Configure Benchmark
Experiment Parameters
Refer to the help text by:
$ python benchmark/run_single.py --help
- --help
show this help message and exit
Logging configuration
- --seed SEED
random seed
- --dev DEV
GPU id
- --suffix SUFFIX
Result log file name.
None:not saving results- -quiet
File log.
True:dry run without saving logs- --storage STORAGE
Checkpoint log storage scheme. Options:
state_file,state_ram,state_gpu- --loglevel LOGLEVEL
Console log.
10:progress,15:train,20:info,25:result
Data configuration
- --data DATA
Dataset name
- --data_split DATA_SPLIT
Index or percentage of dataset split
- --normg NORMG
Generalized graph norm
- --normf NORMF
Embedding norm dimension.
0: feat-wise,1: node-wise,None: disable
Model configuration
- --model MODEL
Model class name
- --conv CONV
Conv class name
- --num_hops NUM_HOPS
Number of conv hops
- --in_layers IN_LAYERS
Number of MLP layers before conv
- --out_layers OUT_LAYERS
Number of MLP layers after conv
- --hidden_channels HIDDEN
Number of hidden width
- --dropout_lin DP_LIN
Dropout rate for linear
- --dropout_conv DP_CONV
Dropout rate for conv
Training configuration
- --epoch EPOCH
Number of epochs
- --patience PATIENCE
Patience epoch for early stopping
- --period PERIOD
Periodic saving epoch interval
- --batch BATCH
Batch size
- --lr_lin LR_LIN
Learning rate for linear
- --lr_conv LR_CONV
Learning rate for conv
- --wd_lin WD_LIN
Weight decay for linear
- --wd_conv WD_CONV
Weight decay for conv
Model-specific
- --theta_scheme THETA_SCHEME
Filter name
- --theta_param THETA_PARAM
Hyperparameter for filter
- --combine COMBINE
How to combine different channels of convs. Options:
sum,sum_weighted,cat
Conv-specific
- --alpha ALPHA
Decay factor
- --beta BETA
Scaling factor
Test flags
- --test_deg
Call
test_deg()
Add New Dataset
Append the SingleGraphLoader._resolve_import() method to include new datasets under respective protocols.