.60 +ep60 val_rocauc=0.64286 val_adapt_rocauc=0.63480 adapt_steps=3.69 halt=0.26 train_steps=3.31 +ep70 val_rocauc=0.70916 val_adapt_rocauc=0.71502 adapt_steps=4.54 halt=0.26 train_steps=3.45 +ep80 val_rocauc=0.63626 val_adapt_rocauc=0.65897 adapt_steps=4.31 halt=0.28 train_steps=3.07 +ep90 val_rocauc=0.64066 val_adapt_rocauc=0.63590 adapt_steps=3.86 halt=0.32 train_steps=2.74 +ep100 val_rocauc=0.64066 val_adapt_rocauc=0.64835 adapt_steps=3.68 halt=0.30 train_steps=2.89 +[ogbg-molbace_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.7091575091575092} test={'rocauc': 0.7821248478525474} adaptive={'rocauc': 0.7909928708050773} steps=3.75 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.68608 val_adapt_rocauc=0.68938 adapt_steps=7.89 halt=0.17 train_steps=3.74 +ep20 val_rocauc=0.63260 val_adapt_rocauc=0.62674 adapt_steps=5.79 halt=0.21 train_steps=3.57 +ep30 val_rocauc=0.61612 val_adapt_rocauc=0.64615 adapt_steps=5.33 halt=0.23 train_steps=3.07 +ep40 val_rocauc=0.71319 val_adapt_rocauc=0.71978 adapt_steps=4.52 halt=0.23 train_steps=3.55 +ep50 val_rocauc=0.66960 val_adapt_rocauc=0.65458 adapt_steps=5.34 halt=0.21 train_steps=3.69 +ep60 val_rocauc=0.69927 val_adapt_rocauc=0.68571 adapt_steps=5.17 halt=0.21 train_steps=3.63 +ep70 val_rocauc=0.63956 val_adapt_rocauc=0.64652 adapt_steps=4.17 halt=0.28 train_steps=3.24 +ep80 val_rocauc=0.63333 val_adapt_rocauc=0.63260 adapt_steps=3.86 halt=0.26 train_steps=3.23 +ep90 val_rocauc=0.64103 val_adapt_rocauc=0.65714 adapt_steps=2.97 halt=0.34 train_steps=2.71 +ep100 val_rocauc=0.63297 val_adapt_rocauc=0.63773 adapt_steps=3.26 halt=0.32 train_steps=2.75 +[ogbg-molbace_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.7131868131868132} test={'rocauc': 0.8261171970092158} adaptive={'rocauc': 0.8262910798122065} steps=4.006578947368421 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.56081 val_adapt_rocauc=0.58388 adapt_steps=6.43 halt=0.27 train_steps=3.07 +ep20 val_rocauc=0.61245 val_adapt_rocauc=0.59780 adapt_steps=7.42 halt=0.18 train_steps=3.93 +ep30 val_rocauc=0.69084 val_adapt_rocauc=0.69231 adapt_steps=5.89 halt=0.22 train_steps=3.39 +ep40 val_rocauc=0.66154 val_adapt_rocauc=0.66520 adapt_steps=3.93 halt=0.21 train_steps=3.61 +ep50 val_rocauc=0.57399 val_adapt_rocauc=0.60147 adapt_steps=3.54 halt=0.32 train_steps=2.79 +ep60 val_rocauc=0.67546 val_adapt_rocauc=0.69011 adapt_steps=3.45 halt=0.30 train_steps=2.92 +ep70 val_rocauc=0.61099 val_adapt_rocauc=0.62564 adapt_steps=3.86 halt=0.33 train_steps=2.69 +ep80 val_rocauc=0.65275 val_adapt_rocauc=0.65458 adapt_steps=3.17 halt=0.37 train_steps=2.41 +ep90 val_rocauc=0.66740 val_adapt_rocauc=0.66703 adapt_steps=3.09 halt=0.40 train_steps=2.22 +ep100 val_rocauc=0.67766 val_adapt_rocauc=0.67875 adapt_steps=3.11 halt=0.36 train_steps=2.30 +[ogbg-molbace_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.6908424908424909} test={'rocauc': 0.7475221700573813} adaptive={'rocauc': 0.7638671535385151} steps=4.276315789473684 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.63223 val_adapt_rocauc=0.64322 adapt_steps=6.61 halt=0.18 train_steps=3.96 +ep20 val_rocauc=0.54066 val_adapt_rocauc=0.57179 adapt_steps=7.52 halt=0.18 train_steps=3.90 +ep30 val_rocauc=0.51538 val_adapt_rocauc=0.54872 adapt_steps=3.85 halt=0.19 train_steps=3.74 +ep40 val_rocauc=0.61978 val_adapt_rocauc=0.59597 adapt_steps=3.91 halt=0.24 train_steps=3.50 +ep50 val_rocauc=0.57106 val_adapt_rocauc=0.58095 adapt_steps=3.20 halt=0.26 train_steps=3.27 +ep60 val_rocauc=0.62967 val_adapt_rocauc=0.62747 adapt_steps=5.23 halt=0.28 train_steps=3.29 +ep70 val_rocauc=0.61575 val_adapt_rocauc=0.62857 adapt_steps=3.82 halt=0.35 train_steps=2.50 +ep80 val_rocauc=0.65348 val_adapt_rocauc=0.65385 adapt_steps=3.36 halt=0.37 train_steps=2.42 +ep90 val_rocauc=0.64103 val_adapt_rocauc=0.63114 adapt_steps=3.39 halt=0.36 train_steps=2.45 +ep100 val_rocauc=0.64396 val_adapt_rocauc=0.62784 adapt_steps=3.23 halt=0.37 train_steps=2.26 +[ogbg-molbace_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.6534798534798535} test={'rocauc': 0.7191792731698834} adaptive={'rocauc': 0.729264475743349} steps=2.710526315789474 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --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=0.59634 val_adapt_rocauc=0.59707 adapt_steps=7.95 halt=0.19 train_steps=3.73 +/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=0.70952 val_adapt_rocauc=0.58462 adapt_steps=3.56 halt=0.17 train_steps=3.89 +/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=0.62454 val_adapt_rocauc=0.62454 adapt_steps=7.94 halt=0.18 train_steps=3.65 +/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=0.50879 val_adapt_rocauc=0.50623 adapt_steps=7.53 halt=0.13 train_steps=4.40 +/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( +ep50 val_rocauc=0.51941 val_adapt_rocauc=0.51319 adapt_steps=6.01 halt=0.18 train_steps=3.86 +/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=0.64579 val_adapt_rocauc=0.65238 adapt_steps=6.48 halt=0.18 train_steps=3.94 +/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=0.64249 val_adapt_rocauc=0.63333 adapt_steps=4.91 halt=0.24 train_steps=3.31 +/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=0.60293 val_adapt_rocauc=0.60806 adapt_steps=5.57 halt=0.22 train_steps=3.46 +/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=0.61209 val_adapt_rocauc=0.60952 adapt_steps=5.67 halt=0.23 train_steps=3.43 +/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=0.61465 val_adapt_rocauc=0.62491 adapt_steps=6.01 halt=0.23 train_steps=3.48 +[ogbg-molbace_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=20 val={'rocauc': 0.7095238095238096} test={'rocauc': 0.7809076682316118} adaptive={'rocauc': 0.7337854286211093} steps=3.914473684210526 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.43187 val_adapt_rocauc=0.56960 adapt_steps=3.77 halt=0.20 train_steps=4.07 +ep20 val_rocauc=0.58755 val_adapt_rocauc=0.58315 adapt_steps=6.03 halt=0.16 train_steps=4.18 +ep30 val_rocauc=0.65165 val_adapt_rocauc=0.65201 adapt_steps=7.28 halt=0.17 train_steps=4.07 +ep40 val_rocauc=0.56667 val_adapt_rocauc=0.56703 adapt_steps=7.34 halt=0.19 train_steps=3.89 +ep50 val_rocauc=0.56703 val_adapt_rocauc=0.55275 adapt_steps=5.61 halt=0.21 train_steps=3.62 +ep60 val_rocauc=0.65348 val_adapt_rocauc=0.64286 adapt_steps=4.45 halt=0.28 train_steps=3.22 +ep70 val_rocauc=0.60403 val_adapt_rocauc=0.60623 adapt_steps=6.13 halt=0.20 train_steps=3.81 +ep80 val_rocauc=0.61685 val_adapt_rocauc=0.62051 adapt_steps=4.32 halt=0.29 train_steps=2.95 +ep90 val_rocauc=0.62308 val_adapt_rocauc=0.63223 adapt_steps=4.03 halt=0.32 train_steps=2.75 +ep100 val_rocauc=0.63150 val_adapt_rocauc=0.64066 adapt_steps=3.91 halt=0.31 train_steps=2.88 +[ogbg-molbace_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.6534798534798535} test={'rocauc': 0.6915319074943488} adaptive={'rocauc': 0.6788384628760215} steps=3.9802631578947367 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.62637 val_adapt_rocauc=0.61355 adapt_steps=6.25 halt=0.18 train_steps=3.97 +ep20 val_rocauc=0.57436 val_adapt_rocauc=0.57473 adapt_steps=7.62 halt=0.14 train_steps=4.26 +ep30 val_rocauc=0.54359 val_adapt_rocauc=0.56227 adapt_steps=6.98 halt=0.16 train_steps=4.10 +ep40 val_rocauc=0.59689 val_adapt_rocauc=0.58095 adapt_steps=6.34 halt=0.17 train_steps=4.15 +ep50 val_rocauc=0.61868 val_adapt_rocauc=0.61648 adapt_steps=7.64 halt=0.16 train_steps=4.16 +ep60 val_rocauc=0.59634 val_adapt_rocauc=0.59890 adapt_steps=6.07 halt=0.19 train_steps=3.90 +ep70 val_rocauc=0.64670 val_adapt_rocauc=0.64725 adapt_steps=6.14 halt=0.22 train_steps=3.54 +ep80 val_rocauc=0.59744 val_adapt_rocauc=0.59359 adapt_steps=5.54 halt=0.22 train_steps=3.55 +ep90 val_rocauc=0.63333 val_adapt_rocauc=0.63187 adapt_steps=5.75 halt=0.23 train_steps=3.63 +ep100 val_rocauc=0.62381 val_adapt_rocauc=0.61703 adapt_steps=5.77 halt=0.24 train_steps=3.54 +[ogbg-molbace_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.6467032967032967} test={'rocauc': 0.6802295252999478} adaptive={'rocauc': 0.6732742131803164} steps=5.256578947368421 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.61245 val_adapt_rocauc=0.64286 adapt_steps=7.03 halt=0.17 train_steps=3.93 +ep20 val_rocauc=0.53004 val_adapt_rocauc=0.55201 adapt_steps=5.85 halt=0.25 train_steps=3.12 +ep30 val_rocauc=0.69158 val_adapt_rocauc=0.65897 adapt_steps=3.81 halt=0.27 train_steps=3.13 +ep40 val_rocauc=0.58132 val_adapt_rocauc=0.57509 adapt_steps=4.23 halt=0.26 train_steps=3.03 +ep50 val_rocauc=0.73956 val_adapt_rocauc=0.72930 adapt_steps=4.14 halt=0.26 train_steps=3.32 +ep60 val_rocauc=0.67766 val_adapt_rocauc=0.67253 adapt_steps=5.34 halt=0.25 train_steps=3.32 +ep70 val_rocauc=0.72418 val_adapt_rocauc=0.72967 adapt_steps=3.80 halt=0.30 train_steps=2.96 +ep80 val_rocauc=0.71062 val_adapt_rocauc=0.69963 adapt_steps=3.62 halt=0.28 train_steps=3.28 +ep90 val_rocauc=0.71538 val_adapt_rocauc=0.71612 adapt_steps=3.32 halt=0.34 train_steps=2.66 +ep100 val_rocauc=0.69963 val_adapt_rocauc=0.69670 adapt_steps=3.08 halt=0.33 train_steps=2.65 +[ogbg-molbace_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.7395604395604396} test={'rocauc': 0.7313510693792384} adaptive={'rocauc': 0.7617805599026256} steps=3.388157894736842 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.65641 val_adapt_rocauc=0.66630 adapt_steps=5.21 halt=0.15 train_steps=4.34 +ep20 val_rocauc=0.54725 val_adapt_rocauc=0.53040 adapt_steps=4.77 halt=0.20 train_steps=3.52 +ep30 val_rocauc=0.51172 val_adapt_rocauc=0.58132 adapt_steps=4.25 halt=0.18 train_steps=3.92 +ep40 val_rocauc=0.52821 val_adapt_rocauc=0.54835 adapt_steps=2.84 halt=0.30 train_steps=2.92 +ep50 val_rocauc=0.62088 val_adapt_rocauc=0.63736 adapt_steps=3.09 halt=0.32 train_steps=2.79 +ep60 val_rocauc=0.70842 val_adapt_rocauc=0.69707 adapt_steps=2.97 halt=0.36 train_steps=2.52 +ep70 val_rocauc=0.68938 val_adapt_rocauc=0.72711 adapt_steps=3.27 halt=0.35 train_steps=2.61 +ep80 val_rocauc=0.63516 val_adapt_rocauc=0.66667 adapt_steps=2.93 halt=0.39 train_steps=2.19 +ep90 val_rocauc=0.62894 val_adapt_rocauc=0.65861 adapt_steps=2.70 halt=0.39 train_steps=2.17 +ep100 val_rocauc=0.62930 val_adapt_rocauc=0.66154 adapt_steps=2.59 halt=0.40 train_steps=2.06 +[ogbg-molbace_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.7084249084249085} test={'rocauc': 0.7960354720918101} adaptive={'rocauc': 0.7776038949747869} steps=2.5526315789473686 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.56667 val_adapt_rocauc=0.65934 adapt_steps=5.01 halt=0.16 train_steps=4.12 +ep20 val_rocauc=0.62637 val_adapt_rocauc=0.63626 adapt_steps=5.57 halt=0.17 train_steps=4.08 +ep30 val_rocauc=0.57985 val_adapt_rocauc=0.58498 adapt_steps=6.50 halt=0.21 train_steps=3.54 +ep40 val_rocauc=0.64286 val_adapt_rocauc=0.64469 adapt_steps=6.27 halt=0.20 train_steps=3.71 +ep50 val_rocauc=0.65678 val_adapt_rocauc=0.68791 adapt_steps=4.30 halt=0.25 train_steps=3.33 +ep60 val_rocauc=0.66154 val_adapt_rocauc=0.66410 adapt_steps=3.97 halt=0.25 train_steps=3.40 +ep70 val_rocauc=0.64799 val_adapt_rocauc=0.63223 adapt_steps=3.69 halt=0.27 train_steps=3.13 +ep80 val_rocauc=0.63114 val_adapt_rocauc=0.62711 adapt_steps=4.02 halt=0.29 train_steps=3.02 +ep90 val_rocauc=0.64103 val_adapt_rocauc=0.62125 adapt_steps=3.56 halt=0.31 train_steps=2.86 +ep100 val_rocauc=0.63223 val_adapt_rocauc=0.61795 adapt_steps=3.49 halt=0.33 train_steps=2.77 +[ogbg-molbace_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.6615384615384615} test={'rocauc': 0.7970787689097547} adaptive={'rocauc': 0.7988175969396626} steps=3.638157894736842 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.63846 val_adapt_rocauc=0.65495 adapt_steps=4.03 halt=0.18 train_steps=3.80 +ep20 val_rocauc=0.67143 val_adapt_rocauc=0.69011 adapt_steps=4.54 halt=0.19 train_steps=3.98 +ep30 val_rocauc=0.61245 val_adapt_rocauc=0.69084 adapt_steps=3.26 halt=0.28 train_steps=2.95 +ep40 val_rocauc=0.59817 val_adapt_rocauc=0.60879 adapt_steps=3.16 halt=0.28 train_steps=3.20 +ep50 val_rocauc=0.67729 val_adapt_rocauc=0.68498 adapt_steps=3.72 halt=0.33 train_steps=2.63 +ep60 val_rocauc=0.65714 val_adapt_rocauc=0.68938 adapt_steps=3.75 halt=0.34 train_steps=2.55 +ep70 val_rocauc=0.71648 val_adapt_rocauc=0.73810 adapt_steps=2.87 halt=0.41 train_steps=2.00 +ep80 val_rocauc=0.70440 val_adapt_rocauc=0.70366 adapt_steps=2.56 halt=0.42 train_steps=2.02 +ep90 val_rocauc=0.67656 val_adapt_rocauc=0.68315 adapt_steps=2.33 halt=0.46 train_steps=1.67 +ep100 val_rocauc=0.67729 val_adapt_rocauc=0.68352 adapt_steps=2.35 halt=0.45 train_steps=1.70 +[ogbg-molbace_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.7164835164835166} test={'rocauc': 0.8007303077725613} adaptive={'rocauc': 0.8120326899669622} steps=2.598684210526316 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.62711 val_adapt_rocauc=0.60293 adapt_steps=4.62 halt=0.25 train_steps=3.40 +ep20 val_rocauc=0.68095 val_adapt_rocauc=0.63114 adapt_steps=4.19 halt=0.27 train_steps=3.04 +ep30 val_rocauc=0.53516 val_adapt_rocauc=0.52125 adapt_steps=6.76 halt=0.21 train_steps=3.47 +ep40 val_rocauc=0.72564 val_adapt_rocauc=0.74139 adapt_steps=4.15 halt=0.26 train_steps=3.14 +ep50 val_rocauc=0.73553 val_adapt_rocauc=0.73480 adapt_steps=4.72 halt=0.26 train_steps=3.28 +ep60 val_rocauc=0.68278 val_adapt_rocauc=0.61465 adapt_steps=3.82 halt=0.30 train_steps=2.82 +ep70 val_rocauc=0.70659 val_adapt_rocauc=0.71245 adapt_steps=3.50 halt=0.34 train_steps=2.66 +ep80 val_rocauc=0.69853 val_adapt_rocauc=0.68718 adapt_steps=3.68 halt=0.34 train_steps=2.53 +ep90 val_rocauc=0.69597 val_adapt_rocauc=0.68901 adapt_steps=2.83 halt=0.40 train_steps=2.18 +ep100 val_rocauc=0.68828 val_adapt_rocauc=0.67766 adapt_steps=2.85 halt=0.39 train_steps=2.21 +[ogbg-molbace_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.7355311355311356} test={'rocauc': 0.7450878108155102} adaptive={'rocauc': 0.7645626847504782} steps=4.375 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbace view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbace --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:0 --num_workers 0 +ep10 val_rocauc=0.74066 val_adapt_rocauc=0.75311 adapt_steps=6.21 halt=0.21 train_steps=3.61 +ep20 val_rocauc=0.68388 val_adapt_rocauc=0.68755 adapt_steps=6.04 halt=0.22 train_steps=3.45 +ep30 val_rocauc=0.77473 val_adapt_rocauc=0.74725 adapt_steps=5.03 halt=0.19 train_steps=3.88 +ep40 val_rocauc=0.63260 val_adapt_rocauc=0.63773 adapt_steps=5.52 halt=0.26 train_steps=3.11 +ep50 val_rocauc=0.62894 val_adapt_rocauc=0.63260 adapt_steps=3.91 halt=0.29 train_steps=2.98 +ep60 val_rocauc=0.70586 val_adapt_rocauc=0.69927 adapt_steps=3.87 halt=0.29 train_steps=2.99 +ep70 val_rocauc=0.67656 val_adapt_rocauc=0.67619 adapt_steps=3.77 halt=0.33 train_steps=2.76 +ep80 val_rocauc=0.68022 val_adapt_rocauc=0.67326 adapt_steps=3.08 halt=0.33 train_steps=2.72 +ep90 val_rocauc=0.67179 val_adapt_rocauc=0.66740 adapt_steps=2.82 halt=0.38 train_steps=2.33 +ep100 val_rocauc=0.67949 val_adapt_rocauc=0.68205 adapt_steps=2.88 halt=0.39 train_steps=2.19 +[ogbg-molbace_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.7747252747252747} test={'rocauc': 0.8019474873934969} adaptive={'rocauc': 0.7949921752738653} steps=4.980263157894737 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.55678 val_adapt_rocauc=0.62051 adapt_steps=2.15 halt=0.39 train_steps=2.28 +ep20 val_rocauc=0.68352 val_adapt_rocauc=0.65495 adapt_steps=2.36 halt=0.42 train_steps=1.96 +ep30 val_rocauc=0.63700 val_adapt_rocauc=0.65092 adapt_steps=2.30 halt=0.44 train_steps=1.66 +ep40 val_rocauc=0.61429 val_adapt_rocauc=0.60037 adapt_steps=2.01 halt=0.46 train_steps=1.65 +ep50 val_rocauc=0.59414 val_adapt_rocauc=0.59011 adapt_steps=2.03 halt=0.47 train_steps=1.57 +ep60 val_rocauc=0.61868 val_adapt_rocauc=0.59670 adapt_steps=2.00 halt=0.48 train_steps=1.59 +ep70 val_rocauc=0.58901 val_adapt_rocauc=0.60256 adapt_steps=2.00 halt=0.47 train_steps=1.59 +ep80 val_rocauc=0.56923 val_adapt_rocauc=0.58608 adapt_steps=2.00 halt=0.47 train_steps=1.62 +ep90 val_rocauc=0.57839 val_adapt_rocauc=0.60183 adapt_steps=2.00 halt=0.48 train_steps=1.58 +ep100 val_rocauc=0.58059 val_adapt_rocauc=0.60073 adapt_steps=2.00 halt=0.46 train_steps=1.60 +[ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=20 val={'rocauc': 0.6835164835164835} test={'rocauc': 0.7118761954442705} adaptive={'rocauc': 0.7328290732046601} steps=2.1315789473684212 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbace_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json diff --git a/logs/ogbg-molbbbp_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-molbbbp_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..1402929 --- /dev/null +++ b/logs/ogbg-molbbbp_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,278 @@ +[run] ogbg-molbbbp view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.68724 val_adapt_rocauc=0.69058 adapt_steps=2.34 halt=0.32 train_steps=2.70 +ep20 val_rocauc=0.71443 val_adapt_rocauc=0.73106 adapt_steps=4.76 halt=0.35 train_steps=2.43 +ep30 val_rocauc=0.89704 val_adapt_rocauc=0.89107 adapt_steps=2.92 halt=0.32 train_steps=2.76 +ep40 val_rocauc=0.92044 val_adapt_rocauc=0.93149 adapt_steps=3.13 halt=0.31 train_steps=2.82 +ep50 val_rocauc=0.89326 val_adapt_rocauc=0.91984 adapt_steps=2.52 halt=0.34 train_steps=2.62 +ep60 val_rocauc=0.88529 val_adapt_rocauc=0.90411 adapt_steps=2.35 halt=0.39 train_steps=2.28 +ep70 val_rocauc=0.86876 val_adapt_rocauc=0.88728 adapt_steps=2.40 halt=0.38 train_steps=2.31 +ep80 val_rocauc=0.90929 val_adapt_rocauc=0.91228 adapt_steps=2.47 halt=0.38 train_steps=2.27 +ep90 val_rocauc=0.90491 val_adapt_rocauc=0.90760 adapt_steps=2.26 halt=0.42 train_steps=2.01 +ep100 val_rocauc=0.90979 val_adapt_rocauc=0.91825 adapt_steps=2.25 halt=0.41 train_steps=2.05 +[ogbg-molbbbp_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.92044209897441} test={'rocauc': 0.6527777777777778} adaptive={'rocauc': 0.65258487654321} steps=4.872549019607843 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.90073 val_adapt_rocauc=0.88450 adapt_steps=2.43 halt=0.27 train_steps=3.20 +ep20 val_rocauc=0.92024 val_adapt_rocauc=0.93090 adapt_steps=3.02 halt=0.32 train_steps=2.63 +ep30 