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gem.sh
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gnn_type=gcn
device=0
cpus=0-15
# generate ground truth explanations
taskset -c $cpus python source/gem_gt.py --dataset Mutagenicity --gnn_type $gnn_type --device $device
taskset -c $cpus python source/gem_gt.py --dataset Proteins --gnn_type $gnn_type --device $device
taskset -c $cpus python source/gem_gt.py --dataset IMDB-B --gnn_type $gnn_type --device $device
taskset -c $cpus python source/gem_gt.py --dataset Mutag --gnn_type $gnn_type --device $device
taskset -c $cpus python source/gem_gt.py --dataset AIDS --gnn_type $gnn_type --device $device
taskset -c $cpus python source/gem_gt.py --dataset NCI1 --gnn_type $gnn_type --device $device
# collect explanations from datasets
taskset -c $cpus python source/gem.py --dataset Mutagenicity --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label
taskset -c $cpus python source/gem.py --dataset Proteins --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label
taskset -c $cpus python source/gem.py --dataset IMDB-B --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label
taskset -c $cpus python source/gem.py --dataset Mutag --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label
taskset -c $cpus python source/gem.py --dataset AIDS --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label
taskset -c $cpus python source/gem.py --dataset NCI1 --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label
# collect explanations from noisy datasets
taskset -c $cpus python source/gem.py --dataset Mutagenicity --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label --robustness topology_random
taskset -c $cpus python source/gem.py --dataset Proteins --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label --robustness topology_random
taskset -c $cpus python source/gem.py --dataset IMDB-B --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label --robustness topology_random
taskset -c $cpus python source/gem.py --dataset AIDS --gnn_type $gnn_type --device $device --weighted --gae3 --early_stop --normalize_feat --train_on_positive_label --robustness topology_random
# generate results
#gnn_type=gcn
#explainers="gem"
#metrics="faithfulness faithfulness_with_removal"
#for metric in $metrics; do
# for explainer in $explainers; do
# taskset -c $cpus python source/result_generator.py --explainer_name "$explainer" --dataset Mutagenicity --gnn_type "$gnn_type" --device $device --explanation_metric "$metric"
# taskset -c $cpus python source/result_generator.py --explainer_name "$explainer" --dataset Proteins --gnn_type "$gnn_type" --device $device --explanation_metric "$metric"
# taskset -c $cpus python source/result_generator.py --explainer_name "$explainer" --dataset IMDB-B --gnn_type "$gnn_type" --device $device --explanation_metric "$metric"
# taskset -c $cpus python source/result_generator.py --explainer_name "$explainer" --dataset AIDS --gnn_type "$gnn_type" --device $device --explanation_metric "$metric"
# taskset -c $cpus python source/result_generator.py --explainer_name "$explainer" --dataset Mutag --gnn_type "$gnn_type" --device $device --explanation_metric "$metric"
# taskset -c $cpus python source/result_generator.py --explainer_name "$explainer" --dataset NCI1 --gnn_type "$gnn_type" --device $device --explanation_metric "$metric"
# done
#done