# Format for each row: name in config.py; alias; range to search
# No spaces, except between these 3 fields
# Line breaks are used to union different grid search spaces
# Feel free to add '#' to add comments

# dataset: Single, task: node (Attention)
k_fold kfold [1,2]
dataset.task task ['node']
dataset.transductive trans [True]
optim.base_lr lr [0.05]
# GATv2 Set
gnn.lambda_policy l_lambda ['None']
gnn.convolve convolve [False]
gnn.share_weights share [True]
gnn.gcn_mode gcn_mode [False]
gnn.fixed_ansatz ansatz [True]
gnn.partial_ansatz partial [True]
bcsbm.p csbm_p [0.5]
bcsbm.q csbm_q [0.1,0.3,0.4]
bcsbm.mu_norm csbm_mu [0.0050,0.0065,0.0084,0.0108,0.0140,0.0181,0.0233,0.0302,0.0390,0.0504,0.0652,0.0843,0.1090,0.1409,0.1822,0.2356,0.3045,0.3937,0.5090,0.6581,0.8508,1.0999,1.4220,1.8384,2.3767,3.0727,3.9724,5.1357,6.6396,8.5839]
bcsbm.std_dev csbm_std_dev [0.1]
bcsbm.version toyv ['v2']
dataset.name dataset ['BCSBM']

# dataset: Single, task: node   gcn_mode: false  (Attention-lambdas)
k_fold kfold [1,2]
dataset.task task ['node']
dataset.transductive trans [True]
optim.base_lr lr [0.05]
# GATv2 Set
gnn.lambda_policy l_lambda [None]
gnn.convolve convolve [True]
gnn.share_weights share [True]
gnn.gcn_mode gcn_mode [False]
gnn.fixed_ansatz ansatz [True]
gnn.partial_ansatz partial [True]
bcsbm.p csbm_p [0.5]
bcsbm.q csbm_q [0.1,0.3,0.4]
bcsbm.mu_norm csbm_mu [0.0050,0.0065,0.0084,0.0108,0.0140,0.0181,0.0233,0.0302,0.0390,0.0504,0.0652,0.0843,0.1090,0.1409,0.1822,0.2356,0.3045,0.3937,0.5090,0.6581,0.8508,1.0999,1.4220,1.8384,2.3767,3.0727,3.9724,5.1357,6.6396,8.5839]
bcsbm.std_dev csbm_std_dev [0.1]
bcsbm.version toyv ['v2']
dataset.name dataset ['BCSBM']

# dataset: Single, task: node (GCN)
k_fold kfold [1,2]
dataset.task task ['node']
dataset.transductive trans [True]
optim.base_lr lr [0.05]
# GATv2 Set
gnn.lambda_policy l_lambda ['None']
gnn.convolve convolve [True]
gnn.share_weights share [True]
gnn.gcn_mode gcn_mode [True]
gnn.fixed_ansatz ansatz [True]
gnn.partial_ansatz partial [True]
bcsbm.p csbm_p [0.5]
bcsbm.q csbm_q [0.1,0.3,0.4]
bcsbm.mu_norm csbm_mu [0.0050,0.0065,0.0084,0.0108,0.0140,0.0181,0.0233,0.0302,0.0390,0.0504,0.0652,0.0843,0.1090,0.1409,0.1822,0.2356,0.3045,0.3937,0.5090,0.6581,0.8508,1.0999,1.4220,1.8384,2.3767,3.0727,3.9724,5.1357,6.6396,8.5839]
bcsbm.std_dev csbm_std_dev [0.1]
bcsbm.version toyv ['v2']
dataset.name dataset ['BCSBM']