val_rocauc=0.85622 val_adapt_rocauc=0.87673 adapt_steps=3.15 halt=0.34 train_steps=2.57 +ep40 val_rocauc=0.89276 val_adapt_rocauc=0.88928 adapt_steps=3.26 halt=0.33 train_steps=2.70 +ep50 val_rocauc=0.91795 val_adapt_rocauc=0.92114 adapt_steps=2.88 halt=0.34 train_steps=2.67 +ep60 val_rocauc=0.91696 val_adapt_rocauc=0.90889 adapt_steps=2.46 halt=0.36 train_steps=2.44 +ep70 val_rocauc=0.90501 val_adapt_rocauc=0.89037 adapt_steps=2.88 halt=0.38 train_steps=2.30 +ep80 val_rocauc=0.92054 val_adapt_rocauc=0.91228 adapt_steps=2.57 halt=0.39 train_steps=2.24 +ep90 val_rocauc=0.90949 val_adapt_rocauc=0.90312 adapt_steps=2.32 halt=0.41 train_steps=2.07 +ep100 val_rocauc=0.91576 val_adapt_rocauc=0.91148 adapt_steps=2.29 halt=0.42 train_steps=2.02 +[ogbg-molbbbp_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.9205416708154933} test={'rocauc': 0.591820987654321} adaptive={'rocauc': 0.5948109567901234} steps=2.9166666666666665 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.82177 val_adapt_rocauc=0.93209 adapt_steps=2.11 halt=0.30 train_steps=2.97 +ep20 val_rocauc=0.88241 val_adapt_rocauc=0.89923 adapt_steps=2.39 halt=0.38 train_steps=2.27 +ep30 val_rocauc=0.84248 val_adapt_rocauc=0.89794 adapt_steps=2.54 halt=0.38 train_steps=2.19 +ep40 val_rocauc=0.95280 val_adapt_rocauc=0.95390 adapt_steps=2.17 halt=0.41 train_steps=2.07 +ep50 val_rocauc=0.89525 val_adapt_rocauc=0.92164 adapt_steps=2.07 halt=0.45 train_steps=1.74 +ep60 val_rocauc=0.93727 val_adapt_rocauc=0.93050 adapt_steps=2.03 halt=0.45 train_steps=1.73 +ep70 val_rocauc=0.92612 val_adapt_rocauc=0.92881 adapt_steps=2.03 halt=0.46 train_steps=1.68 +ep80 val_rocauc=0.91845 val_adapt_rocauc=0.92273 adapt_steps=2.01 halt=0.47 train_steps=1.61 +ep90 val_rocauc=0.91278 val_adapt_rocauc=0.91138 adapt_steps=2.00 halt=0.47 train_steps=1.66 +ep100 val_rocauc=0.91477 val_adapt_rocauc=0.91626 adapt_steps=2.00 halt=0.47 train_steps=1.66 +[ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.9528029473264961} test={'rocauc': 0.6794945987654321} adaptive={'rocauc': 0.6629050925925926} steps=2.269607843137255 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.94066 val_adapt_rocauc=0.95440 adapt_steps=2.54 halt=0.30 train_steps=2.86 +ep20 val_rocauc=0.93299 val_adapt_rocauc=0.93956 adapt_steps=2.87 halt=0.38 train_steps=2.26 +ep30 val_rocauc=0.83142 val_adapt_rocauc=0.88171 adapt_steps=2.41 halt=0.36 train_steps=2.40 +ep40 val_rocauc=0.87494 val_adapt_rocauc=0.87374 adapt_steps=2.28 halt=0.40 train_steps=2.07 +ep50 val_rocauc=0.92233 val_adapt_rocauc=0.94285 adapt_steps=2.27 halt=0.38 train_steps=2.38 +ep60 val_rocauc=0.86478 val_adapt_rocauc=0.88539 adapt_steps=2.44 halt=0.40 train_steps=2.08 +ep70 val_rocauc=0.91029 val_adapt_rocauc=0.91377 adapt_steps=2.14 halt=0.45 train_steps=1.75 +ep80 val_rocauc=0.92532 val_adapt_rocauc=0.91218 adapt_steps=2.07 halt=0.46 train_steps=1.68 +ep90 val_rocauc=0.90630 val_adapt_rocauc=0.90202 adapt_steps=2.06 halt=0.45 train_steps=1.73 +ep100 val_rocauc=0.90531 val_adapt_rocauc=0.90083 adapt_steps=2.04 halt=0.46 train_steps=1.67 +[ogbg-molbbbp_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=10 val={'rocauc': 0.9406551827143284} test={'rocauc': 0.6039737654320988} adaptive={'rocauc': 0.6147762345679012} steps=2.5686274509803924 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.87544 val_adapt_rocauc=0.89704 adapt_steps=3.72 halt=0.33 train_steps=2.64 +ep20 val_rocauc=0.92492 val_adapt_rocauc=0.94852 adapt_steps=2.61 halt=0.39 train_steps=2.17 +ep30 val_rocauc=0.89804 val_adapt_rocauc=0.93239 adapt_steps=2.27 halt=0.37 train_steps=2.35 +ep40 val_rocauc=0.90511 val_adapt_rocauc=0.92612 adapt_steps=2.27 halt=0.41 train_steps=2.00 +ep50 val_rocauc=0.90103 val_adapt_rocauc=0.89475 adapt_steps=2.46 halt=0.41 train_steps=2.01 +ep60 val_rocauc=0.90401 val_adapt_rocauc=0.89306 adapt_steps=2.24 halt=0.41 train_steps=2.05 +ep70 val_rocauc=0.93030 val_adapt_rocauc=0.91656 adapt_steps=2.10 halt=0.46 train_steps=1.67 +ep80 val_rocauc=0.92233 val_adapt_rocauc=0.90411 adapt_steps=2.09 halt=0.46 train_steps=1.66 +ep90 val_rocauc=0.91546 val_adapt_rocauc=0.89386 adapt_steps=2.11 halt=0.46 train_steps=1.70 +ep100 val_rocauc=0.91287 val_adapt_rocauc=0.88868 adapt_steps=2.09 halt=0.47 train_steps=1.65 +[ogbg-molbbbp_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.9302997112416609} test={'rocauc': 0.6648341049382716} adaptive={'rocauc': 0.6627121913580247} steps=2.1372549019607843 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.83053 val_adapt_rocauc=0.84875 adapt_steps=3.46 halt=0.34 train_steps=2.62 +ep20 val_rocauc=0.71931 val_adapt_rocauc=0.75465 adapt_steps=3.00 halt=0.37 train_steps=2.40 +ep30 val_rocauc=0.88380 val_adapt_rocauc=0.89704 adapt_steps=2.44 halt=0.37 train_steps=2.40 +ep40 val_rocauc=0.89913 val_adapt_rocauc=0.91507 adapt_steps=2.17 halt=0.37 train_steps=2.35 +ep50 val_rocauc=0.88938 val_adapt_rocauc=0.93737 adapt_steps=2.25 halt=0.43 train_steps=1.90 +ep60 val_rocauc=0.92343 val_adapt_rocauc=0.93757 adapt_steps=2.21 halt=0.41 train_steps=2.04 +ep70 val_rocauc=0.87703 val_adapt_rocauc=0.90889 adapt_steps=2.45 halt=0.41 train_steps=1.97 +ep80 val_rocauc=0.89396 val_adapt_rocauc=0.91726 adapt_steps=2.09 halt=0.46 train_steps=1.73 +ep90 val_rocauc=0.86498 val_adapt_rocauc=0.89167 adapt_steps=2.19 halt=0.46 train_steps=1.70 +ep100 val_rocauc=0.87016 val_adapt_rocauc=0.89545 adapt_steps=2.13 halt=0.47 train_steps=1.68 +[ogbg-molbbbp_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.9234292542069104} test={'rocauc': 0.6602044753086419} adaptive={'rocauc': 0.6875} steps=2.7941176470588234 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.87494 val_adapt_rocauc=0.89316 adapt_steps=3.50 halt=0.33 train_steps=2.53 +ep20 val_rocauc=0.88878 val_adapt_rocauc=0.89784 adapt_steps=2.60 halt=0.35 train_steps=2.46 +ep30 val_rocauc=0.85243 val_adapt_rocauc=0.93747 adapt_steps=2.47 halt=0.36 train_steps=2.40 +ep40 val_rocauc=0.93687 val_adapt_rocauc=0.94046 adapt_steps=2.35 halt=0.41 train_steps=2.09 +ep50 val_rocauc=0.90959 val_adapt_rocauc=0.91875 adapt_steps=2.32 halt=0.41 train_steps=2.16 +ep60 val_rocauc=0.93090 val_adapt_rocauc=0.93617 adapt_steps=2.40 halt=0.42 train_steps=1.90 +ep70 val_rocauc=0.93199 val_adapt_rocauc=0.92134 adapt_steps=2.23 halt=0.45 train_steps=1.72 +ep80 val_rocauc=0.93637 val_adapt_rocauc=0.93866 adapt_steps=2.15 halt=0.45 train_steps=1.78 +ep90 val_rocauc=0.93976 val_adapt_rocauc=0.93378 adapt_steps=2.13 halt=0.45 train_steps=1.81 +ep100 val_rocauc=0.93966 val_adapt_rocauc=0.93369 adapt_steps=2.13 halt=0.45 train_steps=1.79 +[ogbg-molbbbp_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.9397590361445782} test={'rocauc': 0.642554012345679} adaptive={'rocauc': 0.6309799382716049} steps=2.2254901960784315 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --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=0.92731 val_adapt_rocauc=0.92950 adapt_steps=6.11 halt=0.24 train_steps=3.52 +/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=0.89097 val_adapt_rocauc=0.90093 adapt_steps=2.08 halt=0.32 train_steps=2.95 +/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=0.92433 val_adapt_rocauc=0.92502 adapt_steps=3.31 halt=0.34 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( +ep40 val_rocauc=0.93777 val_adapt_rocauc=0.94056 adapt_steps=2.97 halt=0.35 train_steps=2.49 +/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=0.95001 val_adapt_rocauc=0.95051 adapt_steps=3.67 halt=0.31 train_steps=2.90 +/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=0.91317 val_adapt_rocauc=0.89913 adapt_steps=2.84 halt=0.37 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=0.94583 val_adapt_rocauc=0.94613 adapt_steps=2.63 halt=0.36 train_steps=2.49 +/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=0.90770 val_adapt_rocauc=0.90132 adapt_steps=2.44 halt=0.39 train_steps=2.22 +/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=0.92761 val_adapt_rocauc=0.92482 adapt_steps=2.29 halt=0.42 train_steps=1.98 +/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=0.92871 val_adapt_rocauc=0.92612 adapt_steps=2.34 halt=0.43 train_steps=1.94 +[ogbg-molbbbp_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.9500149357761626} test={'rocauc': 0.6172839506172839} adaptive={'rocauc': 0.6179591049382716} steps=4.686274509803922 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.78104 val_adapt_rocauc=0.86747 adapt_steps=2.68 halt=0.35 train_steps=2.43 +ep20 val_rocauc=0.89664 val_adapt_rocauc=0.89754 adapt_steps=4.28 halt=0.31 train_steps=2.84 +ep30 val_rocauc=0.92512 val_adapt_rocauc=0.92114 adapt_steps=4.62 halt=0.30 train_steps=3.15 +ep40 val_rocauc=0.88798 val_adapt_rocauc=0.86727 adapt_steps=3.66 halt=0.35 train_steps=2.40 +ep50 val_rocauc=0.92383 val_adapt_rocauc=0.93737 adapt_steps=2.48 halt=0.35 train_steps=2.51 +ep60 val_rocauc=0.91218 val_adapt_rocauc=0.91278 adapt_steps=2.67 halt=0.37 train_steps=2.35 +ep70 val_rocauc=0.90083 val_adapt_rocauc=0.91785 adapt_steps=2.15 halt=0.40 train_steps=2.04 +ep80 val_rocauc=0.91646 val_adapt_rocauc=0.92612 adapt_steps=2.24 halt=0.43 train_steps=1.95 +ep90 val_rocauc=0.91616 val_adapt_rocauc=0.92751 adapt_steps=2.23 halt=0.45 train_steps=1.79 +ep100 val_rocauc=0.90909 val_adapt_rocauc=0.91865 adapt_steps=2.24 halt=0.44 train_steps=1.86 +[ogbg-molbbbp_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.925121975505327} test={'rocauc': 0.6313657407407408} adaptive={'rocauc': 0.6291473765432098} steps=3.7892156862745097 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.65558 val_adapt_rocauc=0.57483 adapt_steps=4.25 halt=0.29 train_steps=2.83 +ep20 val_rocauc=0.89615 val_adapt_rocauc=0.88997 adapt_steps=4.61 halt=0.29 train_steps=3.15 +ep30 val_rocauc=0.91606 val_adapt_rocauc=0.91606 adapt_steps=3.94 halt=0.30 train_steps=2.97 +ep40 val_rocauc=0.87683 val_adapt_rocauc=0.88221 adapt_steps=3.41 halt=0.27 train_steps=3.07 +ep50 val_rocauc=0.93926 val_adapt_rocauc=0.94832 adapt_steps=2.70 halt=0.29 train_steps=3.03 +ep60 val_rocauc=0.92204 val_adapt_rocauc=0.92881 adapt_steps=3.16 halt=0.29 train_steps=2.99 +ep70 val_rocauc=0.89714 val_adapt_rocauc=0.90451 adapt_steps=2.59 halt=0.34 train_steps=2.64 +ep80 val_rocauc=0.91835 val_adapt_rocauc=0.92413 adapt_steps=2.57 halt=0.35 train_steps=2.65 +ep90 val_rocauc=0.91048 val_adapt_rocauc=0.91745 adapt_steps=2.50 halt=0.34 train_steps=2.57 +ep100 val_rocauc=0.92582 val_adapt_rocauc=0.93189 adapt_steps=2.41 halt=0.37 train_steps=2.51 +[ogbg-molbbbp_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.9392611769391616} test={'rocauc': 0.5584490740740741} adaptive={'rocauc': 0.5745563271604939} steps=3.2058823529411766 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.79478 val_adapt_rocauc=0.79906 adapt_steps=4.00 halt=0.30 train_steps=2.83 +ep20 val_rocauc=0.90192 val_adapt_rocauc=0.90431 adapt_steps=2.94 halt=0.36 train_steps=2.35 +ep30 val_rocauc=0.91327 val_adapt_rocauc=0.93100 adapt_steps=2.63 halt=0.36 train_steps=2.32 +ep40 val_rocauc=0.88051 val_adapt_rocauc=0.89535 adapt_steps=2.30 halt=0.37 train_steps=2.38 +ep50 val_rocauc=0.90401 val_adapt_rocauc=0.90829 adapt_steps=2.96 halt=0.37 train_steps=2.33 +ep60 val_rocauc=0.86060 val_adapt_rocauc=0.87822 adapt_steps=2.16 halt=0.41 train_steps=2.03 +ep70 val_rocauc=0.90859 val_adapt_rocauc=0.90770 adapt_steps=2.04 halt=0.44 train_steps=1.88 +ep80 val_rocauc=0.89893 val_adapt_rocauc=0.90581 adapt_steps=2.04 halt=0.45 train_steps=1.76 +ep90 val_rocauc=0.89824 val_adapt_rocauc=0.89893 adapt_steps=2.02 halt=0.45 train_steps=1.72 +ep100 val_rocauc=0.89206 val_adapt_rocauc=0.89406 adapt_steps=2.01 halt=0.45 train_steps=1.74 +[ogbg-molbbbp_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.9132729264164094} test={'rocauc': 0.5753279320987655} adaptive={'rocauc': 0.5887345679012346} steps=3.593137254901961 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.79010 val_adapt_rocauc=0.90242 adapt_steps=2.69 halt=0.30 train_steps=2.96 +ep20 val_rocauc=0.78353 val_adapt_rocauc=0.88868 adapt_steps=2.15 halt=0.32 train_steps=2.81 +ep30 val_rocauc=0.94344 val_adapt_rocauc=0.94145 adapt_steps=2.73 halt=0.38 train_steps=2.31 +ep40 val_rocauc=0.86787 val_adapt_rocauc=0.89565 adapt_steps=2.29 halt=0.39 train_steps=2.18 +ep50 val_rocauc=0.94962 val_adapt_rocauc=0.95420 adapt_steps=2.25 halt=0.40 train_steps=2.20 +ep60 val_rocauc=0.93269 val_adapt_rocauc=0.94374 adapt_steps=2.16 halt=0.41 train_steps=2.00 +ep70 val_rocauc=0.93996 val_adapt_rocauc=0.94155 adapt_steps=2.23 halt=0.42 train_steps=1.93 +ep80 val_rocauc=0.93727 val_adapt_rocauc=0.93598 adapt_steps=2.08 halt=0.46 train_steps=1.75 +ep90 val_rocauc=0.93508 val_adapt_rocauc=0.92691 adapt_steps=2.04 halt=0.46 train_steps=1.73 +ep100 val_rocauc=0.93717 val_adapt_rocauc=0.92980 adapt_steps=2.02 halt=0.46 train_steps=1.69 +[ogbg-molbbbp_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.9496166484118291} test={'rocauc': 0.6579861111111112} adaptive={'rocauc': 0.6550925925925926} steps=2.6176470588235294 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.65259 val_adapt_rocauc=0.79578 adapt_steps=2.69 halt=0.32 train_steps=2.68 +ep20 val_rocauc=0.92612 val_adapt_rocauc=0.94066 adapt_steps=2.18 halt=0.38 train_steps=2.24 +ep30 val_rocauc=0.93478 val_adapt_rocauc=0.94484 adapt_steps=2.27 halt=0.34 train_steps=2.50 +ep40 val_rocauc=0.91576 val_adapt_rocauc=0.94056 adapt_steps=2.19 halt=0.42 train_steps=2.00 +ep50 val_rocauc=0.90760 val_adapt_rocauc=0.92552 adapt_steps=2.36 halt=0.41 train_steps=2.02 +ep60 val_rocauc=0.94753 val_adapt_rocauc=0.95798 adapt_steps=2.07 halt=0.45 train_steps=1.74 +ep70 val_rocauc=0.93647 val_adapt_rocauc=0.94066 adapt_steps=2.13 halt=0.46 train_steps=1.65 +ep80 val_rocauc=0.93289 val_adapt_rocauc=0.93777 adapt_steps=2.06 halt=0.46 train_steps=1.67 +ep90 val_rocauc=0.93817 val_adapt_rocauc=0.94165 adapt_steps=2.05 halt=0.47 train_steps=1.68 +ep100 val_rocauc=0.93757 val_adapt_rocauc=0.93916 adapt_steps=2.03 halt=0.46 train_steps=1.68 +[ogbg-molbbbp_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.947525639749079} test={'rocauc': 0.6593364197530864} adaptive={'rocauc': 0.6675347222222222} steps=2.2549019607843137 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.79966 val_adapt_rocauc=0.83352 adapt_steps=2.95 halt=0.33 train_steps=2.69 +ep20 val_rocauc=0.87763 val_adapt_rocauc=0.88738 adapt_steps=2.30 halt=0.38 train_steps=2.38 +ep30 val_rocauc=0.83511 val_adapt_rocauc=0.87225 adapt_steps=2.24 halt=0.40 train_steps=2.04 +ep40 val_rocauc=0.93578 val_adapt_rocauc=0.94066 adapt_steps=2.38 halt=0.41 train_steps=2.09 +ep50 val_rocauc=0.92881 val_adapt_rocauc=0.92642 adapt_steps=2.17 halt=0.44 train_steps=1.85 +ep60 val_rocauc=0.92353 val_adapt_rocauc=0.91337 adapt_steps=2.12 halt=0.45 train_steps=1.78 +ep70 val_rocauc=0.94962 val_adapt_rocauc=0.94494 adapt_steps=2.03 halt=0.46 train_steps=1.65 +ep80 val_rocauc=0.93986 val_adapt_rocauc=0.93508 adapt_steps=2.13 halt=0.47 train_steps=1.65 +ep90 val_rocauc=0.93080 val_adapt_rocauc=0.91835 adapt_steps=2.03 halt=0.46 train_steps=1.72 +ep100 val_rocauc=0.92433 val_adapt_rocauc=0.91208 adapt_steps=2.03 halt=0.45 train_steps=1.80 +[ogbg-molbbbp_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.9496166484118291} test={'rocauc': 0.6182484567901234} adaptive={'rocauc': 0.611014660493827} steps=2.1666666666666665 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.55989 val_adapt_rocauc=0.61585 adapt_steps=2.59 halt=0.37 train_steps=2.15 +ep20 val_rocauc=0.88748 val_adapt_rocauc=0.93000 adapt_steps=2.67 halt=0.40 train_steps=2.09 +ep30 val_rocauc=0.90172 val_adapt_rocauc=0.91427 adapt_steps=2.22 halt=0.39 train_steps=2.27 +ep40 val_rocauc=0.93269 val_adapt_rocauc=0.93189 adapt_steps=2.33 halt=0.38 train_steps=2.31 +ep50 val_rocauc=0.92771 val_adapt_rocauc=0.92433 adapt_steps=2.20 halt=0.46 train_steps=1.75 +ep60 val_rocauc=0.91228 val_adapt_rocauc=0.91984 adapt_steps=2.14 halt=0.44 train_steps=1.83 +ep70 val_rocauc=0.94046 val_adapt_rocauc=0.93757 adapt_steps=2.02 halt=0.45 train_steps=1.70 +ep80 val_rocauc=0.92273 val_adapt_rocauc=0.92801 adapt_steps=2.06 halt=0.47 train_steps=1.64 +ep90 val_rocauc=0.92154 val_adapt_rocauc=0.92542 adapt_steps=2.08 halt=0.45 train_steps=1.79 +ep100 val_rocauc=0.91845 val_adapt_rocauc=0.92233 adapt_steps=2.07 halt=0.46 train_steps=1.74 +[ogbg-molbbbp_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.9404560390321618} test={'rocauc': 0.6411072530864197} adaptive={'rocauc': 0.636766975308642} steps=2.1519607843137254 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molbbbp view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molbbbp --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:0 --num_workers 0 +ep10 val_rocauc=0.70109 val_adapt_rocauc=0.81280 adapt_steps=2.37 halt=0.29 train_steps=2.98 +ep20 val_rocauc=0.91815 val_adapt_rocauc=0.92184 adapt_steps=3.19 halt=0.33 train_steps=2.59 +ep30 val_rocauc=0.93030 val_adapt_rocauc=0.94095 adapt_steps=2.34 halt=0.36 train_steps=2.50 +ep40 val_rocauc=0.93677 val_adapt_rocauc=0.94534 adapt_steps=2.69 halt=0.35 train_steps=2.51 +ep50 val_rocauc=0.91098 val_adapt_rocauc=0.91238 adapt_steps=2.40 halt=0.38 train_steps=2.23 +ep60 val_rocauc=0.92184 val_adapt_rocauc=0.92672 adapt_steps=2.20 halt=0.44 train_steps=1.87 +ep70 val_rocauc=0.93598 val_adapt_rocauc=0.93926 adapt_steps=2.13 halt=0.45 train_steps=1.70 +ep80 val_rocauc=0.90790 val_adapt_rocauc=0.91785 adapt_steps=2.10 halt=0.47 train_steps=1.64 +ep90 val_rocauc=0.89864 val_adapt_rocauc=0.91019 adapt_steps=2.09 halt=0.47 train_steps=1.65 +ep100 val_rocauc=0.89406 val_adapt_rocauc=0.90561 adapt_steps=2.11 halt=0.46 train_steps=1.70 +[ogbg-molbbbp_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.936771880912078} test={'rocauc': 0.662133487654321} adaptive={'rocauc': 0.667824074074074} steps=3.5441176470588234 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.84975 val_adapt_rocauc=0.88719 adapt_steps=2.18 halt=0.43 train_steps=1.80 +ep20 val_rocauc=0.88748 val_adapt_rocauc=0.92572 adapt_steps=2.08 halt=0.47 train_steps=1.62 +ep30 val_rocauc=0.78114 val_adapt_rocauc=0.87962 adapt_steps=2.04 halt=0.46 train_steps=1.63 +ep40 val_rocauc=0.86936 val_adapt_rocauc=0.91825 adapt_steps=2.01 halt=0.47 