-
Notifications
You must be signed in to change notification settings - Fork 15
/
Copy pathtune_sccn.sh
179 lines (167 loc) · 7.51 KB
/
tune_sccn.sh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
# SCCN
python -m topobenchmark \
dataset=graph/MUTAG \
model=simplicial/topotune_onehasse,simplicial/topotune \
model.feature_encoder.out_channels=128 \
model.tune_gnn=GCN,GIN,GAT,GraphSAGE \
model.backbone.GNN.num_layers=1 \
model.backbone.neighborhoods=\[1-up_laplacian-0,1-up_incidence-0,1-down_incidence-1,1-down_laplacian-1,1-up_laplacian-1,1-up_incidence-1,1-down_incidence-2,1-down_laplacian-2\] \
model.backbone.layers=3 \
dataset.split_params.data_seed=1,3,5,7,9 \
model.readout.readout_name=NoReadOut \
logger.wandb.project=TopoTune_repSCCNone \
trainer.max_epochs=1000 \
trainer.min_epochs=50 \
trainer.devices=\[0\] \
transforms.graph2simplicial_lifting.signed=True \
model.feature_encoder.proj_dropout=0.25 \
dataset.dataloader_params.batch_size=64 \
trainer.check_val_every_n_epoch=5 \
callbacks.early_stopping.patience=10 \
optimizer.parameters.lr=0.001 \
--multirun &
python -m topobenchmark \
dataset=graph/NCI1 \
model=simplicial/topotune_onehasse,simplicial/topotune \
model.feature_encoder.out_channels=64 \
model.backbone.GNN.num_layers=1 \
model.tune_gnn=GCN,GIN,GAT,GraphSAGE \
model.backbone.neighborhoods=\[1-up_laplacian-0,1-up_incidence-0,1-down_incidence-1,1-down_laplacian-1,1-up_laplacian-1,1-up_incidence-1,1-down_incidence-2,1-down_laplacian-2\] \
model.backbone.layers=3 \
model.feature_encoder.proj_dropout=0.5 \
model.readout.readout_name=PropagateSignalDown \
transforms.graph2simplicial_lifting.signed=True \
dataset.dataloader_params.batch_size=128 \
dataset.split_params.data_seed=0,3,5,7,9 \
trainer.max_epochs=500 \
trainer.min_epochs=50 \
trainer.check_val_every_n_epoch=5 \
callbacks.early_stopping.patience=10 \
trainer.devices=\[0\] \
logger.wandb.project=TopoTune_repSCCNone \
optimizer.parameters.lr=0.001 \
--multirun &
python -m topobenchmark \
dataset=graph/NCI109 \
model=simplicial/topotune_onehasse,simplicial/topotune \
model.feature_encoder.out_channels=64 \
model.backbone.GNN.num_layers=1 \
model.tune_gnn=GCN,GIN,GAT,GraphSAGE \
model.backbone.neighborhoods=\[1-up_laplacian-0,1-up_incidence-0,1-down_incidence-1,1-down_laplacian-1,1-up_laplacian-1,1-up_incidence-1,1-down_incidence-2,1-down_laplacian-2\] \
model.backbone.layers=4 \
model.readout.readout_name=NoReadOut \
transforms.graph2simplicial_lifting.signed=True \
model.feature_encoder.proj_dropout=0.25 \
dataset.dataloader_params.batch_size=128 \
dataset.split_params.data_seed=0,3,5,7,9 \
trainer.max_epochs=500 \
trainer.min_epochs=50 \
trainer.check_val_every_n_epoch=5 \
callbacks.early_stopping.patience=10 \
trainer.devices=\[1\] \
logger.wandb.project=TopoTune_repSCCNone \
optimizer.parameters.lr=0.001 \
--multirun &
python -m topobenchmark \
model=simplicial/topotune_onehasse,simplicial/topotune \
model.tune_gnn=GCN,GIN,GAT,GraphSAGE \
model.backbone.neighborhoods=\[1-up_laplacian-0,1-up_incidence-0,1-down_incidence-1,1-down_laplacian-1,1-up_laplacian-1,1-up_incidence-1,1-down_incidence-2,1-down_laplacian-2\] \
dataset=graph/PROTEINS \
optimizer.parameters.lr=0.01 \
model.feature_encoder.out_channels=128 \
model.backbone.layers=3 \
model.readout.readout_name=NoReadOut \
transforms.graph2simplicial_lifting.signed=True \
model.feature_encoder.proj_dropout=0.5 \
dataset.dataloader_params.batch_size=128 \
dataset.split_params.data_seed=0,3,5,7,9 \
trainer.max_epochs=500 \
trainer.min_epochs=50 \
trainer.check_val_every_n_epoch=5 \
callbacks.early_stopping.patience=10 \
trainer.devices=\[1\] \
