chore: import upstream snapshot with attribution

2026-07-13 13:35:51 +08:00
commit c36a561cd8
2172 changed files with 455595 additions and 0 deletions
@@ -0,0 +1,88 @@
+#!/bin/bash
+
+# input arguments
+DATA="${1-DD}"  # ENZYMES, DD, PROTEINS, COLLAB, IMDB-BINARY, IMDB-MULTI
+device=${2-0}
+num_trials=${3-10}
+print_every=${4-10}
+
+
+# general settings
+hidden_gxn=96
+k1=0.8
+k2=0.7
+sortpooling_k=30
+hidden_final=128
+batch_size=64
+dropout=0.5
+cross_weight=1.0
+fuse_weight=0.9
+weight_decay=1e-3
+
+# dataset-specific settings
+case ${DATA} in
+IMDB-BINARY)
+  num_epochs=200
+  learning_rate=0.001
+  sortpooling_k=31
+  k1=0.8
+  k2=0.5
+  ;;
+IMDB-MULTI)
+  num_epochs=200
+  learning_rate=0.001
+  sortpooling_k=22
+  k1=0.8
+  k2=0.7
+  ;;
+COLLAB)
+  num_epochs=100
+  learning_rate=0.001
+  sortpooling_k=130
+  k1=0.9
+  k2=0.5
+  ;;
+DD)
+  num_epochs=100
+  learning_rate=0.0005
+  sortpooling_k=291
+  k1=0.8
+  k2=0.6
+  ;;
+PROTEINS)
+  num_epochs=100
+  learning_rate=0.001
+  sortpooling_k=32
+  k1=0.8
+  k2=0.7
+  ;;
+ENZYMES)
+  num_epochs=500
+  learning_rate=0.0001
+  sortpooling_k=42
+  k1=0.7
+  k2=0.5
+  ;;
+*)
+  num_epochs=500
+  learning_rate=0.00001
+  ;;
+esac
+
+
+python main.py \
+      --dataset $DATA \
+      --lr $learning_rate \
+      --epochs $num_epochs \
+      --hidden_dim $hidden_gxn \
+      --final_dense_hidden_dim $hidden_final \
+      --readout_nodes $sortpooling_k \
+      --pool_ratios $k1 $k2 \
+      --batch_size $batch_size \
+      --device $device \
+      --dropout $dropout \
+      --cross_weight $cross_weight\
+      --fuse_weight $fuse_weight\
+      --weight_decay $weight_decay\
+      --num_trials $num_trials\
+      --print_every $print_every\
@@ -0,0 +1,96 @@
+#!/bin/bash
+
+# input arguments
+DATA="${1-DD}"  # ENZYMES, DD, PROTEINS, COLLAB, IMDB-BINARY, IMDB-MULTI
+device=${2-0}
+num_trials=${3-10}
+print_every=${4-10}
+
+
+# general settings
+hidden_gxn=96
+k1=0.8
+k2=0.7
+sortpooling_k=30
+hidden_final=128
+batch_size=64
+dropout=0.5
+cross_weight=1.0
+fuse_weight=0.9
+weight_decay=1e-3
+
+# dataset-specific settings
+case ${DATA} in
+IMDB-BINARY)
+  num_epochs=200
+  patience=40
+  learning_rate=0.001
+  sortpooling_k=31
+  k1=0.8
+  k2=0.5
+  ;;
+IMDB-MULTI)
+  num_epochs=200
+  patience=40
+  learning_rate=0.001
+  sortpooling_k=22
+  k1=0.8
+  k2=0.7
+  ;;
+COLLAB)
+  num_epochs=100
+  patience=20
+  learning_rate=0.001
+  sortpooling_k=130
+  k1=0.9
+  k2=0.5
+  ;;
+DD)
+  num_epochs=100
+  patience=20
+  learning_rate=0.0005
+  sortpooling_k=291
+  k1=0.8
+  k2=0.6
+  ;;
+PROTEINS)
+  num_epochs=100
+  patience=20
+  learning_rate=0.001
+  sortpooling_k=32
+  k1=0.8
+  k2=0.7
+  ;;
+ENZYMES)
+  num_epochs=500
+  patience=100
+  learning_rate=0.0001
+  sortpooling_k=42
+  k1=0.7
+  k2=0.5
+  ;;
+*)
+  num_epochs=500
+  patience=100
+  learning_rate=0.00001
+  ;;
+esac
+
+
+python main_early_stop.py \
+      --dataset $DATA \
+      --lr $learning_rate \
+      --epochs $num_epochs \
+      --hidden_dim $hidden_gxn \
+      --final_dense_hidden_dim $hidden_final \
+      --readout_nodes $sortpooling_k \
+      --pool_ratios $k1 $k2 \
+      --batch_size $batch_size \
+      --device $device \
+      --dropout $dropout \
+      --cross_weight $cross_weight\
+      --fuse_weight $fuse_weight\
+      --weight_decay $weight_decay\
+      --num_trials $num_trials\
+      --print_every $print_every\
+      --patience $patience\