train_steps=1.63 +ep50 val_rocauc=0.90660 val_adapt_rocauc=0.93378 adapt_steps=2.00 halt=0.46 train_steps=1.65 +ep60 val_rocauc=0.82316 val_adapt_rocauc=0.90620 adapt_steps=2.01 halt=0.46 train_steps=1.68 +ep70 val_rocauc=0.86389 val_adapt_rocauc=0.90242 adapt_steps=2.00 halt=0.46 train_steps=1.70 +ep80 val_rocauc=0.82684 val_adapt_rocauc=0.89884 adapt_steps=2.02 halt=0.46 train_steps=1.68 +ep90 val_rocauc=0.81639 val_adapt_rocauc=0.89884 adapt_steps=2.01 halt=0.47 train_steps=1.70 +ep100 val_rocauc=0.82445 val_adapt_rocauc=0.90192 adapt_steps=2.01 halt=0.46 train_steps=1.64 +[ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.9066016130638256} test={'rocauc': 0.5573881172839507} adaptive={'rocauc': 0.6225887345679013} steps=2.014705882352941 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molbbbp_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json diff --git a/logs/ogbg-molclintox_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-molclintox_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..fdfc936 --- /dev/null +++ b/logs/ogbg-molclintox_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,278 @@ +[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 diff --git a/logs/ogbg-molesol_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-molesol_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..cd5a0e1 --- /dev/null +++ b/logs/ogbg-molesol_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,242 @@ +[run] ogbg-molesol view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gin --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.63809 val_adapt_rmse=2.39395 adapt_steps=6.48 halt=0.19 train_steps=3.84 +ep20 val_rmse=4.26988 val_adapt_rmse=3.11447 adapt_steps=3.99 halt=0.16 train_steps=4.33 +ep30 val_rmse=4.14634 val_adapt_rmse=3.52731 adapt_steps=4.76 halt=0.16 train_steps=4.14 +ep40 val_rmse=2.34153 val_adapt_rmse=1.55824 adapt_steps=2.54 halt=0.29 train_steps=2.64 +ep50 val_rmse=2.10126 val_adapt_rmse=1.29124 adapt_steps=2.93 halt=0.34 train_steps=2.23 +ep60 val_rmse=1.97711 val_adapt_rmse=1.38502 adapt_steps=3.55 halt=0.29 train_steps=2.55 +ep70 val_rmse=1.85198 val_adapt_rmse=1.17093 adapt_steps=2.89 halt=0.35 train_steps=2.24 +ep80 val_rmse=1.40467 val_adapt_rmse=0.94661 adapt_steps=2.88 halt=0.37 train_steps=2.11 +ep90 val_rmse=1.51603 val_adapt_rmse=0.96581 adapt_steps=2.71 halt=0.39 train_steps=1.94 +ep100 val_rmse=1.55791 val_adapt_rmse=0.98643 adapt_steps=2.61 halt=0.40 train_steps=1.96 +[ogbg-molesol_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.4046698)} test={'rmse': np.float32(2.0651195)} adaptive={'rmse': np.float32(0.96633816)} steps=2.982300884955752 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gine --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=3.38193 val_adapt_rmse=3.24861 adapt_steps=5.82 halt=0.18 train_steps=4.23 +ep20 val_rmse=2.14610 val_adapt_rmse=1.81691 adapt_steps=4.67 halt=0.18 train_steps=3.98 +ep30 val_rmse=2.42302 val_adapt_rmse=2.12907 adapt_steps=4.80 halt=0.19 train_steps=3.43 +ep40 val_rmse=1.72178 val_adapt_rmse=1.35344 adapt_steps=4.30 halt=0.24 train_steps=3.14 +ep50 val_rmse=2.54499 val_adapt_rmse=1.50567 adapt_steps=2.35 halt=0.30 train_steps=2.66 +ep60 val_rmse=1.52869 val_adapt_rmse=1.10370 adapt_steps=3.33 halt=0.34 train_steps=2.66 +ep70 val_rmse=1.72160 val_adapt_rmse=1.01718 adapt_steps=3.65 halt=0.35 train_steps=2.32 +ep80 val_rmse=1.64223 val_adapt_rmse=1.07042 adapt_steps=2.33 halt=0.38 train_steps=2.24 +ep90 val_rmse=1.31103 val_adapt_rmse=1.01651 adapt_steps=2.51 halt=0.41 train_steps=2.03 +ep100 val_rmse=1.36548 val_adapt_rmse=1.01212 adapt_steps=2.47 halt=0.40 train_steps=2.11 +[ogbg-molesol_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(1.3110343)} test={'rmse': np.float32(2.0394285)} adaptive={'rmse': np.float32(1.0992771)} steps=2.8849557522123894 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gcn --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.02916 val_adapt_rmse=1.75337 adapt_steps=4.50 halt=0.23 train_steps=3.50 +ep20 val_rmse=1.54387 val_adapt_rmse=1.38205 adapt_steps=4.77 halt=0.22 train_steps=3.63 +ep30 val_rmse=1.69653 val_adapt_rmse=1.49022 adapt_steps=4.99 halt=0.22 train_steps=3.20 +ep40 val_rmse=2.92037 val_adapt_rmse=1.90808 adapt_steps=3.73 halt=0.25 train_steps=3.16 +ep50 val_rmse=1.03997 val_adapt_rmse=0.90930 adapt_steps=3.62 halt=0.29 train_steps=2.79 +ep60 val_rmse=1.07837 val_adapt_rmse=1.00303 adapt_steps=3.17 halt=0.39 train_steps=2.10 +ep70 val_rmse=1.16818 val_adapt_rmse=0.92152 adapt_steps=3.02 halt=0.38 train_steps=2.08 +ep80 val_rmse=1.08067 val_adapt_rmse=0.92960 adapt_steps=3.04 halt=0.38 train_steps=2.18 +ep90 val_rmse=1.02939 val_adapt_rmse=0.87992 adapt_steps=2.79 halt=0.40 train_steps=2.00 +ep100 val_rmse=1.04713 val_adapt_rmse=0.88052 adapt_steps=2.70 halt=0.40 train_steps=1.98 +[ogbg-molesol_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(1.0293915)} test={'rmse': np.float32(1.2572919)} adaptive={'rmse': np.float32(0.92217094)} steps=2.7168141592920354 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view graphsage --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.09992 val_adapt_rmse=1.91741 adapt_steps=5.06 halt=0.15 train_steps=4.24 +ep20 val_rmse=1.34611 val_adapt_rmse=1.17463 adapt_steps=3.27 halt=0.20 train_steps=3.81 +ep30 val_rmse=2.05686 val_adapt_rmse=1.52317 adapt_steps=3.48 halt=0.24 train_steps=3.01 +ep40 val_rmse=1.58216 val_adapt_rmse=1.15681 adapt_steps=2.60 halt=0.34 train_steps=2.19 +ep50 val_rmse=1.32595 val_adapt_rmse=1.11669 adapt_steps=3.81 halt=0.24 train_steps=2.77 +ep60 val_rmse=1.68484 val_adapt_rmse=1.33655 adapt_steps=2.79 halt=0.38 train_steps=2.03 +ep70 val_rmse=1.46531 val_adapt_rmse=1.02634 adapt_steps=2.50 halt=0.36 train_steps=2.18 +ep80 val_rmse=1.21621 val_adapt_rmse=0.92526 adapt_steps=2.48 halt=0.40 train_steps=1.95 +ep90 val_rmse=1.15871 val_adapt_rmse=0.92033 adapt_steps=2.41 halt=0.43 train_steps=1.76 +ep100 val_rmse=1.19358 val_adapt_rmse=0.92401 adapt_steps=2.24 halt=0.44 train_steps=1.82 +[ogbg-molesol_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(1.1587086)} test={'rmse': np.float32(1.3228503)} adaptive={'rmse': np.float32(0.9323515)} steps=2.398230088495575 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gatv2 --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.71115 val_adapt_rmse=1.59292 adapt_steps=5.16 halt=0.19 train_steps=3.79 +ep20 val_rmse=2.04041 val_adapt_rmse=1.48254 adapt_steps=3.27 halt=0.19 train_steps=3.61 +ep30 val_rmse=2.19314 val_adapt_rmse=1.41846 adapt_steps=2.98 halt=0.26 train_steps=3.01 +ep40 val_rmse=1.26104 val_adapt_rmse=1.11810 adapt_steps=2.53 halt=0.31 train_steps=2.64 +ep50 val_rmse=1.35004 val_adapt_rmse=1.06584 adapt_steps=3.13 halt=0.32 train_steps=2.50 +ep60 val_rmse=1.14151 val_adapt_rmse=0.91810 adapt_steps=2.64 halt=0.39 train_steps=2.00 +ep70 val_rmse=1.08552 val_adapt_rmse=0.98888 adapt_steps=3.42 halt=0.35 train_steps=2.30 +ep80 val_rmse=1.01822 val_adapt_rmse=0.95246 adapt_steps=2.61 halt=0.44 train_steps=1.82 +ep90 val_rmse=0.98423 val_adapt_rmse=0.94151 adapt_steps=2.59 halt=0.44 train_steps=1.75 +ep100 val_rmse=1.02002 val_adapt_rmse=0.97264 adapt_steps=2.60 halt=0.46 train_steps=1.75 +[ogbg-molesol_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(0.9842344)} test={'rmse': np.float32(0.95342916)} adaptive={'rmse': np.float32(0.88059396)} steps=2.4867256637168142 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view graphconv --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=3.24691 val_adapt_rmse=3.06485 adapt_steps=5.43 halt=0.16 train_steps=4.14 +ep20 val_rmse=2.19544 val_adapt_rmse=1.92386 adapt_steps=4.11 halt=0.22 train_steps=3.14 +ep30 val_rmse=1.85038 val_adapt_rmse=1.84516 adapt_steps=5.91 halt=0.20 train_steps=3.80 +ep40 val_rmse=1.80320 val_adapt_rmse=1.53707 adapt_steps=4.28 halt=0.24 train_steps=3.32 +ep50 val_rmse=1.61943 val_adapt_rmse=1.16471 adapt_steps=4.05 halt=0.34 train_steps=2.62 +ep60 val_rmse=1.38128 val_adapt_rmse=1.12648 adapt_steps=4.63 halt=0.30 train_steps=2.80 +ep70 val_rmse=1.15362 val_adapt_rmse=0.98844 adapt_steps=2.86 halt=0.38 train_steps=2.03 +ep80 val_rmse=1.14805 val_adapt_rmse=1.00274 adapt_steps=3.15 halt=0.43 train_steps=1.82 +ep90 val_rmse=1.14935 val_adapt_rmse=1.02412 adapt_steps=3.17 halt=0.42 train_steps=1.87 +ep100 val_rmse=1.15233 val_adapt_rmse=1.03384 adapt_steps=3.10 halt=0.43 train_steps=1.84 +[ogbg-molesol_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.148049)} test={'rmse': np.float32(1.2080547)} adaptive={'rmse': np.float32(1.0046481)} steps=2.743362831858407 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view transformer --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.80556 val_adapt_rmse=1.57940 adapt_steps=5.16 halt=0.21 train_steps=3.72 +ep20 val_rmse=2.04585 val_adapt_rmse=1.53384 adapt_steps=4.59 halt=0.19 train_steps=3.46 +ep30 val_rmse=2.20692 val_adapt_rmse=1.76335 adapt_steps=2.60 halt=0.24 train_steps=3.17 +ep40 val_rmse=1.06643 val_adapt_rmse=1.01122 adapt_steps=2.19 halt=0.37 train_steps=2.20 +ep50 val_rmse=1.26673 val_adapt_rmse=1.02385 adapt_steps=2.27 halt=0.35 train_steps=2.07 +ep60 val_rmse=1.27758 val_adapt_rmse=1.04181 adapt_steps=2.62 halt=0.34 train_steps=2.26 +ep70 val_rmse=1.27827 val_adapt_rmse=1.01072 adapt_steps=2.54 halt=0.36 train_steps=2.05 +ep80 val_rmse=1.20543 val_adapt_rmse=1.03738 adapt_steps=2.62 halt=0.41 train_steps=1.93 +ep90 val_rmse=1.26838 val_adapt_rmse=1.02284 adapt_steps=2.44 halt=0.44 train_steps=1.75 +ep100 val_rmse=1.23701 val_adapt_rmse=1.02901 adapt_steps=2.45 halt=0.44 train_steps=1.76 +[ogbg-molesol_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rmse': np.float32(1.0664288)} test={'rmse': np.float32(0.95339394)} adaptive={'rmse': np.float32(0.8505217)} steps=2.2831858407079646 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view pna --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep10 val_rmse=2.43831 val_adapt_rmse=2.32531 adapt_steps=5.19 halt=0.16 train_steps=4.00 +ep20 val_rmse=2.56767 val_adapt_rmse=1.59439 adapt_steps=3.97 halt=0.17 train_steps=3.98 +ep30 val_rmse=1.46321 val_adapt_rmse=1.22048 adapt_steps=3.73 halt=0.24 train_steps=3.12 +ep40 val_rmse=1.91382 val_adapt_rmse=1.86215 adapt_steps=3.05 halt=0.22 train_steps=3.11 +ep50 val_rmse=1.55782 val_adapt_rmse=1.32158 adapt_steps=2.92 halt=0.32 train_steps=2.34 +ep60 val_rmse=1.68320 val_adapt_rmse=1.18630 adapt_steps=2.27 halt=0.35 train_steps=2.29 +ep70 val_rmse=1.38794 val_adapt_rmse=1.15712 adapt_steps=2.46 halt=0.33 train_steps=2.29 +ep80 val_rmse=1.28100 val_adapt_rmse=1.02706 adapt_steps=2.46 halt=0.35 train_steps=2.23 +ep90 val_rmse=1.47195 val_adapt_rmse=1.10808 adapt_steps=2.43 halt=0.35 train_steps=2.19 +ep100 val_rmse=1.45332 val_adapt_rmse=1.10590 adapt_steps=2.44 halt=0.35 train_steps=2.21 +[ogbg-molesol_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.2809987)} test={'rmse': np.float32(1.4175682)} adaptive={'rmse': np.float32(0.98294556)} steps=2.601769911504425 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view gen --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.68554 val_adapt_rmse=1.40872 adapt_steps=4.66 halt=0.17 train_steps=4.16 +ep20 val_rmse=1.78903 val_adapt_rmse=1.34417 adapt_steps=3.88 halt=0.27 train_steps=2.88 +ep30 val_rmse=1.43062 val_adapt_rmse=1.26301 adapt_steps=2.82 halt=0.29 train_steps=2.68 +ep40 val_rmse=1.26387 val_adapt_rmse=1.08550 adapt_steps=2.36 halt=0.32 train_steps=2.40 +ep50 val_rmse=1.43121 val_adapt_rmse=1.00136 adapt_steps=2.40 halt=0.32 train_steps=2.47 +ep60 val_rmse=1.16224 val_adapt_rmse=1.00159 adapt_steps=2.69 halt=0.32 train_steps=2.49 +ep70 val_rmse=1.36256 val_adapt_rmse=1.13936 adapt_steps=2.18 halt=0.39 train_steps=2.13 +ep80 val_rmse=1.19902 val_adapt_rmse=0.99500 adapt_steps=2.50 halt=0.39 train_steps=1.97 +ep90 val_rmse=1.19996 val_adapt_rmse=1.00030 adapt_steps=2.23 halt=0.41 train_steps=1.93 +ep100 val_rmse=1.16268 val_adapt_rmse=0.98398 adapt_steps=2.26 halt=0.40 train_steps=2.02 +[ogbg-molesol_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rmse': np.float32(1.1622369)} test={'rmse': np.float32(1.4459299)} adaptive={'rmse': np.float32(1.0918992)} steps=2.6106194690265485 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view film --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.15953 val_adapt_rmse=1.69788 adapt_steps=5.27 halt=0.13 train_steps=4.40 +ep20 val_rmse=1.76413 val_adapt_rmse=1.78195 adapt_steps=5.78 halt=0.17 train_steps=4.04 +ep30 val_rmse=1.71072 val_adapt_rmse=1.54898 adapt_steps=4.97 halt=0.15 train_steps=3.94 +ep40 val_rmse=1.73032 val_adapt_rmse=1.23604 adapt_steps=4.69 halt=0.19 train_steps=3.30 +ep50 val_rmse=1.80233 val_adapt_rmse=1.54453 adapt_steps=4.03 halt=0.23 train_steps=3.17 +ep60 val_rmse=2.03690 val_adapt_rmse=1.28646 adapt_steps=3.64 halt=0.22 train_steps=3.11 +ep70 val_rmse=1.81923 val_adapt_rmse=1.44603 adapt_steps=4.35 halt=0.20 train_steps=3.30 +ep80 val_rmse=1.36738 val_adapt_rmse=1.27507 adapt_steps=4.00 halt=0.28 train_steps=2.75 +ep90 val_rmse=1.47914 val_adapt_rmse=1.26687 adapt_steps=3.88 halt=0.27 train_steps=2.67 +ep100 val_rmse=1.56815 val_adapt_rmse=1.29753 adapt_steps=3.90 halt=0.28 train_steps=2.80 +[ogbg-molesol_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.3673769)} test={'rmse': np.float32(1.364793)} adaptive={'rmse': np.float32(1.12864)} steps=3.6106194690265485 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view resgated --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.01199 val_adapt_rmse=1.99778 adapt_steps=6.58 halt=0.17 train_steps=4.21 +ep20 val_rmse=2.81354 val_adapt_rmse=1.57554 adapt_steps=3.77 halt=0.24 train_steps=3.39 +ep30 val_rmse=2.27715 val_adapt_rmse=1.78467 adapt_steps=2.41 halt=0.31 train_steps=2.96 +ep40 val_rmse=2.06149 val_adapt_rmse=1.59902 adapt_steps=4.17 halt=0.25 train_steps=2.81 +ep50 val_rmse=1.25669 val_adapt_rmse=1.02207 adapt_steps=3.41 halt=0.33 train_steps=2.60 +ep60 val_rmse=1.24545 val_adapt_rmse=1.02109 adapt_steps=3.96 halt=0.38 train_steps=2.21 +ep70 val_rmse=1.11263 val_adapt_rmse=0.97278 adapt_steps=2.63 halt=0.47 train_steps=1.62 +ep80 val_rmse=1.21134 val_adapt_rmse=1.06008 adapt_steps=3.45 halt=0.41 train_steps=1.89 +ep90 val_rmse=1.09389 val_adapt_rmse=0.97993 adapt_steps=3.27 halt=0.41 train_steps=1.90 +ep100 val_rmse=1.14293 val_adapt_rmse=1.00867 adapt_steps=3.06 halt=0.44 train_steps=1.83 +[ogbg-molesol_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(1.0938909)} test={'rmse': np.float32(1.0833443)} adaptive={'rmse': np.float32(0.9181242)} steps=3.230088495575221 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view tag --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=3.47158 val_adapt_rmse=2.85814 adapt_steps=6.48 halt=0.15 train_steps=4.28 +ep20 val_rmse=2.59229 val_adapt_rmse=2.29301 adapt_steps=4.50 halt=0.19 train_steps=3.54 +ep30 val_rmse=1.38104 val_adapt_rmse=1.23529 adapt_steps=3.79 halt=0.17 train_steps=4.02 +ep40 val_rmse=1.62549 val_adapt_rmse=1.31054 adapt_steps=3.39 halt=0.24 train_steps=3.04 +ep50 val_rmse=1.17882 val_adapt_rmse=1.00373 adapt_steps=3.59 halt=0.26 train_steps=2.89 +ep60 val_rmse=1.11478 val_adapt_rmse=1.01010 adapt_steps=2.65 halt=0.36 train_steps=2.17 +ep70 val_rmse=1.21310 val_adapt_rmse=1.04888 adapt_steps=2.49 halt=0.35 train_steps=2.14 +ep80 val_rmse=1.13492 val_adapt_rmse=1.00575 adapt_steps=2.39 halt=0.40 train_steps=1.92 +ep90 val_rmse=1.10848 val_adapt_rmse=0.98178 adapt_steps=2.41 halt=0.39 train_steps=1.99 +ep100 val_rmse=1.08712 val_adapt_rmse=0.96400 adapt_steps=2.39 halt=0.44 train_steps=1.82 +[ogbg-molesol_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rmse': np.float32(1.087122)} test={'rmse': np.float32(1.2508167)} adaptive={'rmse': np.float32(1.0189501)} steps=2.353982300884956 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view sgc --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.13452 val_adapt_rmse=1.54890 adapt_steps=4.80 halt=0.18 train_steps=4.20 +ep20 val_rmse=1.80887 val_adapt_rmse=1.55135 adapt_steps=4.19 halt=0.20 train_steps=3.79 +ep30 val_rmse=1.56727 val_adapt_rmse=1.38135 adapt_steps=3.77 halt=0.28 train_steps=3.18 +ep40 val_rmse=1.44096 val_adapt_rmse=1.19056 adapt_steps=5.21 halt=0.21 train_steps=3.29 +ep50 val_rmse=1.27696 val_adapt_rmse=1.20518 adapt_steps=2.98 halt=0.28 train_steps=2.83 +ep60 val_rmse=1.03453 val_adapt_rmse=1.03118 adapt_steps=3.41 halt=0.29 train_steps=2.72 +ep70 val_rmse=1.36152 val_adapt_rmse=1.19328 adapt_steps=2.70 halt=0.37 train_steps=2.20 +ep80 val_rmse=1.10044 val_adapt_rmse=1.00095 adapt_steps=2.53 halt=0.41 train_steps=1.89 +ep90 val_rmse=1.09772 val_adapt_rmse=1.00221 adapt_steps=2.59 halt=0.43 train_steps=1.80 +ep100 val_rmse=1.08154 val_adapt_rmse=1.01459 adapt_steps=2.57 halt=0.42 train_steps=1.90 +[ogbg-molesol_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rmse': np.float32(1.0345254)} test={'rmse': np.float32(1.0465622)} adaptive={'rmse': np.float32(0.97806746)} steps=3.2831858407079646 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view cheb --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.61304 val_adapt_rmse=1.41832 adapt_steps=3.95 halt=0.23 train_steps=3.80 +ep20 val_rmse=2.75789 val_adapt_rmse=2.14843 adapt_steps=3.42 halt=0.25 train_steps=3.13 +ep30 val_rmse=1.83964 val_adapt_rmse=1.52535 adapt_steps=3.04 halt=0.22 train_steps=3.33 +ep40 val_rmse=1.78527 val_adapt_rmse=1.47363 adapt_steps=2.77 halt=0.34 train_steps=2.29 +ep50 val_rmse=1.79619 val_adapt_rmse=1.39923 adapt_steps=2.56 halt=0.46 train_steps=1.75 +ep60 val_rmse=1.55892 val_adapt_rmse=1.29826 adapt_steps=2.79 halt=0.40 train_steps=2.14 +ep70 val_rmse=1.21742 val_adapt_rmse=1.01859 adapt_steps=2.35 halt=0.43 train_steps=1.82 +ep80 val_rmse=1.06434 val_adapt_rmse=0.91884 adapt_steps=2.42 halt=0.44 train_steps=1.73 +ep90 val_rmse=1.08489 val_adapt_rmse=0.95548 adapt_steps=2.42 halt=0.46 train_steps=1.66 +ep100 val_rmse=1.08888 val_adapt_rmse=0.95485 adapt_steps=2.50 halt=0.46 train_steps=1.74 +[ogbg-molesol_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(1.0643402)} test={'rmse': np.float32(1.034204)} adaptive={'rmse': np.float32(0.8497807)} steps=2.601769911504425 