logger.wandb.project=TopoTune_repSCCNone \
--multirun &
python -m topobenchmark \
model=simplicial/topotune_onehasse,simplicial/topotune \
dataset=graph/ZINC \
model.tune_gnn=GCN,GIN,GAT,GraphSAGE \
model.backbone.neighborhoods=\[1-up_laplacian-0,1-up_incidence-0,1-down_incidence-1,1-down_laplacian-1,1-up_laplacian-1,1-up_incidence-1,1-down_incidence-2,1-down_laplacian-2\] \
optimizer.parameters.lr=0.001 \
model.feature_encoder.out_channels=128 \
model.backbone.layers=4 \
model.readout.readout_name=PropagateSignalDown \
transforms.graph2simplicial_lifting.signed=True \
model.feature_encoder.proj_dropout=0.5 \
dataset.dataloader_params.batch_size=128 \
callbacks.early_stopping.min_delta=0.005 \
transforms.one_hot_node_degree_features.degrees_fields=x \
seed=42,3,5,23,150 \
trainer.max_epochs=500 \
trainer.min_epochs=50 \
trainer.check_val_every_n_epoch=5 \
callbacks.early_stopping.patience=10 \
logger.wandb.project=TopoTune_repSCCNone \
trainer.devices=\[0\] \
--multirun &
python -m topobenchmark \
model=simplicial/topotune_onehasse,simplicial/topotune \
model.tune_gnn=GCN,GIN,GAT,GraphSAGE \
model.backbone.neighborhoods=\[1-up_laplacian-0,1-up_incidence-0,1-down_incidence-1,1-down_laplacian-1,1-up_laplacian-1,1-up_incidence-1,1-down_incidence-2,1-down_laplacian-2\] \
dataset=graph/cocitation_citeseer \
optimizer.parameters.lr=0.01 \
model.feature_encoder.out_channels=64 \
model.backbone.layers=2 \
model.readout.readout_name=NoReadOut \
transforms.graph2simplicial_lifting.signed=True \
model.feature_encoder.proj_dropout=0.5 \
dataset.dataloader_params.batch_size=1 \
dataset.split_params.data_seed=0,3,5,7,9 \
trainer.max_epochs=1000 \
trainer.min_epochs=50 \
trainer.check_val_every_n_epoch=1 \
callbacks.early_stopping.patience=50 \
logger.wandb.project=TopoTune_repSCCNone \
trainer.devices=\[0\] \
--multirun &
python -m topobenchmark \
model=simplicial/topotune_onehasse,simplicial/topotune \
model.tune_gnn=GCN,GIN,GAT,GraphSAGE \
model.backbone.GNN._target_=topobenchmark.nn.backbones.graph.IdentityGCN \
model.backbone.neighborhoods=\[1-up_laplacian-0,1-up_incidence-0,1-down_incidence-1,1-down_laplacian-1,1-up_laplacian-1,1-up_incidence-1,1-down_incidence-2,1-down_laplacian-2\] \
dataset=graph/cocitation_cora \
optimizer.parameters.lr=0.01 \
model.feature_encoder.out_channels=32 \
model.backbone.layers=2 \
model.readout.readout_name=NoReadOut \
transforms.graph2simplicial_lifting.signed=True \
model.feature_encoder.proj_dropout=0.5 \
dataset.dataloader_params.batch_size=1 \
dataset.split_params.data_seed=0,3,5,7,9 \
trainer.max_epochs=1000 \
trainer.min_epochs=50 \
trainer.check_val_every_n_epoch=1 \
callbacks.early_stopping.patience=50 \
logger.wandb.project=TopoTune_repSCCNone \
trainer.devices=\[1\] \
--multirun &
python -m topobenchmark \
model=simplicial/topotune_onehasse,simplicial/topotune \
model.tune_gnn=GCN,GIN,GAT,GraphSAGE \
model.backbone.neighborhoods=\[1-up_laplacian-0,1-up_incidence-0,1-down_incidence-1,1-down_laplacian-1,1-up_laplacian-1,1-up_incidence-1,1-down_incidence-2,1-down_laplacian-2\] \
dataset=graph/cocitation_pubmed \
optimizer.parameters.lr=0.01 \
model.feature_encoder.out_channels=64 \
model.backbone.layers=2 \
model.readout.readout_name=NoReadOut \
transforms.graph2simplicial_lifting.signed=True \
model.feature_encoder.proj_dropout=0.5 \
dataset.dataloader_params.batch_size=1 \
dataset.split_params.data_seed=0,3,5,7,9 \
trainer.max_epochs=1000 \
trainer.min_epochs=50 \
trainer.check_val_every_n_epoch=1 \
callbacks.early_stopping.patience=50 \
logger.wandb.project=TopoTune_repSCCNone \
trainer.devices=\[1\] \
--multirun