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view arma --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=4.56663 val_adapt_rmse=3.60617 adapt_steps=2.74 halt=0.19 train_steps=3.89 +ep20 val_rmse=1.79390 val_adapt_rmse=1.59002 adapt_steps=3.36 halt=0.18 train_steps=3.97 +ep30 val_rmse=2.24326 val_adapt_rmse=1.60470 adapt_steps=3.49 halt=0.18 train_steps=3.64 +ep40 val_rmse=1.96715 val_adapt_rmse=1.62786 adapt_steps=2.96 halt=0.23 train_steps=3.09 +ep50 val_rmse=1.30996 val_adapt_rmse=1.07779 adapt_steps=2.49 halt=0.31 train_steps=2.61 +ep60 val_rmse=1.59369 val_adapt_rmse=1.15346 adapt_steps=2.60 halt=0.31 train_steps=2.58 +ep70 val_rmse=1.33600 val_adapt_rmse=1.06852 adapt_steps=2.23 halt=0.39 train_steps=2.12 +ep80 val_rmse=1.51381 val_adapt_rmse=1.08174 adapt_steps=2.51 halt=0.36 train_steps=2.25 +ep90 val_rmse=1.57786 val_adapt_rmse=1.05584 adapt_steps=2.32 halt=0.37 train_steps=2.15 +ep100 val_rmse=1.51730 val_adapt_rmse=1.01467 adapt_steps=2.27 halt=0.39 train_steps=2.00 +[ogbg-molesol_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rmse': np.float32(1.3099641)} test={'rmse': np.float32(1.5309947)} adaptive={'rmse': np.float32(1.0385827)} steps=2.575221238938053 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view mf --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=3.91043 val_adapt_rmse=3.93609 adapt_steps=7.12 halt=0.15 train_steps=4.32 +ep20 val_rmse=1.56765 val_adapt_rmse=1.40924 adapt_steps=3.93 halt=0.21 train_steps=3.97 +ep30 val_rmse=2.21943 val_adapt_rmse=1.92857 adapt_steps=4.80 halt=0.21 train_steps=3.70 +ep40 val_rmse=1.34838 val_adapt_rmse=1.13183 adapt_steps=2.79 halt=0.24 train_steps=2.98 +ep50 val_rmse=2.04182 val_adapt_rmse=1.18497 adapt_steps=3.55 halt=0.32 train_steps=2.48 +ep60 val_rmse=1.07650 val_adapt_rmse=1.06298 adapt_steps=3.69 halt=0.38 train_steps=2.00 +ep70 val_rmse=1.17131 val_adapt_rmse=1.05686 adapt_steps=3.22 halt=0.40 train_steps=2.01 +ep80 val_rmse=1.16899 val_adapt_rmse=1.03185 adapt_steps=4.14 halt=0.37 train_steps=2.18 +ep90 val_rmse=1.09374 val_adapt_rmse=1.03779 adapt_steps=3.41 halt=0.41 train_steps=1.92 +ep100 val_rmse=1.13886 val_adapt_rmse=1.05515 adapt_steps=3.32 halt=0.42 train_steps=1.92 +[ogbg-molesol_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rmse': np.float32(1.0765038)} test={'rmse': np.float32(1.0843762)} adaptive={'rmse': np.float32(0.95887977)} steps=3.4070796460176993 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molesol view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molesol --view appnp --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=5.21048 val_adapt_rmse=2.38789 adapt_steps=5.34 halt=0.15 train_steps=4.20 +ep20 val_rmse=2.82679 val_adapt_rmse=2.25175 adapt_steps=6.12 halt=0.18 train_steps=3.93 +ep30 val_rmse=1.68909 val_adapt_rmse=1.41500 adapt_steps=4.84 halt=0.19 train_steps=3.72 +ep40 val_rmse=2.08134 val_adapt_rmse=1.83294 adapt_steps=4.53 halt=0.20 train_steps=3.51 +ep50 val_rmse=1.95089 val_adapt_rmse=1.48969 adapt_steps=3.67 halt=0.26 train_steps=2.94 +ep60 val_rmse=1.80235 val_adapt_rmse=1.37428 adapt_steps=3.46 halt=0.33 train_steps=2.30 +ep70 val_rmse=1.62703 val_adapt_rmse=1.25301 adapt_steps=2.74 halt=0.42 train_steps=1.88 +ep80 val_rmse=1.70083 val_adapt_rmse=1.27133 adapt_steps=2.71 halt=0.39 train_steps=2.06 +ep90 val_rmse=1.71529 val_adapt_rmse=1.30814 adapt_steps=2.67 halt=0.40 train_steps=1.94 +ep100 val_rmse=1.69038 val_adapt_rmse=1.31634 adapt_steps=2.68 halt=0.40 train_steps=1.95 +[ogbg-molesol_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rmse': np.float32(1.6270279)} test={'rmse': np.float32(1.2973164)} adaptive={'rmse': np.float32(1.0733075)} steps=2.814159292035398 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molesol_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json diff --git a/logs/ogbg-molhiv_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-molhiv_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..ff2e7a5 --- /dev/null +++ b/logs/ogbg-molhiv_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,278 @@ +[run] ogbg-molhiv view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --view gin --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.50465 val_adapt_rocauc=0.51605 adapt_steps=2.17 halt=0.44 train_steps=1.86 +ep20 val_rocauc=0.68965 val_adapt_rocauc=0.70338 adapt_steps=2.05 halt=0.43 train_steps=1.93 +ep30 val_rocauc=0.74705 val_adapt_rocauc=0.71674 adapt_steps=2.16 halt=0.44 train_steps=1.88 +ep40 val_rocauc=0.66882 val_adapt_rocauc=0.69730 adapt_steps=2.23 halt=0.44 train_steps=1.90 +ep50 val_rocauc=0.69645 val_adapt_rocauc=0.75311 adapt_steps=2.17 halt=0.44 train_steps=1.88 +ep60 val_rocauc=0.72560 val_adapt_rocauc=0.75246 adapt_steps=2.12 halt=0.44 train_steps=1.87 +ep70 val_rocauc=0.73678 val_adapt_rocauc=0.76610 adapt_steps=2.13 halt=0.44 train_steps=1.86 +ep80 val_rocauc=0.73638 val_adapt_rocauc=0.77730 adapt_steps=2.07 halt=0.44 train_steps=1.85 +ep90 val_rocauc=0.76228 val_adapt_rocauc=0.78163 adapt_steps=2.11 halt=0.44 train_steps=1.85 +ep100 val_rocauc=0.75586 val_adapt_rocauc=0.78034 adapt_steps=2.10 halt=0.44 train_steps=1.85 +[ogbg-molhiv_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.7622844405251813} test={'rocauc': 0.728463276617934} adaptive={'rocauc': 0.7414685490256668} steps=2.1835643082907854 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.69659 val_adapt_rocauc=0.67019 adapt_steps=2.27 halt=0.43 train_steps=1.91 +ep20 val_rocauc=0.71128 val_adapt_rocauc=0.74182 adapt_steps=2.25 halt=0.44 train_steps=1.90 +ep30 val_rocauc=0.71784 val_adapt_rocauc=0.71432 adapt_steps=2.09 halt=0.43 train_steps=1.92 +ep40 val_rocauc=0.57809 val_adapt_rocauc=0.61863 adapt_steps=2.07 halt=0.43 train_steps=1.95 +ep50 val_rocauc=0.71898 val_adapt_rocauc=0.72970 adapt_steps=2.15 halt=0.44 train_steps=1.90 +ep60 val_rocauc=0.74272 val_adapt_rocauc=0.75436 adapt_steps=2.17 halt=0.44 train_steps=1.91 +ep70 val_rocauc=0.64453 val_adapt_rocauc=0.67305 adapt_steps=2.09 halt=0.43 train_steps=1.92 +ep80 val_rocauc=0.66148 val_adapt_rocauc=0.71639 adapt_steps=2.11 halt=0.44 train_steps=1.89 +ep90 val_rocauc=0.68795 val_adapt_rocauc=0.73859 adapt_steps=2.10 halt=0.44 train_steps=1.89 +ep100 val_rocauc=0.69479 val_adapt_rocauc=0.73030 adapt_steps=2.10 halt=0.44 train_steps=1.88 +[ogbg-molhiv_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.7427218058005095} test={'rocauc': 0.7216728789663763} adaptive={'rocauc': 0.7219567778442999} steps=2.1913445173839046 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.65285 val_adapt_rocauc=0.67983 adapt_steps=2.17 halt=0.43 train_steps=1.95 +ep20 val_rocauc=0.63964 val_adapt_rocauc=0.67770 adapt_steps=2.12 halt=0.43 train_steps=1.91 +ep30 val_rocauc=0.70439 val_adapt_rocauc=0.72607 adapt_steps=2.28 halt=0.43 train_steps=1.93 +ep40 val_rocauc=0.67857 val_adapt_rocauc=0.67646 adapt_steps=2.09 halt=0.44 train_steps=1.90 +ep50 val_rocauc=0.66299 val_adapt_rocauc=0.70493 adapt_steps=2.10 halt=0.44 train_steps=1.89 +ep60 val_rocauc=0.72309 val_adapt_rocauc=0.75250 adapt_steps=2.10 halt=0.43 train_steps=1.91 +ep70 val_rocauc=0.69147 val_adapt_rocauc=0.71552 adapt_steps=2.06 halt=0.44 train_steps=1.88 +ep80 val_rocauc=0.75410 val_adapt_rocauc=0.76395 adapt_steps=2.12 halt=0.44 train_steps=1.88 +ep90 val_rocauc=0.76238 val_adapt_rocauc=0.75313 adapt_steps=2.09 halt=0.44 train_steps=1.85 +ep100 val_rocauc=0.76521 val_adapt_rocauc=0.75985 adapt_steps=2.09 halt=0.44 train_steps=1.87 +[ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.76521164021164} test={'rocauc': 0.7279630738330211} adaptive={'rocauc': 0.7195040460418316} steps=2.1412594213469487 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.60161 val_adapt_rocauc=0.64669 adapt_steps=2.08 halt=0.43 train_steps=1.92 +ep20 val_rocauc=0.71865 val_adapt_rocauc=0.72325 adapt_steps=2.51 halt=0.43 train_steps=1.95 +ep30 val_rocauc=0.72758 val_adapt_rocauc=0.72496 adapt_steps=2.13 halt=0.43 train_steps=1.95 +ep40 val_rocauc=0.75529 val_adapt_rocauc=0.73154 adapt_steps=2.08 halt=0.43 train_steps=1.93 +ep50 val_rocauc=0.74199 val_adapt_rocauc=0.74141 adapt_steps=2.12 halt=0.43 train_steps=1.96 +ep60 val_rocauc=0.70099 val_adapt_rocauc=0.73010 adapt_steps=2.10 halt=0.43 train_steps=1.95 +ep70 val_rocauc=0.76185 val_adapt_rocauc=0.77202 adapt_steps=2.10 halt=0.44 train_steps=1.91 +ep80 val_rocauc=0.77242 val_adapt_rocauc=0.76566 adapt_steps=2.14 halt=0.44 train_steps=1.91 +ep90 val_rocauc=0.75081 val_adapt_rocauc=0.75828 adapt_steps=2.14 halt=0.44 train_steps=1.90 +ep100 val_rocauc=0.74508 val_adapt_rocauc=0.74839 adapt_steps=2.13 halt=0.44 train_steps=1.90 +[ogbg-molhiv_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7724224720752498} test={'rocauc': 0.7540721141775624} adaptive={'rocauc': 0.7493028061569362} steps=2.225382932166302 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.63791 val_adapt_rocauc=0.65941 adapt_steps=2.16 halt=0.44 train_steps=1.86 +ep20 val_rocauc=0.65958 val_adapt_rocauc=0.68114 adapt_steps=2.14 halt=0.43 train_steps=1.98 +ep30 val_rocauc=0.70813 val_adapt_rocauc=0.71648 adapt_steps=2.10 halt=0.44 train_steps=1.91 +ep40 val_rocauc=0.71160 val_adapt_rocauc=0.71489 adapt_steps=2.12 halt=0.43 train_steps=1.92 +ep50 val_rocauc=0.74629 val_adapt_rocauc=0.72922 adapt_steps=2.12 halt=0.43 train_steps=1.93 +ep60 val_rocauc=0.77221 val_adapt_rocauc=0.77362 adapt_steps=2.10 halt=0.44 train_steps=1.91 +ep70 val_rocauc=0.73550 val_adapt_rocauc=0.75380 adapt_steps=2.22 halt=0.43 train_steps=1.96 +ep80 val_rocauc=0.75176 val_adapt_rocauc=0.76963 adapt_steps=2.17 halt=0.43 train_steps=1.95 +ep90 val_rocauc=0.77064 val_adapt_rocauc=0.77482 adapt_steps=2.17 halt=0.44 train_steps=1.89 +ep100 val_rocauc=0.77092 val_adapt_rocauc=0.77462 adapt_steps=2.15 halt=0.44 train_steps=1.89 +[ogbg-molhiv_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.7722111992945326} test={'rocauc': 0.7005330346279379} adaptive={'rocauc': 0.7209988605419185} steps=2.161196207148067 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.62286 val_adapt_rocauc=0.63631 adapt_steps=2.12 halt=0.43 train_steps=1.92 +ep20 val_rocauc=0.50681 val_adapt_rocauc=0.62452 adapt_steps=2.03 halt=0.44 train_steps=1.88 +ep30 val_rocauc=0.71981 val_adapt_rocauc=0.71587 adapt_steps=2.12 halt=0.44 train_steps=1.92 +ep40 val_rocauc=0.63676 val_adapt_rocauc=0.69827 adapt_steps=2.10 halt=0.44 train_steps=1.89 +ep50 val_rocauc=0.71987 val_adapt_rocauc=0.71579 adapt_steps=2.10 halt=0.43 train_steps=1.95 +ep60 val_rocauc=0.77652 val_adapt_rocauc=0.77421 adapt_steps=2.13 halt=0.43 train_steps=1.94 +ep70 val_rocauc=0.73578 val_adapt_rocauc=0.73905 adapt_steps=2.14 halt=0.44 train_steps=1.90 +ep80 val_rocauc=0.77909 val_adapt_rocauc=0.77380 adapt_steps=2.21 halt=0.43 train_steps=1.93 +ep90 val_rocauc=0.77284 val_adapt_rocauc=0.76992 adapt_steps=2.20 halt=0.43 train_steps=1.95 +ep100 val_rocauc=0.75856 val_adapt_rocauc=0.75794 adapt_steps=2.19 halt=0.43 train_steps=1.95 +[ogbg-molhiv_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7790944052518126} test={'rocauc': 0.7510651036134339} adaptive={'rocauc': 0.7493443287819387} steps=2.2287867736445417 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.69482 val_adapt_rocauc=0.69337 adapt_steps=2.09 halt=0.43 train_steps=1.95 +ep20 val_rocauc=0.69048 val_adapt_rocauc=0.68828 adapt_steps=2.11 halt=0.43 train_steps=1.92 +ep30 val_rocauc=0.70734 val_adapt_rocauc=0.68263 adapt_steps=2.08 halt=0.43 train_steps=1.96 +ep40 val_rocauc=0.75896 val_adapt_rocauc=0.75541 adapt_steps=2.17 halt=0.43 train_steps=1.96 +ep50 val_rocauc=0.63094 val_adapt_rocauc=0.71781 adapt_steps=2.15 halt=0.43 train_steps=2.00 +ep60 val_rocauc=0.78134 val_adapt_rocauc=0.78253 adapt_steps=2.15 halt=0.43 train_steps=1.95 +ep70 val_rocauc=0.74767 val_adapt_rocauc=0.77658 adapt_steps=2.14 halt=0.43 train_steps=1.93 +ep80 val_rocauc=0.75221 val_adapt_rocauc=0.76723 adapt_steps=2.19 halt=0.43 train_steps=1.98 +ep90 val_rocauc=0.73516 val_adapt_rocauc=0.74942 adapt_steps=2.14 halt=0.43 train_steps=1.92 +ep100 val_rocauc=0.74673 val_adapt_rocauc=0.75054 adapt_steps=2.13 halt=0.44 train_steps=1.91 +[ogbg-molhiv_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.7813418577307466} test={'rocauc': 0.7294279534174086} adaptive={'rocauc': 0.7396338283860252} steps=2.215171407731583 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --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=0.65392 val_adapt_rocauc=0.65972 adapt_steps=2.26 halt=0.45 train_steps=1.76 +/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=0.70167 val_adapt_rocauc=0.73359 adapt_steps=2.14 halt=0.45 train_steps=1.83 +/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( +ep30 val_rocauc=0.57289 val_adapt_rocauc=0.60013 adapt_steps=2.02 halt=0.45 train_steps=1.83 +/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( +ep40 val_rocauc=0.74876 val_adapt_rocauc=0.72038 adapt_steps=2.03 halt=0.44 train_steps=1.89 +/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=0.69108 val_adapt_rocauc=0.72229 adapt_steps=2.11 halt=0.43 train_steps=1.92 +/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=0.69969 val_adapt_rocauc=0.70883 adapt_steps=2.12 halt=0.44 train_steps=1.89 +/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=0.72681 val_adapt_rocauc=0.77015 adapt_steps=2.16 halt=0.43 train_steps=1.93 +/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=0.74562 val_adapt_rocauc=0.77410 adapt_steps=2.13 halt=0.43 train_steps=1.92 +/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=0.71370 val_adapt_rocauc=0.78801 adapt_steps=2.16 halt=0.44 train_steps=1.90 +/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=0.71775 val_adapt_rocauc=0.78617 adapt_steps=2.14 halt=0.44 train_steps=1.89 +[ogbg-molhiv_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.7487599206349206} test={'rocauc': 0.6730373317368046} adaptive={'rocauc': 0.6877382722725429} steps=2.0588378312667155 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.58244 val_adapt_rocauc=0.62459 adapt_steps=2.17 halt=0.43 train_steps=1.95 +ep20 val_rocauc=0.65886 val_adapt_rocauc=0.66235 adapt_steps=2.06 halt=0.44 train_steps=1.89 +ep30 val_rocauc=0.69707 val_adapt_rocauc=0.69637 adapt_steps=2.06 halt=0.44 train_steps=1.92 +ep40 val_rocauc=0.73515 val_adapt_rocauc=0.77200 adapt_steps=2.17 halt=0.44 train_steps=1.91 +ep50 val_rocauc=0.72530 val_adapt_rocauc=0.75137 adapt_steps=2.12 halt=0.43 train_steps=1.97 +ep60 val_rocauc=0.69888 val_adapt_rocauc=0.73379 adapt_steps=2.09 halt=0.43 train_steps=1.98 +ep70 val_rocauc=0.71051 val_adapt_rocauc=0.74897 adapt_steps=2.12 halt=0.43 train_steps=1.94 +ep80 val_rocauc=0.76901 val_adapt_rocauc=0.77657 adapt_steps=2.10 halt=0.43 train_steps=1.93 +ep90 val_rocauc=0.73056 val_adapt_rocauc=0.76530 adapt_steps=2.11 halt=0.44 train_steps=1.92 +ep100 val_rocauc=0.73376 val_adapt_rocauc=0.75580 adapt_steps=2.13 halt=0.43 train_steps=1.93 +[ogbg-molhiv_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.769011488340192} test={'rocauc': 0.7434075590490352} adaptive={'rocauc': 0.7426736707931786} steps=2.178215414539266 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.60803 val_adapt_rocauc=0.69045 adapt_steps=2.06 halt=0.47 train_steps=1.67 +ep20 val_rocauc=0.64308 val_adapt_rocauc=0.78621 adapt_steps=2.01 halt=0.45 train_steps=1.79 +ep30 val_rocauc=0.74069 val_adapt_rocauc=0.75513 adapt_steps=2.21 halt=0.45 train_steps=1.83 +ep40 val_rocauc=0.75046 val_adapt_rocauc=0.78035 adapt_steps=2.23 halt=0.43 train_steps=1.93 +ep50 val_rocauc=0.71486 val_adapt_rocauc=0.75589 adapt_steps=2.34 halt=0.43 train_steps=2.01 +ep60 val_rocauc=0.77074 val_adapt_rocauc=0.80191 adapt_steps=2.10 halt=0.43 train_steps=1.99 +ep70 val_rocauc=0.78228 val_adapt_rocauc=0.80466 adapt_steps=2.21 halt=0.43 train_steps=1.97 +ep80 val_rocauc=0.81468 val_adapt_rocauc=0.81506 adapt_steps=2.13 halt=0.43 train_steps=1.96 +ep90 val_rocauc=0.81502 val_adapt_rocauc=0.81015 adapt_steps=2.14 halt=0.43 train_steps=1.95 +ep100 val_rocauc=0.81203 val_adapt_rocauc=0.80753 adapt_steps=2.11 halt=0.43 train_steps=1.95 +[ogbg-molhiv_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.8150199637468156} test={'rocauc': 0.7415303501419496} adaptive={'rocauc': 0.7291546766063463} steps=2.2144420131291027 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.57563 val_adapt_rocauc=0.57248 adapt_steps=2.08 halt=0.43 train_steps=1.96 +ep20 val_rocauc=0.68901 val_adapt_rocauc=0.69659 adapt_steps=2.07 halt=0.43 train_steps=1.97 +ep30 val_rocauc=0.72785 val_adapt_rocauc=0.73945 adapt_steps=2.17 halt=0.43 train_steps=1.95 +ep40 val_rocauc=0.80307 val_adapt_rocauc=0.79528 adapt_steps=2.10 halt=0.43 train_steps=1.93 +ep50 val_rocauc=0.74046 val_adapt_rocauc=0.74882 adapt_steps=2.15 halt=0.43 train_steps=1.96 +ep60 val_rocauc=0.76188 val_adapt_rocauc=0.76877 adapt_steps=2.13 halt=0.43 train_steps=1.95 +ep70 val_rocauc=0.74584 val_adapt_rocauc=0.74880 adapt_steps=2.14 halt=0.43 train_steps=1.99 +ep80 val_rocauc=0.72576 val_adapt_rocauc=0.72937 adapt_steps=2.09 halt=0.43 train_steps=1.95 +ep90 val_rocauc=0.72962 val_adapt_rocauc=0.72854 adapt_steps=2.17 halt=0.43 train_steps=1.98 +ep100 val_rocauc=0.73262 val_adapt_rocauc=0.73243 adapt_steps=2.13 halt=0.43 train_steps=1.97 +[ogbg-molhiv_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.8030723349010386} test={'rocauc': 0.7502983835145524} adaptive={'rocauc': 0.7566658297765504} steps=2.2205203014831025 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.55912 val_adapt_rocauc=0.62342 adapt_steps=2.04 halt=0.43 train_steps=1.90 +ep20 val_rocauc=0.68402 val_adapt_rocauc=0.67609 adapt_steps=2.15 halt=0.44 train_steps=1.84 +ep30 val_rocauc=0.70234 val_adapt_rocauc=0.71080 adapt_steps=2.18 halt=0.44 train_steps=1.90 +ep40 val_rocauc=0.71746 val_adapt_rocauc=0.70275 adapt_steps=2.42 halt=0.44 train_steps=1.86 +ep50 val_rocauc=0.74377 val_adapt_rocauc=0.74631 adapt_steps=2.14 halt=0.44 train_steps=1.90 +ep60 val_rocauc=0.68302 val_adapt_rocauc=0.74882 adapt_steps=2.18 halt=0.44 train_steps=1.91 +ep70 val_rocauc=0.70337 val_adapt_rocauc=0.73207 adapt_steps=2.09 halt=0.44 train_steps=1.90 +ep80 val_rocauc=0.75679 val_adapt_rocauc=0.76447 adapt_steps=2.14 halt=0.44 train_steps=1.90 +ep90 val_rocauc=0.74719 val_adapt_rocauc=0.76515 adapt_steps=2.12 halt=0.44 train_steps=1.88 +ep100 val_rocauc=0.74130 val_adapt_rocauc=0.75597 adapt_steps=2.12 halt=0.44 train_steps=1.89 +[ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7567852243778168} test={'rocauc': 0.7480619556190734} adaptive={'rocauc': 0.7477104617702157} steps=2.225869195234622 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.62000 val_adapt_rocauc=0.63880 adapt_steps=2.22 halt=0.44 train_steps=1.89 +ep20 val_rocauc=0.59820 val_adapt_rocauc=0.61098 adapt_steps=2.16 halt=0.44 train_steps=1.89 +ep30 val_rocauc=0.67764 val_adapt_rocauc=0.68890 adapt_steps=2.08 halt=0.44 train_steps=1.86 +ep40 val_rocauc=0.66809 val_adapt_rocauc=0.66128 adapt_steps=2.09 halt=0.44 train_steps=1.89 +ep50 val_rocauc=0.73528 val_adapt_rocauc=0.71478 adapt_steps=2.09 halt=0.44 train_steps=1.91 +ep60 val_rocauc=0.69053 val_adapt_rocauc=0.68013 adapt_steps=2.16 halt=0.44 train_steps=1.89 +ep70 val_rocauc=0.68528 val_adapt_rocauc=0.72841 adapt_steps=2.10 halt=0.44 train_steps=1.89 +ep80 val_rocauc=0.68138 val_adapt_rocauc=0.69448 adapt_steps=2.11 halt=0.44 train_steps=1.88 +ep90 val_rocauc=0.68754 val_adapt_rocauc=0.69915 adapt_steps=2.12 halt=0.43 train_steps=1.93 +ep100 val_rocauc=0.69254 val_adapt_rocauc=0.70377 adapt_steps=2.12 halt=0.44 train_steps=1.88 +[ogbg-molhiv_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.7352782676856752} test={'rocauc': 0.6961702620753587} adaptive={'rocauc': 0.7016995306977732} steps=2.0795040116703136 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.63285 val_adapt_rocauc=0.63797 adapt_steps=2.09 halt=0.43 train_steps=1.94 +ep20 val_rocauc=0.59546 val_adapt_rocauc=0.62621 adapt_steps=2.09 halt=0.43 train_steps=1.94 +ep30 val_rocauc=0.64157 val_adapt_rocauc=0.64537 adapt_steps=2.07 halt=0.43 train_steps=1.95 +ep40 val_rocauc=0.78253 val_adapt_rocauc=0.79697 adapt_steps=2.21 halt=0.43 train_steps=1.94 +ep50 val_rocauc=0.78099 val_adapt_rocauc=0.78545 adapt_steps=2.23 halt=0.42 train_steps=2.02 +ep60 val_rocauc=0.75496 val_adapt_rocauc=0.75580 adapt_steps=2.16 halt=0.43 train_steps=1.92 +ep70 val_rocauc=0.76923 val_adapt_rocauc=0.76459 adapt_steps=2.17 halt=0.43 train_steps=1.94 +ep80 val_rocauc=0.75888 val_adapt_rocauc=0.75674 adapt_steps=2.10 halt=0.45 train_steps=1.83 +ep90 val_rocauc=0.73937 val_adapt_rocauc=0.73410 adapt_steps=2.10 halt=0.45 train_steps=1.77 +ep100 val_rocauc=0.71941 val_adapt_rocauc=0.71715 adapt_steps=2.07 halt=0.46 train_steps=1.74 +[ogbg-molhiv_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.7825329463060945} test={'rocauc': 0.7205932907163135} adaptive={'rocauc': 0.7218775951640628} steps=2.2939460247994163 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.58405 val_adapt_rocauc=0.62652 adapt_steps=2.13 halt=0.44 train_steps=1.87 +ep20 val_rocauc=0.63653 val_adapt_rocauc=0.65469 adapt_steps=2.04 halt=0.44 train_steps=1.83 +ep30 val_rocauc=0.68206 val_adapt_rocauc=0.66472 adapt_steps=2.09 halt=0.44 train_steps=1.85 +ep40 val_rocauc=0.73261 val_adapt_rocauc=0.71919 adapt_steps=2.08 halt=0.44 train_steps=1.82 +ep50 val_rocauc=0.76797 val_adapt_rocauc=0.79653 adapt_steps=2.13 halt=0.44 train_steps=1.86 +ep60 val_rocauc=0.74831 val_adapt_rocauc=0.72643 adapt_steps=2.04 halt=0.45 train_steps=1.77 +ep70 val_rocauc=0.73358 val_adapt_rocauc=0.77502 adapt_steps=2.03 halt=0.46 train_steps=1.73 +ep80 val_rocauc=0.77783 val_adapt_rocauc=0.77223 adapt_steps=2.06 halt=0.45 train_steps=1.75 +ep90 val_rocauc=0.78442 val_adapt_rocauc=0.76721 adapt_steps=2.05 halt=0.46 train_steps=1.71 +ep100 val_rocauc=0.78612 val_adapt_rocauc=0.76507 adapt_steps=2.06 halt=0.46 train_steps=1.73 +[ogbg-molhiv_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.7861153978052127} test={'rocauc': 0.7306939106587612} adaptive={'rocauc': 0.7378782904266208} steps=2.085825431558473 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molhiv view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molhiv --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:0 --num_workers 0 +ep10 val_rocauc=0.65109 val_adapt_rocauc=0.65071 adapt_steps=2.09 halt=0.43 train_steps=1.91 +ep20 val_rocauc=0.66377 val_adapt_rocauc=0.70133 adapt_steps=2.15 halt=0.43 train_steps=1.92 +ep30 val_rocauc=0.69912 val_adapt_rocauc=0.72873 adapt_steps=2.15 halt=0.43 train_steps=1.91 +ep40 val_rocauc=0.75265 val_adapt_rocauc=0.77675 adapt_steps=2.15 halt=0.43 train_steps=1.95 +ep50 val_rocauc=0.71979 val_adapt_rocauc=0.76668 adapt_steps=2.10 halt=0.45 train_steps=1.82 +ep60 val_rocauc=0.78688 val_adapt_rocauc=0.78537 adapt_steps=2.27 halt=0.44 train_steps=1.89 +ep70 val_rocauc=0.80465 val_adapt_rocauc=0.78273 adapt_steps=2.15 halt=0.43 train_steps=1.93 +ep80 val_rocauc=0.77804 val_adapt_rocauc=0.78100 adapt_steps=2.15 halt=0.43 train_steps=1.94 +ep90 val_rocauc=0.76305 val_adapt_rocauc=0.77873 adapt_steps=2.18 halt=0.44 train_steps=1.91 +ep100 val_rocauc=0.76926 val_adapt_rocauc=0.78354 adapt_steps=2.14 halt=0.44 train_steps=1.90 +[ogbg-molhiv_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.8046522878698804} test={'rocauc': 0.7416423646652118} adaptive={'rocauc': 0.7333127329612392} steps=2.1964502796012644 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.62676 val_adapt_rocauc=0.67960 adapt_steps=2.09 halt=0.44 train_steps=1.87 +ep20 val_rocauc=0.65528 val_adapt_rocauc=0.72533 adapt_steps=2.03 halt=0.44 train_steps=1.88 +ep30 val_rocauc=0.72398 val_adapt_rocauc=0.73609 adapt_steps=2.22 halt=0.43 train_steps=1.92 +ep40 val_rocauc=0.67653 val_adapt_rocauc=0.71372 adapt_steps=2.12 halt=0.44 train_steps=1.88 +ep50 val_rocauc=0.72748 val_adapt_rocauc=0.72608 adapt_steps=2.14 halt=0.44 train_steps=1.90 +ep60 val_rocauc=0.69598 val_adapt_rocauc=0.70466 adapt_steps=2.12 halt=0.44 train_steps=1.87 +ep70 val_rocauc=0.73788 val_adapt_rocauc=0.71230 adapt_steps=2.10 halt=0.44 train_steps=1.88 +ep80 val_rocauc=0.72564 val_adapt_rocauc=0.74313 adapt_steps=2.06 halt=0.45 train_steps=1.82 +ep90 val_rocauc=0.73463 val_adapt_rocauc=0.75132 adapt_steps=2.07 halt=0.45 train_steps=1.78 +ep100 val_rocauc=0.72183 val_adapt_rocauc=0.73975 adapt_steps=2.05 halt=0.45 train_steps=1.76 +[ogbg-molhiv_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.7378778414658045} test={'rocauc': 0.6883099325981575} adaptive={'rocauc': 0.7290619749319223} steps=2.102358375881352 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molhiv_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json diff --git a/logs/ogbg-mollipo_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-mollipo_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..d6e2617 --- /dev/null +++ b/logs/ogbg-mollipo_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,242 @@ +[run] ogbg-mollipo view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view gin --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.27165 val_adapt_rmse=1.16086 adapt_steps=5.19 halt=0.18 train_steps=4.00 +ep20 val_rmse=1.51709 val_adapt_rmse=1.16539 adapt_steps=5.08 halt=0.19 train_steps=3.67 +ep30 val_rmse=3.96000 val_adapt_rmse=2.88970 adapt_steps=4.23 halt=0.21 train_steps=3.41 +ep40 val_rmse=1.45958 val_adapt_rmse=1.27486 adapt_steps=6.80 halt=0.17 train_steps=3.91 +ep50 val_rmse=1.62306 val_adapt_rmse=1.21914 adapt_steps=3.90 halt=0.21 train_steps=3.43 +ep60 val_rmse=0.96105 val_adapt_rmse=0.88005 adapt_steps=3.28 halt=0.29 train_steps=2.74 +ep70 val_rmse=0.93501 val_adapt_rmse=0.81324 adapt_steps=2.69 halt=0.29 train_steps=2.70 +ep80 val_rmse=0.92098 val_adapt_rmse=0.82825 adapt_steps=2.68 halt=0.33 train_steps=2.45 +ep90 val_rmse=0.91291 val_adapt_rmse=0.76874 adapt_steps=2.81 halt=0.36 train_steps=2.21 +ep100 val_rmse=0.88727 val_adapt_rmse=0.77048 adapt_steps=2.72 halt=0.36 train_steps=2.25 +[ogbg-mollipo_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rmse': np.float32(0.88727427)} test={'rmse': np.float32(1.0246027)} adaptive={'rmse': np.float32(0.86185706)} steps=2.5404761904761903 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view gine --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.40935 val_adapt_rmse=1.37490 adapt_steps=6.02 halt=0.16 train_steps=3.96 +ep20 val_rmse=1.87982 val_adapt_rmse=1.47829 adapt_steps=5.06 halt=0.19 train_steps=3.73 +ep30 val_rmse=1.00892 val_adapt_rmse=0.95657 adapt_steps=4.83 halt=0.24 train_steps=3.32 +ep40 val_rmse=1.92570 val_adapt_rmse=1.26685 adapt_steps=4.02 halt=0.23 train_steps=3.29 +ep50 val_rmse=0.89318 val_adapt_rmse=0.84550 adapt_steps=4.34 halt=0.21 train_steps=3.32 +ep60 val_rmse=0.95712 val_adapt_rmse=0.82385 adapt_steps=3.63 halt=0.29 train_steps=2.75 +ep70 val_rmse=0.99810 val_adapt_rmse=0.83945 adapt_steps=3.09 halt=0.30 train_steps=2.58 +ep80 val_rmse=0.93375 val_adapt_rmse=0.78058 adapt_steps=2.90 halt=0.34 train_steps=2.41 +ep90 val_rmse=0.87733 val_adapt_rmse=0.75005 adapt_steps=2.50 halt=0.36 train_steps=2.25 +ep100 val_rmse=0.89479 val_adapt_rmse=0.75851 adapt_steps=2.63 halt=0.37 train_steps=2.22 +[ogbg-mollipo_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(0.87732804)} test={'rmse': np.float32(0.9709947)} adaptive={'rmse': np.float32(0.82210046)} steps=2.395238095238095 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=gcn compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view gcn --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.21491 val_adapt_rmse=1.09189 adapt_steps=6.06 halt=0.20 train_steps=3.72 +ep20 val_rmse=0.94709 val_adapt_rmse=0.88665 adapt_steps=4.28 halt=0.20 train_steps=3.65 +ep30 val_rmse=1.53588 val_adapt_rmse=1.21575 adapt_steps=5.26 halt=0.23 train_steps=3.20 +ep40 val_rmse=1.16658 val_adapt_rmse=0.91900 adapt_steps=2.85 halt=0.29 train_steps=2.66 +ep50 val_rmse=1.44945 val_adapt_rmse=0.92876 adapt_steps=3.54 halt=0.28 train_steps=2.66 +ep60 val_rmse=1.13499 val_adapt_rmse=0.82488 adapt_steps=2.63 halt=0.38 train_steps=2.07 +ep70 val_rmse=0.91036 val_adapt_rmse=0.73458 adapt_steps=2.57 halt=0.41 train_steps=1.95 +ep80 val_rmse=1.03989 val_adapt_rmse=0.75262 adapt_steps=2.41 halt=0.42 train_steps=1.81 +ep90 val_rmse=0.94022 val_adapt_rmse=0.73763 adapt_steps=2.20 halt=0.44 train_steps=1.74 +ep100 val_rmse=0.93598 val_adapt_rmse=0.74143 adapt_steps=2.24 halt=0.44 train_steps=1.75 +[ogbg-mollipo_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rmse': np.float32(0.91035604)} test={'rmse': np.float32(0.9299253)} adaptive={'rmse': np.float32(0.80096245)} steps=2.4785714285714286 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view graphsage --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.07418 val_adapt_rmse=0.96580 adapt_steps=5.63 halt=0.17 train_steps=4.01 +ep20 val_rmse=1.90831 val_adapt_rmse=1.30970 adapt_steps=4.28 halt=0.20 train_steps=3.73 +ep30 val_rmse=1.69953 val_adapt_rmse=1.09305 adapt_steps=3.80 halt=0.28 train_steps=2.82 +ep40 val_rmse=1.27229 val_adapt_rmse=0.92711 adapt_steps=3.40 halt=0.32 train_steps=2.51 +ep50 val_rmse=1.35372 val_adapt_rmse=0.91724 adapt_steps=2.40 halt=0.37 train_steps=2.18 +ep60 val_rmse=1.15361 val_adapt_rmse=0.77828 adapt_steps=2.54 halt=0.37 train_steps=2.12 +ep70 val_rmse=1.14055 val_adapt_rmse=0.76690 adapt_steps=2.25 halt=0.40 train_steps=1.94 +ep80 val_rmse=1.12685 val_adapt_rmse=0.76632 adapt_steps=2.16 halt=0.42 train_steps=1.82 +ep90 val_rmse=1.16042 val_adapt_rmse=0.74041 adapt_steps=2.18 halt=0.43 train_steps=1.75 +ep100 val_rmse=1.14354 val_adapt_rmse=0.74383 adapt_steps=2.17 halt=0.44 train_steps=1.72 +[ogbg-mollipo_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=10 val={'rmse': np.float32(1.0741799)} test={'rmse': np.float32(1.1165451)} adaptive={'rmse': np.float32(0.9747765)} steps=5.461904761904762 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view gatv2 --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.08473 val_adapt_rmse=1.00704 adapt_steps=4.76 halt=0.23 train_steps=3.42 +ep20 val_rmse=1.22357 val_adapt_rmse=1.10102 adapt_steps=5.70 halt=0.18 train_steps=3.84 +ep30 val_rmse=1.41681 val_adapt_rmse=1.07035 adapt_steps=3.46 halt=0.24 train_steps=3.17 +ep40 val_rmse=1.58552 val_adapt_rmse=1.03190 adapt_steps=3.37 halt=0.32 train_steps=2.55 +ep50 val_rmse=0.95944 val_adapt_rmse=0.79974 adapt_steps=4.35 halt=0.32 train_steps=2.42 +ep60 val_rmse=0.88782 val_adapt_rmse=0.74478 adapt_steps=2.66 halt=0.36 train_steps=2.22 +ep70 val_rmse=0.88373 val_adapt_rmse=0.74463 adapt_steps=2.40 halt=0.41 train_steps=1.95 +ep80 val_rmse=0.89006 val_adapt_rmse=0.73390 adapt_steps=2.38 halt=0.41 train_steps=1.89 +ep90 val_rmse=0.93277 val_adapt_rmse=0.72185 adapt_steps=2.30 halt=0.44 train_steps=1.78 +ep100 val_rmse=0.89800 val_adapt_rmse=0.71467 adapt_steps=2.27 halt=0.44 train_steps=1.75 +[ogbg-mollipo_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rmse': np.float32(0.88372606)} test={'rmse': np.float32(0.9250613)} adaptive={'rmse': np.float32(0.79357445)} steps=2.2928571428571427 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=graphconv compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view graphconv --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.53265 val_adapt_rmse=1.42937 adapt_steps=6.60 halt=0.17 train_steps=3.92 +ep20 val_rmse=1.29141 val_adapt_rmse=0.99349 adapt_steps=4.15 halt=0.19 train_steps=3.62 +ep30 val_rmse=1.13429 val_adapt_rmse=0.86465 adapt_steps=3.24 halt=0.24 train_steps=3.34 +ep40 val_rmse=1.92000 val_adapt_rmse=1.25179 adapt_steps=3.38 halt=0.31 train_steps=2.61 +ep50 val_rmse=1.34785 val_adapt_rmse=0.94338 adapt_steps=3.02 halt=0.37 train_steps=2.19 +ep60 val_rmse=1.07604 val_adapt_rmse=0.77996 adapt_steps=2.36 halt=0.39 train_steps=1.97 +ep70 val_rmse=1.03247 val_adapt_rmse=0.74302 adapt_steps=2.47 halt=0.39 train_steps=1.97 +ep80 val_rmse=1.07814 val_adapt_rmse=0.77095 adapt_steps=2.34 halt=0.43 train_steps=1.78 +ep90 val_rmse=0.98119 val_adapt_rmse=0.74076 adapt_steps=2.20 halt=0.44 train_steps=1.73 +ep100 val_rmse=0.96236 val_adapt_rmse=0.73650 adapt_steps=2.20 halt=0.44 train_steps=1.71 +[ogbg-mollipo_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rmse': np.float32(0.96235555)} test={'rmse': np.float32(0.9985843)} adaptive={'rmse': np.float32(0.76624817)} steps=2.123809523809524 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view transformer --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=2.42198 val_adapt_rmse=1.36438 adapt_steps=3.38 halt=0.21 train_steps=3.54 +ep20 val_rmse=1.25519 val_adapt_rmse=0.94352 adapt_steps=3.34 halt=0.23 train_steps=3.29 +ep30 val_rmse=0.88739 val_adapt_rmse=0.77527 adapt_steps=3.58 halt=0.29 train_steps=2.79 +ep40 val_rmse=0.94143 val_adapt_rmse=0.72441 adapt_steps=2.57 halt=0.36 train_steps=2.34 +ep50 val_rmse=1.17491 val_adapt_rmse=0.78578 adapt_steps=2.60 halt=0.39 train_steps=1.98 +ep60 val_rmse=1.07281 val_adapt_rmse=0.74421 adapt_steps=2.29 halt=0.42 train_steps=1.87 +ep70 val_rmse=0.86657 val_adapt_rmse=0.73868 adapt_steps=2.39 halt=0.43 train_steps=1.77 +ep80 val_rmse=1.02592 val_adapt_rmse=0.70370 adapt_steps=2.29 halt=0.45 train_steps=1.68 +ep90 val_rmse=0.92289 val_adapt_rmse=0.68310 adapt_steps=2.12 halt=0.45 train_steps=1.67 +ep100 val_rmse=0.96157 val_adapt_rmse=0.68717 adapt_steps=2.11 halt=0.45 train_steps=1.66 +[ogbg-mollipo_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rmse': np.float32(0.8665701)} test={'rmse': np.float32(0.8929515)} adaptive={'rmse': np.float32(0.7886162)} steps=2.316666666666667 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=pna compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view pna --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='min')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +/orion/u/oscarwan/rrog-gnn-runner/.venv/lib/python3.13/site-packages/torch_geometric/utils/_scatter.py:91: UserWarning: The usage of `scatter(reduce='max')` can be accelerated via the 'torch-scatter' package, but it was not found + warnings.warn( +ep10 val_rmse=1.28346 val_adapt_rmse=1.19172 adapt_steps=7.30 halt=0.17 train_steps=4.01 +ep20 val_rmse=1.19132 val_adapt_rmse=1.15026 adapt_steps=5.02 halt=0.16 train_steps=4.12 +ep30 val_rmse=1.24669 val_adapt_rmse=1.23446 adapt_steps=7.86 halt=0.17 train_steps=3.95 +ep40 val_rmse=1.09641 val_adapt_rmse=1.01818 adapt_steps=6.98 halt=0.17 train_steps=3.91 +ep50 val_rmse=1.74926 val_adapt_rmse=1.34685 adapt_steps=6.52 halt=0.19 train_steps=3.68 +ep60 val_rmse=1.01835 val_adapt_rmse=1.01362 adapt_steps=7.48 halt=0.19 train_steps=3.73 +ep70 val_rmse=0.91474 val_adapt_rmse=0.86541 adapt_steps=4.82 halt=0.22 train_steps=3.43 +ep80 val_rmse=1.25632 val_adapt_rmse=0.98700 adapt_steps=3.31 halt=0.29 train_steps=2.85 +ep90 val_rmse=1.07636 val_adapt_rmse=0.88479 adapt_steps=3.19 halt=0.30 train_steps=2.75 +ep100 val_rmse=0.96630 val_adapt_rmse=0.82440 adapt_steps=3.11 halt=0.32 train_steps=2.60 +[ogbg-mollipo_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rmse': np.float32(0.91474026)} test={'rmse': np.float32(0.92669034)} adaptive={'rmse': np.float32(0.87501276)} steps=4.614285714285714 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view gen --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.86424 val_adapt_rmse=1.27606 adapt_steps=3.81 halt=0.18 train_steps=4.03 +ep20 val_rmse=1.04319 val_adapt_rmse=1.04292 adapt_steps=7.96 halt=0.22 train_steps=3.37 +ep30 val_rmse=0.92998 val_adapt_rmse=0.93388 adapt_steps=4.37 halt=0.24 train_steps=3.26 +ep40 val_rmse=1.51121 val_adapt_rmse=1.15834 adapt_steps=4.63 halt=0.23 train_steps=3.36 +ep50 val_rmse=0.96101 val_adapt_rmse=0.84809 adapt_steps=3.66 halt=0.26 train_steps=3.06 +ep60 val_rmse=1.14213 val_adapt_rmse=1.05520 adapt_steps=3.24 halt=0.28 train_steps=2.91 +ep70 val_rmse=0.93218 val_adapt_rmse=0.81774 adapt_steps=3.45 halt=0.33 train_steps=2.58 +ep80 val_rmse=0.95239 val_adapt_rmse=0.77677 adapt_steps=2.99 halt=0.35 train_steps=2.34 +ep90 val_rmse=0.93136 val_adapt_rmse=0.76093 adapt_steps=2.85 halt=0.36 train_steps=2.30 +ep100 val_rmse=0.93118 val_adapt_rmse=0.76794 adapt_steps=2.76 halt=0.36 train_steps=2.30 +[ogbg-mollipo_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rmse': np.float32(0.9299843)} test={'rmse': np.float32(0.9385538)} adaptive={'rmse': np.float32(0.9375044)} steps=4.252380952380952 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view film --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.88452 val_adapt_rmse=1.87707 adapt_steps=7.73 halt=0.15 train_steps=4.10 +ep20 val_rmse=1.09441 val_adapt_rmse=1.07942 adapt_steps=4.85 halt=0.16 train_steps=4.14 +ep30 val_rmse=1.46053 val_adapt_rmse=1.45161 adapt_steps=6.21 halt=0.18 train_steps=3.76 +ep40 val_rmse=1.06170 val_adapt_rmse=1.01696 adapt_steps=6.72 halt=0.19 train_steps=3.72 +ep50 val_rmse=1.10540 val_adapt_rmse=0.99523 adapt_steps=4.06 halt=0.22 train_steps=3.40 +ep60 val_rmse=1.28399 val_adapt_rmse=1.00615 adapt_steps=3.50 halt=0.25 train_steps=2.98 +ep70 val_rmse=0.98637 val_adapt_rmse=0.86637 adapt_steps=3.27 halt=0.28 train_steps=2.68 +ep80 val_rmse=1.05416 val_adapt_rmse=0.83985 adapt_steps=3.08 halt=0.33 train_steps=2.34 +ep90 val_rmse=1.01988 val_adapt_rmse=0.82922 adapt_steps=2.91 halt=0.34 train_steps=2.30 +ep100 val_rmse=1.01144 val_adapt_rmse=0.82713 adapt_steps=2.86 halt=0.35 train_steps=2.21 +[ogbg-mollipo_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rmse': np.float32(0.9863713)} test={'rmse': np.float32(0.97120994)} adaptive={'rmse': np.float32(0.8344992)} steps=3.211904761904762 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=resgated compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view resgated --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.34779 val_adapt_rmse=0.93483 adapt_steps=4.54 halt=0.20 train_steps=3.73 +ep20 val_rmse=1.15086 val_adapt_rmse=0.84117 adapt_steps=3.96 halt=0.23 train_steps=3.41 +ep30 val_rmse=1.08380 val_adapt_rmse=0.86139 adapt_steps=3.40 halt=0.31 train_steps=2.63 +ep40 val_rmse=1.24278 val_adapt_rmse=1.00814 adapt_steps=2.49 halt=0.35 train_steps=2.27 +ep50 val_rmse=0.85133 val_adapt_rmse=0.72631 adapt_steps=2.55 halt=0.35 train_steps=2.27 +ep60 val_rmse=0.84346 val_adapt_rmse=0.71899 adapt_steps=2.54 halt=0.39 train_steps=2.02 +ep70 val_rmse=0.83666 val_adapt_rmse=0.72927 adapt_steps=2.23 halt=0.43 train_steps=1.81 +ep80 val_rmse=0.83940 val_adapt_rmse=0.68725 adapt_steps=2.22 halt=0.45 train_steps=1.70 +ep90 val_rmse=0.86161 val_adapt_rmse=0.68760 adapt_steps=2.14 halt=0.45 train_steps=1.67 +ep100 val_rmse=0.83073 val_adapt_rmse=0.67974 adapt_steps=2.15 halt=0.46 train_steps=1.66 +[ogbg-mollipo_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rmse': np.float32(0.8307315)} test={'rmse': np.float32(0.88247204)} adaptive={'rmse': np.float32(0.7250288)} steps=2.1166666666666667 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=tag compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view tag --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.43440 val_adapt_rmse=1.35579 adapt_steps=6.75 halt=0.16 train_steps=4.16 +ep20 val_rmse=1.18041 val_adapt_rmse=1.01839 adapt_steps=4.81 halt=0.23 train_steps=3.30 +ep30 val_rmse=1.33342 val_adapt_rmse=1.19676 adapt_steps=4.62 halt=0.24 train_steps=3.29 +ep40 val_rmse=1.14385 val_adapt_rmse=0.94329 adapt_steps=3.83 halt=0.30 train_steps=2.73 +ep50 val_rmse=0.98573 val_adapt_rmse=0.81495 adapt_steps=3.43 halt=0.29 train_steps=2.84 +ep60 val_rmse=1.09272 val_adapt_rmse=0.87901 adapt_steps=3.29 halt=0.35 train_steps=2.31 +ep70 val_rmse=0.98565 val_adapt_rmse=0.80267 adapt_steps=2.66 halt=0.37 train_steps=2.19 +ep80 val_rmse=0.90149 val_adapt_rmse=0.75615 adapt_steps=2.45 halt=0.38 train_steps=2.15 +ep90 val_rmse=0.86151 val_adapt_rmse=0.74536 adapt_steps=2.43 halt=0.39 train_steps=2.05 +ep100 val_rmse=0.86321 val_adapt_rmse=0.74945 adapt_steps=2.36 halt=0.40 train_steps=2.01 +[ogbg-mollipo_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(0.86150765)} test={'rmse': np.float32(0.9196055)} adaptive={'rmse': np.float32(0.80384284)} steps=2.35 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=sgc compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view sgc --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.56494 val_adapt_rmse=1.41555 adapt_steps=7.49 halt=0.17 train_steps=3.92 +ep20 val_rmse=2.31785 val_adapt_rmse=1.61681 adapt_steps=4.02 halt=0.21 train_steps=3.49 +ep30 val_rmse=1.08211 val_adapt_rmse=1.00973 adapt_steps=3.67 halt=0.27 train_steps=3.19 +ep40 val_rmse=1.31061 val_adapt_rmse=0.94954 adapt_steps=3.96 halt=0.26 train_steps=2.95 +ep50 val_rmse=1.32023 val_adapt_rmse=0.95793 adapt_steps=3.31 halt=0.26 train_steps=2.99 +ep60 val_rmse=1.03568 val_adapt_rmse=0.85814 adapt_steps=3.84 halt=0.33 train_steps=2.48 +ep70 val_rmse=1.04043 val_adapt_rmse=0.80950 adapt_steps=2.95 halt=0.33 train_steps=2.40 +ep80 val_rmse=0.91964 val_adapt_rmse=0.75463 adapt_steps=2.46 halt=0.39 train_steps=2.06 +ep90 val_rmse=1.05229 val_adapt_rmse=0.75106 adapt_steps=2.40 halt=0.40 train_steps=1.98 +ep100 val_rmse=0.99474 val_adapt_rmse=0.76454 adapt_steps=2.36 halt=0.40 train_steps=1.96 +[ogbg-mollipo_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rmse': np.float32(0.9196411)} test={'rmse': np.float32(1.0144817)} adaptive={'rmse': np.float32(0.84780806)} steps=2.3452380952380953 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view cheb --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.42499 val_adapt_rmse=1.05416 adapt_steps=3.42 halt=0.19 train_steps=3.92 +ep20 val_rmse=1.07841 val_adapt_rmse=0.88516 adapt_steps=3.39 halt=0.32 train_steps=2.56 +ep30 val_rmse=1.03923 val_adapt_rmse=0.87261 adapt_steps=4.42 halt=0.31 train_steps=2.51 +ep40 val_rmse=1.21034 val_adapt_rmse=0.82150 adapt_steps=2.78 halt=0.33 train_steps=2.51 +ep50 val_rmse=1.11343 val_adapt_rmse=0.92757 adapt_steps=2.13 halt=0.42 train_steps=1.90 +ep60 val_rmse=0.96797 val_adapt_rmse=0.88460 adapt_steps=2.27 halt=0.43 train_steps=1.82 +ep70 val_rmse=0.81329 val_adapt_rmse=0.73885 adapt_steps=2.09 halt=0.44 train_steps=1.74 +ep80 val_rmse=0.79543 val_adapt_rmse=0.73836 adapt_steps=2.12 halt=0.45 train_steps=1.70 +ep90 val_rmse=0.74588 val_adapt_rmse=0.70559 adapt_steps=2.05 halt=0.46 train_steps=1.64 +ep100 val_rmse=0.75996 val_adapt_rmse=0.71414 adapt_steps=2.04 halt=0.47 train_steps=1.61 +[ogbg-mollipo_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rmse': np.float32(0.74587685)} test={'rmse': np.float32(0.80546176)} adaptive={'rmse': np.float32(0.74045366)} steps=2.033333333333333 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view arma --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=108.34754 val_adapt_rmse=108.19418 adapt_steps=6.18 halt=0.21 train_steps=3.49 +ep20 val_rmse=2266.93286 val_adapt_rmse=2266.91235 adapt_steps=4.57 halt=0.23 train_steps=3.37 +ep30 val_rmse=2111.57764 val_adapt_rmse=2111.54224 adapt_steps=3.60 halt=0.26 train_steps=3.07 +ep40 val_rmse=108348.03906 val_adapt_rmse=108348.01562 adapt_steps=3.31 halt=0.31 train_steps=2.56 +ep50 val_rmse=182760.04688 val_adapt_rmse=182759.93750 adapt_steps=3.01 halt=0.35 train_steps=2.25 +ep60 val_rmse=164947.39062 val_adapt_rmse=164947.28125 adapt_steps=3.77 halt=0.34 train_steps=2.36 +ep70 val_rmse=15163.92676 val_adapt_rmse=15163.80664 adapt_steps=2.50 halt=0.41 train_steps=1.95 +ep80 val_rmse=25785.35156 val_adapt_rmse=25785.21094 adapt_steps=2.29 halt=0.40 train_steps=1.97 +ep90 val_rmse=17197.17773 val_adapt_rmse=17197.09961 adapt_steps=2.17 halt=0.44 train_steps=1.78 +ep100 val_rmse=18469.90625 val_adapt_rmse=18469.83008 adapt_steps=2.14 halt=0.44 train_steps=1.76 +[ogbg-mollipo_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=10 val={'rmse': np.float32(108.34754)} test={'rmse': np.float32(1.5814604)} adaptive={'rmse': np.float32(1.2714993)} steps=6.019047619047619 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view mf --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.22657 val_adapt_rmse=1.19078 adapt_steps=6.04 halt=0.16 train_steps=4.01 +ep20 val_rmse=1.00560 val_adapt_rmse=0.97855 adapt_steps=4.33 halt=0.23 train_steps=3.33 +ep30 val_rmse=1.42232 val_adapt_rmse=1.00428 adapt_steps=3.31 halt=0.28 train_steps=2.89 +ep40 val_rmse=1.33162 val_adapt_rmse=0.99679 adapt_steps=3.43 halt=0.32 train_steps=2.59 +ep50 val_rmse=1.29004 val_adapt_rmse=0.84554 adapt_steps=3.06 halt=0.35 train_steps=2.23 +ep60 val_rmse=1.26334 val_adapt_rmse=0.87993 adapt_steps=2.58 halt=0.40 train_steps=2.00 +ep70 val_rmse=1.29285 val_adapt_rmse=0.77047 adapt_steps=2.37 halt=0.41 train_steps=1.92 +ep80 val_rmse=1.30170 val_adapt_rmse=0.73633 adapt_steps=2.18 halt=0.42 train_steps=1.83 +ep90 val_rmse=1.13537 val_adapt_rmse=0.75800 adapt_steps=2.15 halt=0.44 train_steps=1.74 +ep100 val_rmse=1.07797 val_adapt_rmse=0.75675 adapt_steps=2.15 halt=0.44 train_steps=1.75 +[ogbg-mollipo_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=20 val={'rmse': np.float32(1.005599)} test={'rmse': np.float32(0.98203164)} adaptive={'rmse': np.float32(0.9414124)} steps=4.321428571428571 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-mollipo view=appnp compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-mollipo --view appnp --compute rrog-act --T 1 --n_sup 3 --hidden 128 --bs 128 --epochs 100 --eval_every 10 --agg_layers 5 --compute_layers 2 --seed 0 --lam_q 0.1 --halt_max_steps 8 --halt_min_steps 2 --halt_target loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:1 --num_workers 0 +ep10 val_rmse=1.16326 val_adapt_rmse=1.09274 adapt_steps=5.73 halt=0.21 train_steps=3.61 +ep20 val_rmse=2.63258 val_adapt_rmse=1.56333 adapt_steps=4.45 halt=0.24 train_steps=3.16 +ep30 val_rmse=1.78657 val_adapt_rmse=1.24891 adapt_steps=4.25 halt=0.27 train_steps=3.00 +ep40 val_rmse=1.38779 val_adapt_rmse=1.02154 adapt_steps=2.87 halt=0.32 train_steps=2.53 +ep50 val_rmse=1.18581 val_adapt_rmse=0.83394 adapt_steps=2.96 halt=0.34 train_steps=2.37 +ep60 val_rmse=1.45301 val_adapt_rmse=0.94618 adapt_steps=2.93 halt=0.35 train_steps=2.25 +ep70 val_rmse=1.13892 val_adapt_rmse=0.85011 adapt_steps=2.33 halt=0.43 train_steps=1.82 +ep80 val_rmse=1.14148 val_adapt_rmse=0.83007 adapt_steps=2.34 halt=0.43 train_steps=1.77 +ep90 val_rmse=1.20479 val_adapt_rmse=0.82034 adapt_steps=2.19 halt=0.46 train_steps=1.65 +ep100 val_rmse=1.18848 val_adapt_rmse=0.81683 adapt_steps=2.25 halt=0.45 train_steps=1.66 +[ogbg-mollipo_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rmse': np.float32(1.1389227)} test={'rmse': np.float32(1.0732719)} adaptive={'rmse': np.float32(0.83319956)} steps=2.2404761904761905 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-mollipo_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json diff --git a/logs/ogbg-molsider_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-molsider_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..68adc15 --- /dev/null +++ b/logs/ogbg-molsider_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,278 @@ +[run] ogbg-molsider view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.52242 val_adapt_rocauc=0.52242 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.57120 val_adapt_rocauc=0.57031 adapt_steps=7.99 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.52140 val_adapt_rocauc=0.52140 adapt_steps=8.00 halt=0.12 train_steps=4.45 +ep40 val_rocauc=0.54349 val_adapt_rocauc=0.54351 adapt_steps=7.93 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.52355 val_adapt_rocauc=0.52355 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.57651 val_adapt_rocauc=0.57763 adapt_steps=7.97 halt=0.12 train_steps=4.47 +ep70 val_rocauc=0.59417 val_adapt_rocauc=0.59417 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.57162 val_adapt_rocauc=0.57204 adapt_steps=7.96 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.58977 val_adapt_rocauc=0.58977 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep100 val_rocauc=0.59364 val_adapt_rocauc=0.59378 adapt_steps=7.99 halt=0.12 train_steps=4.50 +[ogbg-molsider_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.5941723817458207} test={'rocauc': 0.5949106211087469} adaptive={'rocauc': 0.5949106211087469} steps=8.0 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.52714 val_adapt_rocauc=0.52714 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.53410 val_adapt_rocauc=0.53410 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.55999 val_adapt_rocauc=0.55999 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.58039 val_adapt_rocauc=0.58039 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.59855 val_adapt_rocauc=0.59871 adapt_steps=7.99 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.58511 val_adapt_rocauc=0.58521 adapt_steps=7.98 halt=0.12 train_steps=4.50 +ep70 val_rocauc=0.58872 val_adapt_rocauc=0.58872 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.59935 val_adapt_rocauc=0.59935 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.60537 val_adapt_rocauc=0.60495 adapt_steps=7.96 halt=0.12 train_steps=4.47 +ep100 val_rocauc=0.61174 val_adapt_rocauc=0.61174 adapt_steps=8.00 halt=0.12 train_steps=4.50 +[ogbg-molsider_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.6117392254931898} test={'rocauc': 0.6143023355631505} adaptive={'rocauc': 0.6147815453760646} steps=7.958041958041958 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.53639 val_adapt_rocauc=0.53639 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.54446 val_adapt_rocauc=0.54446 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.56844 val_adapt_rocauc=0.56844 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.59523 val_adapt_rocauc=0.59523 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.58925 val_adapt_rocauc=0.58925 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.61196 val_adapt_rocauc=0.60952 adapt_steps=7.48 halt=0.13 train_steps=4.43 +ep70 val_rocauc=0.60679 val_adapt_rocauc=0.60935 adapt_steps=7.81 halt=0.12 train_steps=4.49 +ep80 val_rocauc=0.62425 val_adapt_rocauc=0.62328 adapt_steps=7.92 halt=0.12 train_steps=4.49 +ep90 val_rocauc=0.63455 val_adapt_rocauc=0.63464 adapt_steps=7.98 halt=0.12 train_steps=4.50 +ep100 val_rocauc=0.63261 val_adapt_rocauc=0.63316 adapt_steps=7.90 halt=0.13 train_steps=4.48 +[ogbg-molsider_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.634553246023819} test={'rocauc': 0.6445134528927392} adaptive={'rocauc': 0.644509359822436} steps=7.93006993006993 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.53993 val_adapt_rocauc=0.53993 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.51721 val_adapt_rocauc=0.51820 adapt_steps=7.81 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.57455 val_adapt_rocauc=0.57455 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.54410 val_adapt_rocauc=0.54400 adapt_steps=7.98 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.57426 val_adapt_rocauc=0.57426 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.57583 val_adapt_rocauc=0.57668 adapt_steps=7.83 halt=0.12 train_steps=4.49 +ep70 val_rocauc=0.57077 val_adapt_rocauc=0.57333 adapt_steps=7.81 halt=0.13 train_steps=4.46 +ep80 val_rocauc=0.60329 val_adapt_rocauc=0.60324 adapt_steps=7.98 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.60080 val_adapt_rocauc=0.60075 adapt_steps=7.99 halt=0.12 train_steps=4.48 +ep100 val_rocauc=0.61496 val_adapt_rocauc=0.61461 adapt_steps=7.97 halt=0.13 train_steps=4.48 +[ogbg-molsider_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.6149561902831908} test={'rocauc': 0.6082036653138152} adaptive={'rocauc': 0.6072637395395359} steps=7.923076923076923 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.51326 val_adapt_rocauc=0.51326 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.53070 val_adapt_rocauc=0.53070 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.52081 val_adapt_rocauc=0.52081 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.53950 val_adapt_rocauc=0.53893 adapt_steps=7.83 halt=0.12 train_steps=4.47 +ep50 val_rocauc=0.55260 val_adapt_rocauc=0.55337 adapt_steps=7.90 halt=0.12 train_steps=4.48 +ep60 val_rocauc=0.55241 val_adapt_rocauc=0.55241 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep70 val_rocauc=0.56511 val_adapt_rocauc=0.56511 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.56634 val_adapt_rocauc=0.56626 adapt_steps=7.99 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.57675 val_adapt_rocauc=0.57675 adapt_steps=8.00 halt=0.12 train_steps=4.49 +ep100 val_rocauc=0.57777 val_adapt_rocauc=0.57777 adapt_steps=8.00 halt=0.12 train_steps=4.49 +[ogbg-molsider_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.5777678714357024} test={'rocauc': 0.6337321824820535} adaptive={'rocauc': 0.6339582691134998} steps=7.958041958041958 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.53249 val_adapt_rocauc=0.52907 adapt_steps=7.41 halt=0.12 train_steps=4.47 +ep20 val_rocauc=0.53857 val_adapt_rocauc=0.53838 adapt_steps=7.96 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.55430 val_adapt_rocauc=0.55430 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.55775 val_adapt_rocauc=0.55775 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.53048 val_adapt_rocauc=0.53048 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.58757 val_adapt_rocauc=0.58768 adapt_steps=7.99 halt=0.12 train_steps=4.50 +ep70 val_rocauc=0.58127 val_adapt_rocauc=0.58127 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.58969 val_adapt_rocauc=0.58958 adapt_steps=7.97 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.59525 val_adapt_rocauc=0.59512 adapt_steps=7.94 halt=0.13 train_steps=4.44 +ep100 val_rocauc=0.61397 val_adapt_rocauc=0.61302 adapt_steps=7.97 halt=0.12 train_steps=4.45 +[ogbg-molsider_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.6139745501285409} test={'rocauc': 0.6068834635828694} adaptive={'rocauc': 0.6064255172013142} steps=7.916083916083916 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.53954 val_adapt_rocauc=0.53954 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.54449 val_adapt_rocauc=0.54449 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.58517 val_adapt_rocauc=0.58517 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.57396 val_adapt_rocauc=0.57671 adapt_steps=7.88 halt=0.12 train_steps=4.45 +ep50 val_rocauc=0.58068 val_adapt_rocauc=0.58068 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.60139 val_adapt_rocauc=0.60139 adapt_steps=8.00 halt=0.12 train_steps=4.49 +ep70 val_rocauc=0.61355 val_adapt_rocauc=0.61355 adapt_steps=8.00 halt=0.12 train_steps=4.45 +ep80 val_rocauc=0.57128 val_adapt_rocauc=0.57180 adapt_steps=7.95 halt=0.12 train_steps=4.48 +ep90 val_rocauc=0.62410 val_adapt_rocauc=0.62410 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep100 val_rocauc=0.62875 val_adapt_rocauc=0.62875 adapt_steps=8.00 halt=0.12 train_steps=4.50 +[ogbg-molsider_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.6287543036419472} test={'rocauc': 0.621503855814713} adaptive={'rocauc': 0.6212391169096168} steps=7.951048951048951 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --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=0.53705 val_adapt_rocauc=0.53705 adapt_steps=8.00 halt=0.12 train_steps=4.50 +/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=0.49938 val_adapt_rocauc=0.49938 adapt_steps=8.00 halt=0.12 train_steps=4.43 +/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=0.50914 val_adapt_rocauc=0.50914 adapt_steps=8.00 halt=0.12 train_steps=4.50 +/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=0.52533 val_adapt_rocauc=0.52533 adapt_steps=8.00 halt=0.12 train_steps=4.50 +/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=0.56368 val_adapt_rocauc=0.56368 adapt_steps=8.00 halt=0.12 train_steps=4.50 +/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=0.58102 val_adapt_rocauc=0.58102 adapt_steps=8.00 halt=0.12 train_steps=4.50 +/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=0.55427 val_adapt_rocauc=0.55427 adapt_steps=8.00 halt=0.12 train_steps=4.50 +/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=0.56861 val_adapt_rocauc=0.56861 adapt_steps=8.00 halt=0.12 train_steps=4.50 +/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=0.54785 val_adapt_rocauc=0.54785 adapt_steps=8.00 halt=0.12 train_steps=4.50 +/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=0.56012 val_adapt_rocauc=0.56012 adapt_steps=8.00 halt=0.12 train_steps=4.50 +[ogbg-molsider_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.5810212759423172} test={'rocauc': 0.5397701280540309} adaptive={'rocauc': 0.5397701280540309} steps=8.0 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.52015 val_adapt_rocauc=0.51409 adapt_steps=7.45 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.56979 val_adapt_rocauc=0.56338 adapt_steps=7.21 halt=0.13 train_steps=4.43 +ep30 val_rocauc=0.57163 val_adapt_rocauc=0.57163 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.50300 val_adapt_rocauc=0.50300 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.55048 val_adapt_rocauc=0.55135 adapt_steps=7.97 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.55929 val_adapt_rocauc=0.55929 adapt_steps=8.00 halt=0.13 train_steps=4.50 +ep70 val_rocauc=0.61128 val_adapt_rocauc=0.61133 adapt_steps=7.96 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.61143 val_adapt_rocauc=0.61143 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.59636 val_adapt_rocauc=0.59635 adapt_steps=7.96 halt=0.12 train_steps=4.50 +ep100 val_rocauc=0.59800 val_adapt_rocauc=0.59800 adapt_steps=8.00 halt=0.12 train_steps=4.49 +[ogbg-molsider_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.6114344272964439} test={'rocauc': 0.6071293608886619} adaptive={'rocauc': 0.6071293608886619} steps=8.0 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.50663 val_adapt_rocauc=0.50663 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.53836 val_adapt_rocauc=0.53836 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.54072 val_adapt_rocauc=0.54072 adapt_steps=8.00 halt=0.12 train_steps=4.49 +ep40 val_rocauc=0.52242 val_adapt_rocauc=0.52242 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.52826 val_adapt_rocauc=0.52826 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.52041 val_adapt_rocauc=0.52041 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep70 val_rocauc=0.53993 val_adapt_rocauc=0.53993 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.52758 val_adapt_rocauc=0.52758 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.53864 val_adapt_rocauc=0.53864 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep100 val_rocauc=0.54079 val_adapt_rocauc=0.54079 adapt_steps=8.00 halt=0.12 train_steps=4.50 +[ogbg-molsider_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.5407876481859505} test={'rocauc': 0.5825278400429263} adaptive={'rocauc': 0.5825278400429263} steps=8.0 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 loss --halt_loss_threshold 0.2 --halt_exploration_prob 0.1 --act_train_mode stream --q_warmup_epochs 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.51625 val_adapt_rocauc=0.51625 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.55876 val_adapt_rocauc=0.55876 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.58353 val_adapt_rocauc=0.58374 adapt_steps=7.99 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.59270 val_adapt_rocauc=0.59269 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.59117 val_adapt_rocauc=0.59117 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.59394 val_adapt_rocauc=0.59559 adapt_steps=7.96 halt=0.12 train_steps=4.48 +ep70 val_rocauc=0.57628 val_adapt_rocauc=0.57628 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.59810 val_adapt_rocauc=0.59810 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.59935 val_adapt_rocauc=0.59919 adapt_steps=7.96 halt=0.12 train_steps=4.48 +ep100 val_rocauc=0.60973 val_adapt_rocauc=0.60972 adapt_steps=7.97 halt=0.12 train_steps=4.48 +[ogbg-molsider_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.609727680398977} test={'rocauc': 0.6245839801623748} adaptive={'rocauc': 0.624652550767547} steps=7.951048951048951 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.53875 val_adapt_rocauc=0.53875 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.55745 val_adapt_rocauc=0.55745 adapt_steps=8.00 halt=0.12 train_steps=4.49 +ep30 val_rocauc=0.52523 val_adapt_rocauc=0.52508 adapt_steps=7.99 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.57020 val_adapt_rocauc=0.57005 adapt_steps=7.99 halt=0.12 train_steps=4.43 +ep50 val_rocauc=0.57818 val_adapt_rocauc=0.57818 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.58430 val_adapt_rocauc=0.58478 adapt_steps=7.88 halt=0.13 train_steps=4.46 +ep70 val_rocauc=0.62524 val_adapt_rocauc=0.62524 adapt_steps=8.00 halt=0.12 train_steps=4.49 +ep80 val_rocauc=0.58782 val_adapt_rocauc=0.58782 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep90 val_rocauc=0.63291 val_adapt_rocauc=0.63291 adapt_steps=8.00 halt=0.13 train_steps=4.50 +ep100 val_rocauc=0.63016 val_adapt_rocauc=0.63032 adapt_steps=7.97 halt=0.13 train_steps=4.47 +[ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.6329113613630306} test={'rocauc': 0.6060675375955825} adaptive={'rocauc': 0.6066839663477379} steps=7.909090909090909 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.51769 val_adapt_rocauc=0.51769 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.54554 val_adapt_rocauc=0.54554 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.52433 val_adapt_rocauc=0.52433 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.54839 val_adapt_rocauc=0.54757 adapt_steps=7.82 halt=0.12 train_steps=4.40 +ep50 val_rocauc=0.56667 val_adapt_rocauc=0.56667 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.56001 val_adapt_rocauc=0.56001 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep70 val_rocauc=0.56325 val_adapt_rocauc=0.56263 adapt_steps=7.93 halt=0.12 train_steps=4.38 +ep80 val_rocauc=0.57410 val_adapt_rocauc=0.57405 adapt_steps=7.99 halt=0.12 train_steps=4.49 +ep90 val_rocauc=0.58333 val_adapt_rocauc=0.58333 adapt_steps=7.92 halt=0.13 train_steps=4.47 +ep100 val_rocauc=0.58659 val_adapt_rocauc=0.58673 adapt_steps=7.91 halt=0.13 train_steps=4.47 +[ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.5865936638036943} test={'rocauc': 0.624583829207758} adaptive={'rocauc': 0.6241791163198843} steps=7.881118881118881 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.52959 val_adapt_rocauc=0.53014 adapt_steps=7.83 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.59000 val_adapt_rocauc=0.59000 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.57720 val_adapt_rocauc=0.57720 adapt_steps=8.00 halt=0.12 train_steps=4.49 +ep40 val_rocauc=0.58010 val_adapt_rocauc=0.58016 adapt_steps=7.99 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.56105 val_adapt_rocauc=0.56396 adapt_steps=7.42 halt=0.12 train_steps=4.47 +ep60 val_rocauc=0.60272 val_adapt_rocauc=0.60144 adapt_steps=7.73 halt=0.13 train_steps=4.46 +ep70 val_rocauc=0.63704 val_adapt_rocauc=0.63704 adapt_steps=8.00 halt=0.12 train_steps=4.49 +ep80 val_rocauc=0.63367 val_adapt_rocauc=0.63378 adapt_steps=7.95 halt=0.12 train_steps=4.46 +ep90 val_rocauc=0.64091 val_adapt_rocauc=0.64157 adapt_steps=7.88 halt=0.13 train_steps=4.47 +ep100 val_rocauc=0.63703 val_adapt_rocauc=0.63925 adapt_steps=7.80 halt=0.13 train_steps=4.46 +[ogbg-molsider_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.6409076943311921} test={'rocauc': 0.6149744329414113} adaptive={'rocauc': 0.6144652607315165} steps=7.8671328671328675 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.51335 val_adapt_rocauc=0.51335 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.51105 val_adapt_rocauc=0.50798 adapt_steps=7.59 halt=0.13 train_steps=4.47 +ep30 val_rocauc=0.54401 val_adapt_rocauc=0.54401 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.57421 val_adapt_rocauc=0.57421 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.58087 val_adapt_rocauc=0.58094 adapt_steps=7.98 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.58740 val_adapt_rocauc=0.58740 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep70 val_rocauc=0.62738 val_adapt_rocauc=0.62725 adapt_steps=7.99 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.66049 val_adapt_rocauc=0.66028 adapt_steps=7.93 halt=0.13 train_steps=4.46 +ep90 val_rocauc=0.63467 val_adapt_rocauc=0.63512 adapt_steps=7.97 halt=0.13 train_steps=4.45 +ep100 val_rocauc=0.64614 val_adapt_rocauc=0.64687 adapt_steps=7.94 halt=0.12 train_steps=4.50 +[ogbg-molsider_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.6604919913889579} test={'rocauc': 0.5589855993934405} adaptive={'rocauc': 0.5580832949005652} steps=7.895104895104895 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-molsider view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:0 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-molsider --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:0 --num_workers 0 +ep10 val_rocauc=0.52188 val_adapt_rocauc=0.52188 adapt_steps=8.00 halt=0.12 train_steps=4.49 +ep20 val_rocauc=0.55853 val_adapt_rocauc=0.55853 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep30 val_rocauc=0.55126 val_adapt_rocauc=0.55126 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep40 val_rocauc=0.55645 val_adapt_rocauc=0.55527 adapt_steps=7.83 halt=0.12 train_steps=4.50 +ep50 val_rocauc=0.55799 val_adapt_rocauc=0.55799 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep60 val_rocauc=0.59604 val_adapt_rocauc=0.59534 adapt_steps=7.92 halt=0.12 train_steps=4.49 +ep70 val_rocauc=0.57920 val_adapt_rocauc=0.57921 adapt_steps=7.96 halt=0.12 train_steps=4.50 +ep80 val_rocauc=0.63001 val_adapt_rocauc=0.62920 adapt_steps=7.96 halt=0.12 train_steps=4.49 +ep90 val_rocauc=0.61962 val_adapt_rocauc=0.61885 adapt_steps=7.95 halt=0.12 train_steps=4.50 +ep100 val_rocauc=0.61522 val_adapt_rocauc=0.61430 adapt_steps=7.93 halt=0.12 train_steps=4.47 +[ogbg-molsider_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.630007512812611} test={'rocauc': 0.5843445908586726} adaptive={'rocauc': 0.5856297203566897} steps=7.8671328671328675 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:0 +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 0 --device cuda:0 --num_workers 0 +ep10 val_rocauc=0.52120 val_adapt_rocauc=0.52120 adapt_steps=8.00 halt=0.12 train_steps=4.50 +ep20 val_rocauc=0.54017 val_adapt_rocauc=0.53843 adapt_steps=7.87 halt=0.12 train_steps=4.49 +ep30 val_rocauc=0.53233 val_adapt_rocauc=0.53233 adapt_steps=8.00 halt=0.12 train_steps=4.48 +ep40 val_rocauc=0.53931 val_adapt_rocauc=0.53735 adapt_steps=7.72 halt=0.13 train_steps=4.46 +ep50 val_rocauc=0.56152 val_adapt_rocauc=0.56188 adapt_steps=7.75 halt=0.13 train_steps=4.47 +ep60 val_rocauc=0.57531 val_adapt_rocauc=0.57388 adapt_steps=7.59 halt=0.13 train_steps=4.41 +ep70 val_rocauc=0.55453 val_adapt_rocauc=0.56066 adapt_steps=7.09 halt=0.13 train_steps=4.44 +ep80 val_rocauc=0.58010 val_adapt_rocauc=0.57429 adapt_steps=7.18 halt=0.13 train_steps=4.45 +ep90 val_rocauc=0.56976 val_adapt_rocauc=0.56750 adapt_steps=7.34 halt=0.13 train_steps=4.44 +ep100 val_rocauc=0.57081 val_adapt_rocauc=0.56938 adapt_steps=7.11 halt=0.13 train_steps=4.39 +[ogbg-molsider_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.58009596629467} test={'rocauc': 0.6009364115000575} adaptive={'rocauc': 0.5959003553252203} steps=7.27972027972028 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-molsider_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json diff --git a/logs/ogbg-moltox21_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log b/logs/ogbg-moltox21_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log new file mode 100644 index 0000000..f6f668c --- /dev/null +++ b/logs/ogbg-moltox21_act_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_e100_s0.log @@ -0,0 +1,278 @@ +[run] ogbg-moltox21 view=gin compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +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 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=0.73518 val_adapt_rocauc=0.73087 adapt_steps=4.49 halt=0.28 train_steps=2.97 +ep20 val_rocauc=0.71039 val_adapt_rocauc=0.70931 adapt_steps=4.19 halt=0.28 train_steps=3.12 +ep30 val_rocauc=0.64736 val_adapt_rocauc=0.64143 adapt_steps=2.97 halt=0.28 train_steps=3.01 +ep40 val_rocauc=0.72656 val_adapt_rocauc=0.72350 adapt_steps=4.94 halt=0.27 train_steps=3.15 +ep50 val_rocauc=0.68867 val_adapt_rocauc=0.72256 adapt_steps=3.45 halt=0.29 train_steps=3.01 +ep60 val_rocauc=0.73756 val_adapt_rocauc=0.73596 adapt_steps=5.25 halt=0.28 train_steps=3.07 +ep70 val_rocauc=0.76341 val_adapt_rocauc=0.76107 adapt_steps=4.26 halt=0.29 train_steps=3.08 +ep80 val_rocauc=0.75486 val_adapt_rocauc=0.76475 adapt_steps=4.17 halt=0.30 train_steps=2.91 +ep90 val_rocauc=0.75145 val_adapt_rocauc=0.76691 adapt_steps=3.96 halt=0.31 train_steps=2.86 +ep100 val_rocauc=0.75282 val_adapt_rocauc=0.76451 adapt_steps=4.03 halt=0.30 train_steps=2.99 +[ogbg-moltox21_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.763406691780224} test={'rocauc': 0.7044116432874441} adaptive={'rocauc': 0.7111955163056712} steps=4.165816326530612 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_gin_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=gine compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.66186 val_adapt_rocauc=0.66299 adapt_steps=3.61 halt=0.28 train_steps=3.04 +ep20 val_rocauc=0.71740 val_adapt_rocauc=0.70641 adapt_steps=4.29 halt=0.30 train_steps=2.97 +ep30 val_rocauc=0.67926 val_adapt_rocauc=0.66414 adapt_steps=3.89 halt=0.28 train_steps=3.03 +ep40 val_rocauc=0.71787 val_adapt_rocauc=0.71626 adapt_steps=3.31 halt=0.29 train_steps=2.99 +ep50 val_rocauc=0.71826 val_adapt_rocauc=0.72383 adapt_steps=4.48 halt=0.29 train_steps=2.99 +ep60 val_rocauc=0.74768 val_adapt_rocauc=0.74921 adapt_steps=4.13 halt=0.29 train_steps=2.98 +ep70 val_rocauc=0.75742 val_adapt_rocauc=0.75384 adapt_steps=3.98 halt=0.29 train_steps=3.08 +ep80 val_rocauc=0.75643 val_adapt_rocauc=0.74987 adapt_steps=4.43 halt=0.31 train_steps=2.96 +ep90 val_rocauc=0.75761 val_adapt_rocauc=0.75256 adapt_steps=4.07 halt=0.30 train_steps=2.99 +ep100 val_rocauc=0.76165 val_adapt_rocauc=0.75534 adapt_steps=4.04 halt=0.31 train_steps=2.91 +[ogbg-moltox21_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.7616493170582249} test={'rocauc': 0.7120140634942237} adaptive={'rocauc': 0.7177387150880706} steps=3.931122448979592 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_gine_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1 +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 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=0.71516 val_adapt_rocauc=0.71843 adapt_steps=2.53 halt=0.29 train_steps=2.97 +ep20 val_rocauc=0.72992 val_adapt_rocauc=0.72176 adapt_steps=3.40 halt=0.30 train_steps=2.91 +ep30 val_rocauc=0.71748 val_adapt_rocauc=0.73422 adapt_steps=2.90 halt=0.30 train_steps=2.89 +ep40 val_rocauc=0.75509 val_adapt_rocauc=0.75981 adapt_steps=2.73 halt=0.32 train_steps=2.77 +ep50 val_rocauc=0.75894 val_adapt_rocauc=0.75514 adapt_steps=3.85 halt=0.33 train_steps=2.68 +ep60 val_rocauc=0.76775 val_adapt_rocauc=0.77369 adapt_steps=3.11 halt=0.35 train_steps=2.52 +ep70 val_rocauc=0.75412 val_adapt_rocauc=0.76445 adapt_steps=2.73 halt=0.38 train_steps=2.25 +ep80 val_rocauc=0.74793 val_adapt_rocauc=0.76557 adapt_steps=2.42 halt=0.40 train_steps=2.14 +ep90 val_rocauc=0.74992 val_adapt_rocauc=0.76933 adapt_steps=2.46 halt=0.42 train_steps=2.04 +ep100 val_rocauc=0.74961 val_adapt_rocauc=0.76962 adapt_steps=2.47 halt=0.42 train_steps=1.98 +[ogbg-moltox21_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.7677478126932855} test={'rocauc': 0.7135675459281269} adaptive={'rocauc': 0.7247326710130202} steps=3.2589285714285716 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_gcn_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=graphsage compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.66353 val_adapt_rocauc=0.66241 adapt_steps=6.17 halt=0.30 train_steps=2.79 +ep20 val_rocauc=0.69687 val_adapt_rocauc=0.71600 adapt_steps=3.03 halt=0.28 train_steps=3.04 +ep30 val_rocauc=0.74011 val_adapt_rocauc=0.73276 adapt_steps=3.99 halt=0.30 train_steps=2.91 +ep40 val_rocauc=0.77334 val_adapt_rocauc=0.77752 adapt_steps=4.25 halt=0.31 train_steps=2.82 +ep50 val_rocauc=0.77022 val_adapt_rocauc=0.78137 adapt_steps=3.56 halt=0.32 train_steps=2.78 +ep60 val_rocauc=0.77918 val_adapt_rocauc=0.77520 adapt_steps=3.29 halt=0.34 train_steps=2.65 +ep70 val_rocauc=0.77387 val_adapt_rocauc=0.77500 adapt_steps=2.79 halt=0.37 train_steps=2.37 +ep80 val_rocauc=0.76848 val_adapt_rocauc=0.77284 adapt_steps=2.96 halt=0.40 train_steps=2.15 +ep90 val_rocauc=0.76947 val_adapt_rocauc=0.77447 adapt_steps=2.75 halt=0.40 train_steps=2.14 +ep100 val_rocauc=0.77243 val_adapt_rocauc=0.77696 adapt_steps=2.73 halt=0.40 train_steps=2.18 +[ogbg-moltox21_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.7791810357079593} test={'rocauc': 0.7217088253529022} adaptive={'rocauc': 0.7282454305579198} steps=3.3903061224489797 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_graphsage_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=gatv2 compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.68214 val_adapt_rocauc=0.66532 adapt_steps=3.94 halt=0.27 train_steps=3.13 +ep20 val_rocauc=0.74877 val_adapt_rocauc=0.73707 adapt_steps=4.38 halt=0.29 train_steps=2.96 +ep30 val_rocauc=0.76735 val_adapt_rocauc=0.76425 adapt_steps=4.05 halt=0.30 train_steps=2.88 +ep40 val_rocauc=0.74010 val_adapt_rocauc=0.74347 adapt_steps=3.25 halt=0.31 train_steps=2.84 +ep50 val_rocauc=0.75964 val_adapt_rocauc=0.75650 adapt_steps=4.19 halt=0.33 train_steps=2.73 +ep60 val_rocauc=0.76484 val_adapt_rocauc=0.76741 adapt_steps=3.80 halt=0.30 train_steps=2.94 +ep70 val_rocauc=0.75529 val_adapt_rocauc=0.76640 adapt_steps=3.48 halt=0.35 train_steps=2.56 +ep80 val_rocauc=0.74656 val_adapt_rocauc=0.75879 adapt_steps=2.90 halt=0.36 train_steps=2.46 +ep90 val_rocauc=0.73882 val_adapt_rocauc=0.75668 adapt_steps=3.01 halt=0.39 train_steps=2.26 +ep100 val_rocauc=0.73632 val_adapt_rocauc=0.75539 adapt_steps=2.97 halt=0.38 train_steps=2.35 +[ogbg-moltox21_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=30 val={'rocauc': 0.767354951757618} test={'rocauc': 0.7155377552729235} adaptive={'rocauc': 0.7172144629316312} steps=4.042091836734694 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_gatv2_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1 +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 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=0.70226 val_adapt_rocauc=0.68368 adapt_steps=4.53 halt=0.28 train_steps=3.06 +ep20 val_rocauc=0.69482 val_adapt_rocauc=0.69973 adapt_steps=2.94 halt=0.28 train_steps=3.02 +ep30 val_rocauc=0.73997 val_adapt_rocauc=0.72387 adapt_steps=3.56 halt=0.29 train_steps=2.95 +ep40 val_rocauc=0.73715 val_adapt_rocauc=0.74654 adapt_steps=3.93 halt=0.30 train_steps=2.93 +ep50 val_rocauc=0.76406 val_adapt_rocauc=0.76634 adapt_steps=4.12 halt=0.33 train_steps=2.73 +ep60 val_rocauc=0.74500 val_adapt_rocauc=0.77410 adapt_steps=3.28 halt=0.35 train_steps=2.53 +ep70 val_rocauc=0.74134 val_adapt_rocauc=0.76240 adapt_steps=3.34 halt=0.38 train_steps=2.30 +ep80 val_rocauc=0.74270 val_adapt_rocauc=0.76980 adapt_steps=3.36 halt=0.37 train_steps=2.39 +ep90 val_rocauc=0.74651 val_adapt_rocauc=0.76905 adapt_steps=2.91 halt=0.39 train_steps=2.26 +ep100 val_rocauc=0.74268 val_adapt_rocauc=0.76713 adapt_steps=2.77 halt=0.38 train_steps=2.29 +[ogbg-moltox21_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.7640586359961631} test={'rocauc': 0.721040156330531} adaptive={'rocauc': 0.732265876016213} steps=4.089285714285714 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_graphconv_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=transformer compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.67594 val_adapt_rocauc=0.67877 adapt_steps=2.90 halt=0.27 train_steps=3.04 +ep20 val_rocauc=0.74853 val_adapt_rocauc=0.75119 adapt_steps=4.17 halt=0.28 train_steps=3.04 +ep30 val_rocauc=0.75978 val_adapt_rocauc=0.77013 adapt_steps=3.66 halt=0.28 train_steps=3.06 +ep40 val_rocauc=0.78399 val_adapt_rocauc=0.79071 adapt_steps=4.20 halt=0.32 train_steps=2.76 +ep50 val_rocauc=0.76021 val_adapt_rocauc=0.77394 adapt_steps=3.78 halt=0.32 train_steps=2.70 +ep60 val_rocauc=0.77603 val_adapt_rocauc=0.77979 adapt_steps=3.46 halt=0.35 train_steps=2.50 +ep70 val_rocauc=0.78021 val_adapt_rocauc=0.78970 adapt_steps=2.86 halt=0.39 train_steps=2.27 +ep80 val_rocauc=0.77594 val_adapt_rocauc=0.78551 adapt_steps=2.57 halt=0.42 train_steps=2.00 +ep90 val_rocauc=0.77827 val_adapt_rocauc=0.78340 adapt_steps=2.53 halt=0.42 train_steps=2.00 +ep100 val_rocauc=0.77925 val_adapt_rocauc=0.78691 adapt_steps=2.50 halt=0.43 train_steps=1.93 +[ogbg-moltox21_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=40 val={'rocauc': 0.7839946999002233} test={'rocauc': 0.723701343716436} adaptive={'rocauc': 0.724166086603444} steps=4.32780612244898 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_transformer_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1 +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 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=0.66669 val_adapt_rocauc=0.66243 adapt_steps=7.30 halt=0.29 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=0.69019 val_adapt_rocauc=0.67918 adapt_steps=5.84 halt=0.30 train_steps=2.85 +/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=0.70422 val_adapt_rocauc=0.69523 adapt_steps=4.71 halt=0.28 train_steps=3.13 +/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=0.71722 val_adapt_rocauc=0.71965 adapt_steps=2.52 halt=0.29 train_steps=2.95 +/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=0.70706 val_adapt_rocauc=0.70996 adapt_steps=6.01 halt=0.30 train_steps=2.87 +/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=0.73991 val_adapt_rocauc=0.74273 adapt_steps=4.85 halt=0.29 train_steps=2.98 +/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=0.72423 val_adapt_rocauc=0.73134 adapt_steps=2.85 halt=0.31 train_steps=2.81 +/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=0.75108 val_adapt_rocauc=0.74780 adapt_steps=4.23 halt=0.30 train_steps=2.91 +/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( +ep90 val_rocauc=0.76247 val_adapt_rocauc=0.75804 adapt_steps=3.94 halt=0.32 train_steps=2.79 +/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=0.75859 val_adapt_rocauc=0.75525 adapt_steps=3.88 halt=0.31 train_steps=2.83 +[ogbg-moltox21_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=90 val={'rocauc': 0.7624732674125697} test={'rocauc': 0.7137965144412185} adaptive={'rocauc': 0.7200143809038219} steps=4.058673469387755 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_pna_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=gen compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.65402 val_adapt_rocauc=0.65164 adapt_steps=3.07 halt=0.28 train_steps=2.91 +ep20 val_rocauc=0.67375 val_adapt_rocauc=0.66200 adapt_steps=3.13 halt=0.27 train_steps=3.10 +ep30 val_rocauc=0.70573 val_adapt_rocauc=0.70756 adapt_steps=3.81 halt=0.28 train_steps=3.02 +ep40 val_rocauc=0.73605 val_adapt_rocauc=0.74012 adapt_steps=3.52 halt=0.27 train_steps=3.16 +ep50 val_rocauc=0.71987 val_adapt_rocauc=0.73228 adapt_steps=3.73 halt=0.28 train_steps=3.07 +ep60 val_rocauc=0.74139 val_adapt_rocauc=0.73571 adapt_steps=3.62 halt=0.29 train_steps=3.01 +ep70 val_rocauc=0.74691 val_adapt_rocauc=0.74235 adapt_steps=3.40 halt=0.29 train_steps=3.05 +ep80 val_rocauc=0.75480 val_adapt_rocauc=0.76023 adapt_steps=3.50 halt=0.30 train_steps=2.97 +ep90 val_rocauc=0.75153 val_adapt_rocauc=0.75746 adapt_steps=3.76 halt=0.30 train_steps=2.96 +ep100 val_rocauc=0.75081 val_adapt_rocauc=0.76030 adapt_steps=3.70 halt=0.31 train_steps=2.86 +[ogbg-moltox21_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7548045767051833} test={'rocauc': 0.7300226043604717} adaptive={'rocauc': 0.7365872982320871} steps=3.433673469387755 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_gen_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=film compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.57757 val_adapt_rocauc=0.58541 adapt_steps=3.29 halt=0.31 train_steps=2.50 +ep20 val_rocauc=0.55966 val_adapt_rocauc=0.57096 adapt_steps=4.07 halt=0.28 train_steps=2.95 +ep30 val_rocauc=0.67643 val_adapt_rocauc=0.69130 adapt_steps=3.16 halt=0.28 train_steps=3.07 +ep40 val_rocauc=0.69186 val_adapt_rocauc=0.69814 adapt_steps=4.81 halt=0.28 train_steps=3.08 +ep50 val_rocauc=0.65619 val_adapt_rocauc=0.67613 adapt_steps=3.51 halt=0.27 train_steps=3.19 +ep60 val_rocauc=0.70395 val_adapt_rocauc=0.71660 adapt_steps=3.19 halt=0.31 train_steps=2.93 +ep70 val_rocauc=0.72848 val_adapt_rocauc=0.73235 adapt_steps=3.83 halt=0.31 train_steps=2.87 +ep80 val_rocauc=0.74847 val_adapt_rocauc=0.75433 adapt_steps=4.28 halt=0.30 train_steps=3.00 +ep90 val_rocauc=0.74854 val_adapt_rocauc=0.75584 adapt_steps=3.98 halt=0.32 train_steps=2.89 +ep100 val_rocauc=0.75129 val_adapt_rocauc=0.75550 adapt_steps=3.77 halt=0.32 train_steps=2.83 +[ogbg-moltox21_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.7512888457712221} test={'rocauc': 0.6885051838242511} adaptive={'rocauc': 0.6897262581951776} steps=3.55484693877551 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_film_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1 +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 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=0.69369 val_adapt_rocauc=0.68651 adapt_steps=3.85 halt=0.28 train_steps=3.03 +ep20 val_rocauc=0.73254 val_adapt_rocauc=0.71275 adapt_steps=5.04 halt=0.27 train_steps=3.19 +ep30 val_rocauc=0.70299 val_adapt_rocauc=0.70576 adapt_steps=3.07 halt=0.31 train_steps=2.80 +ep40 val_rocauc=0.76163 val_adapt_rocauc=0.76283 adapt_steps=4.54 halt=0.30 train_steps=2.90 +ep50 val_rocauc=0.75392 val_adapt_rocauc=0.75554 adapt_steps=4.28 halt=0.32 train_steps=2.71 +ep60 val_rocauc=0.77327 val_adapt_rocauc=0.77823 adapt_steps=3.05 halt=0.35 train_steps=2.49 +ep70 val_rocauc=0.77098 val_adapt_rocauc=0.77495 adapt_steps=3.01 halt=0.37 train_steps=2.37 +ep80 val_rocauc=0.77372 val_adapt_rocauc=0.78024 adapt_steps=2.81 halt=0.39 train_steps=2.26 +ep90 val_rocauc=0.77062 val_adapt_rocauc=0.77479 adapt_steps=2.66 halt=0.41 train_steps=2.11 +ep100 val_rocauc=0.76956 val_adapt_rocauc=0.77366 adapt_steps=2.72 halt=0.41 train_steps=2.10 +[ogbg-moltox21_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7737227459288354} test={'rocauc': 0.7454181481867773} adaptive={'rocauc': 0.7448724120402496} steps=2.7767857142857144 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_resgated_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1 +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 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=0.65152 val_adapt_rocauc=0.63598 adapt_steps=5.82 halt=0.28 train_steps=3.00 +ep20 val_rocauc=0.71815 val_adapt_rocauc=0.71620 adapt_steps=3.05 halt=0.28 train_steps=3.03 +ep30 val_rocauc=0.72675 val_adapt_rocauc=0.72953 adapt_steps=5.25 halt=0.30 train_steps=2.85 +ep40 val_rocauc=0.70713 val_adapt_rocauc=0.71988 adapt_steps=4.60 halt=0.30 train_steps=2.87 +ep50 val_rocauc=0.73557 val_adapt_rocauc=0.74105 adapt_steps=3.83 halt=0.31 train_steps=2.81 +ep60 val_rocauc=0.75468 val_adapt_rocauc=0.76648 adapt_steps=3.73 halt=0.31 train_steps=2.88 +ep70 val_rocauc=0.77518 val_adapt_rocauc=0.77338 adapt_steps=3.67 halt=0.33 train_steps=2.67 +ep80 val_rocauc=0.77918 val_adapt_rocauc=0.78370 adapt_steps=3.28 halt=0.35 train_steps=2.52 +ep90 val_rocauc=0.77746 val_adapt_rocauc=0.77301 adapt_steps=3.44 halt=0.36 train_steps=2.46 +ep100 val_rocauc=0.77192 val_adapt_rocauc=0.76945 adapt_steps=3.25 halt=0.36 train_steps=2.43 +[ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=80 val={'rocauc': 0.7791811026208421} test={'rocauc': 0.7194750067722034} adaptive={'rocauc': 0.7225403729796881} steps=3.318877551020408 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_tag_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1 +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 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=0.58511 val_adapt_rocauc=0.58665 adapt_steps=2.96 halt=0.29 train_steps=2.97 +ep20 val_rocauc=0.72203 val_adapt_rocauc=0.68935 adapt_steps=3.69 halt=0.29 train_steps=2.92 +ep30 val_rocauc=0.74058 val_adapt_rocauc=0.74146 adapt_steps=4.68 halt=0.28 train_steps=3.06 +ep40 val_rocauc=0.74632 val_adapt_rocauc=0.74580 adapt_steps=4.82 halt=0.29 train_steps=3.01 +ep50 val_rocauc=0.72977 val_adapt_rocauc=0.73373 adapt_steps=3.75 halt=0.31 train_steps=2.89 +ep60 val_rocauc=0.74202 val_adapt_rocauc=0.74441 adapt_steps=3.87 halt=0.32 train_steps=2.77 +ep70 val_rocauc=0.76058 val_adapt_rocauc=0.75527 adapt_steps=3.41 halt=0.34 train_steps=2.64 +ep80 val_rocauc=0.76323 val_adapt_rocauc=0.76205 adapt_steps=3.39 halt=0.36 train_steps=2.47 +ep90 val_rocauc=0.76418 val_adapt_rocauc=0.76382 adapt_steps=3.20 halt=0.37 train_steps=2.39 +ep100 val_rocauc=0.76686 val_adapt_rocauc=0.76364 adapt_steps=3.21 halt=0.36 train_steps=2.44 +[ogbg-moltox21_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=100 val={'rocauc': 0.7668620788836082} test={'rocauc': 0.7261733029463184} adaptive={'rocauc': 0.7330710041428746} steps=3.260204081632653 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_sgc_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=cheb compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.71726 val_adapt_rocauc=0.71158 adapt_steps=2.69 halt=0.30 train_steps=2.93 +ep20 val_rocauc=0.74514 val_adapt_rocauc=0.74244 adapt_steps=3.13 halt=0.29 train_steps=2.94 +ep30 val_rocauc=0.74745 val_adapt_rocauc=0.74514 adapt_steps=4.27 halt=0.31 train_steps=2.82 +ep40 val_rocauc=0.75855 val_adapt_rocauc=0.75693 adapt_steps=3.17 halt=0.32 train_steps=2.71 +ep50 val_rocauc=0.77450 val_adapt_rocauc=0.77541 adapt_steps=3.24 halt=0.35 train_steps=2.52 +ep60 val_rocauc=0.78240 val_adapt_rocauc=0.78798 adapt_steps=2.92 halt=0.38 train_steps=2.30 +ep70 val_rocauc=0.77174 val_adapt_rocauc=0.78493 adapt_steps=2.44 halt=0.42 train_steps=1.98 +ep80 val_rocauc=0.76722 val_adapt_rocauc=0.78035 adapt_steps=2.14 halt=0.45 train_steps=1.75 +ep90 val_rocauc=0.76854 val_adapt_rocauc=0.78215 adapt_steps=2.12 halt=0.47 train_steps=1.67 +ep100 val_rocauc=0.77046 val_adapt_rocauc=0.78353 adapt_steps=2.12 halt=0.46 train_steps=1.67 +[ogbg-moltox21_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=60 val={'rocauc': 0.7823963460925124} test={'rocauc': 0.7195427399764524} adaptive={'rocauc': 0.7202976536434207} steps=3.014030612244898 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_cheb_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=arma compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.63590 val_adapt_rocauc=0.63888 adapt_steps=2.72 halt=0.29 train_steps=2.91 +ep20 val_rocauc=0.71067 val_adapt_rocauc=0.70324 adapt_steps=4.82 halt=0.30 train_steps=2.86 +ep30 val_rocauc=0.75699 val_adapt_rocauc=0.76269 adapt_steps=4.94 halt=0.29 train_steps=2.96 +ep40 val_rocauc=0.75283 val_adapt_rocauc=0.76066 adapt_steps=2.89 halt=0.31 train_steps=2.87 +ep50 val_rocauc=0.74882 val_adapt_rocauc=0.75319 adapt_steps=2.96 halt=0.32 train_steps=2.76 +ep60 val_rocauc=0.74867 val_adapt_rocauc=0.75550 adapt_steps=2.58 halt=0.34 train_steps=2.61 +ep70 val_rocauc=0.75749 val_adapt_rocauc=0.77569 adapt_steps=2.86 halt=0.38 train_steps=2.31 +ep80 val_rocauc=0.73534 val_adapt_rocauc=0.77063 adapt_steps=2.44 halt=0.40 train_steps=2.10 +ep90 val_rocauc=0.74163 val_adapt_rocauc=0.77322 adapt_steps=2.37 halt=0.41 train_steps=2.04 +ep100 val_rocauc=0.74596 val_adapt_rocauc=0.77377 adapt_steps=2.39 halt=0.42 train_steps=1.95 +[ogbg-moltox21_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.7574890736647663} test={'rocauc': 0.7161943072626955} adaptive={'rocauc': 0.7237147258339075} steps=2.868622448979592 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_arma_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json +[run] ogbg-moltox21 view=mf compute=rrog-act mode=stream T=1 ns=3 seed=0 device=cuda:1 +python3 rrog/train_ogb_graphprop.py --dataset ogbg-moltox21 --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=0.68103 val_adapt_rocauc=0.67327 adapt_steps=6.68 halt=0.28 train_steps=3.06 +ep20 val_rocauc=0.71526 val_adapt_rocauc=0.70565 adapt_steps=3.58 halt=0.27 train_steps=3.17 +ep30 val_rocauc=0.73936 val_adapt_rocauc=0.73882 adapt_steps=4.88 halt=0.30 train_steps=2.92 +ep40 val_rocauc=0.68475 val_adapt_rocauc=0.69545 adapt_steps=3.09 halt=0.32 train_steps=2.71 +ep50 val_rocauc=0.72737 val_adapt_rocauc=0.73189 adapt_steps=3.75 halt=0.33 train_steps=2.71 +ep60 val_rocauc=0.76486 val_adapt_rocauc=0.77034 adapt_steps=3.49 halt=0.35 train_steps=2.53 +ep70 val_rocauc=0.76555 val_adapt_rocauc=0.77366 adapt_steps=2.97 halt=0.37 train_steps=2.39 +ep80 val_rocauc=0.76124 val_adapt_rocauc=0.77200 adapt_steps=2.91 halt=0.40 train_steps=2.18 +ep90 val_rocauc=0.75552 val_adapt_rocauc=0.76936 adapt_steps=2.66 halt=0.40 train_steps=2.13 +ep100 val_rocauc=0.75477 val_adapt_rocauc=0.76857 adapt_steps=2.64 halt=0.42 train_steps=2.02 +[ogbg-moltox21_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=70 val={'rocauc': 0.76555289309204} test={'rocauc': 0.7235855082035453} adaptive={'rocauc': 0.7314152133751847} steps=2.9566326530612246 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_mf_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_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:1 +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 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=0.66956 val_adapt_rocauc=0.68596 adapt_steps=2.92 halt=0.30 train_steps=2.86 +ep20 val_rocauc=0.66741 val_adapt_rocauc=0.68976 adapt_steps=2.90 halt=0.31 train_steps=2.80 +ep30 val_rocauc=0.69725 val_adapt_rocauc=0.69142 adapt_steps=3.11 halt=0.33 train_steps=2.66 +ep40 val_rocauc=0.70858 val_adapt_rocauc=0.72396 adapt_steps=3.15 halt=0.36 train_steps=2.47 +ep50 val_rocauc=0.71714 val_adapt_rocauc=0.73276 adapt_steps=2.59 halt=0.39 train_steps=2.24 +ep60 val_rocauc=0.70738 val_adapt_rocauc=0.72373 adapt_steps=2.53 halt=0.42 train_steps=1.95 +ep70 val_rocauc=0.69595 val_adapt_rocauc=0.71924 adapt_steps=2.25 halt=0.43 train_steps=1.93 +ep80 val_rocauc=0.70875 val_adapt_rocauc=0.72985 adapt_steps=2.16 halt=0.44 train_steps=1.86 +ep90 val_rocauc=0.70758 val_adapt_rocauc=0.72805 adapt_steps=2.16 halt=0.44 train_steps=1.82 +ep100 val_rocauc=0.70806 val_adapt_rocauc=0.72668 adapt_steps=2.16 halt=0.44 train_steps=1.83 +[ogbg-moltox21_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0] best_ep=50 val={'rocauc': 0.7171412864790295} test={'rocauc': 0.7196990667216929} adaptive={'rocauc': 0.7331958989125181} steps=2.586734693877551 + wrote /orion/u/oscarwan/rrog-gnn-runner/runs/ogbg-moltox21_appnp_rrog-act_T1_ns3_stream_hm8_hmin2_loss0.2_lq0.1_hex0.1_qw0_h128_e100_s0.json |