cfg.nr_aids.dataset_name = "AIDS"
cfg.nr_aids.format = "Network_repository"
cfg.nr_aids.task = "node"
cfg.nr_aids.task_type = "classification"
cfg.nr_aids.loss_fun = "cross_entropy"
cfg.nr_aids.task_dim = 38
cfg.nr_aids.split_mode = "random"
cfg.nr_aids.transductive = True
cfg.nr_aids.split_index = 0
cfg.nr_aids.feat_dim = 4
cfg.nr_aids.hidden_dim = 32
cfg.nr_aids.activate_fn = "torch.nn.ReLU()"
cfg.nr_aids.split = [0.6, 0.2, 0.2]
cfg.nr_aids.num_nodes = 31385

cfg.nr_ba_1_10_60_l5.dataset_name = "BA-1_10_60-L5"
cfg.nr_ba_1_10_60_l5.format = "Network_repository"
cfg.nr_ba_1_10_60_l5.task = "node"
cfg.nr_ba_1_10_60_l5.task_type = "classification"
cfg.nr_ba_1_10_60_l5.loss_fun = "cross_entropy"
cfg.nr_ba_1_10_60_l5.task_dim = 5
cfg.nr_ba_1_10_60_l5.split_mode = "random"
cfg.nr_ba_1_10_60_l5.transductive = True
cfg.nr_ba_1_10_60_l5.split_index = 0
cfg.nr_ba_1_10_60_l5.feat_dim = 1
cfg.nr_ba_1_10_60_l5.hidden_dim = 32
cfg.nr_ba_1_10_60_l5.activate_fn = "torch.nn.ReLU()"
cfg.nr_ba_1_10_60_l5.split = [0.6, 0.2, 0.2]
cfg.nr_ba_1_10_60_l5.num_nodes = 804

cfg.nr_ba_2_24_60_l2.dataset_name = "BA-2_24_60-L2"
cfg.nr_ba_2_24_60_l2.format = "Network_repository"
cfg.nr_ba_2_24_60_l2.task = "node"
cfg.nr_ba_2_24_60_l2.task_type = "classification"
cfg.nr_ba_2_24_60_l2.loss_fun = "cross_entropy"
cfg.nr_ba_2_24_60_l2.task_dim = 2
cfg.nr_ba_2_24_60_l2.split_mode = "random"
cfg.nr_ba_2_24_60_l2.transductive = True
cfg.nr_ba_2_24_60_l2.split_index = 0
cfg.nr_ba_2_24_60_l2.feat_dim = 1
cfg.nr_ba_2_24_60_l2.hidden_dim = 32
cfg.nr_ba_2_24_60_l2.activate_fn = "torch.nn.ReLU()"
cfg.nr_ba_2_24_60_l2.split = [0.6, 0.2, 0.2]
cfg.nr_ba_2_24_60_l2.num_nodes = 10693

cfg.nr_bzr.dataset_name = "BZR"
cfg.nr_bzr.format = "Network_repository"
cfg.nr_bzr.task = "node"
cfg.nr_bzr.task_type = "classification"
cfg.nr_bzr.loss_fun = "cross_entropy"
cfg.nr_bzr.task_dim = 53
cfg.nr_bzr.split_mode = "random"
cfg.nr_bzr.transductive = True
cfg.nr_bzr.split_index = 0
cfg.nr_bzr.feat_dim = 3
cfg.nr_bzr.hidden_dim = 32
cfg.nr_bzr.activate_fn = "torch.nn.ReLU()"
cfg.nr_bzr.split = [0.6, 0.2, 0.2]
cfg.nr_bzr.num_nodes = 14479

cfg.nr_cl_100k_1d8_l9.dataset_name = "CL-100K-1d8-L9"
cfg.nr_cl_100k_1d8_l9.format = "Network_repository"
cfg.nr_cl_100k_1d8_l9.task = "node"
cfg.nr_cl_100k_1d8_l9.task_type = "classification"
cfg.nr_cl_100k_1d8_l9.loss_fun = "cross_entropy"
cfg.nr_cl_100k_1d8_l9.task_dim = 9
cfg.nr_cl_100k_1d8_l9.split_mode = "random"
cfg.nr_cl_100k_1d8_l9.transductive = True
cfg.nr_cl_100k_1d8_l9.split_index = 0
cfg.nr_cl_100k_1d8_l9.feat_dim = 1
cfg.nr_cl_100k_1d8_l9.hidden_dim = 32
cfg.nr_cl_100k_1d8_l9.activate_fn = "torch.nn.ReLU()"
cfg.nr_cl_100k_1d8_l9.split = [0.6, 0.2, 0.2]
cfg.nr_cl_100k_1d8_l9.num_nodes = 92482

cfg.nr_cl_10k_1d8_l5.dataset_name = "CL-10K-1d8-L5"
cfg.nr_cl_10k_1d8_l5.format = "Network_repository"
cfg.nr_cl_10k_1d8_l5.task = "node"
cfg.nr_cl_10k_1d8_l5.task_type = "classification"
cfg.nr_cl_10k_1d8_l5.loss_fun = "cross_entropy"
cfg.nr_cl_10k_1d8_l5.task_dim = 5
cfg.nr_cl_10k_1d8_l5.split_mode = "random"
cfg.nr_cl_10k_1d8_l5.transductive = True
cfg.nr_cl_10k_1d8_l5.split_index = 0
cfg.nr_cl_10k_1d8_l5.feat_dim = 1
cfg.nr_cl_10k_1d8_l5.hidden_dim = 32
cfg.nr_cl_10k_1d8_l5.activate_fn = "torch.nn.ReLU()"
cfg.nr_cl_10k_1d8_l5.split = [0.6, 0.2, 0.2]
cfg.nr_cl_10k_1d8_l5.num_nodes = 10000

cfg.nr_cl_10m_1d8_l5.dataset_name = "CL-10M-1d8-L5"
cfg.nr_cl_10m_1d8_l5.format = "Network_repository"
cfg.nr_cl_10m_1d8_l5.task = "node"
cfg.nr_cl_10m_1d8_l5.task_type = "classification"
cfg.nr_cl_10m_1d8_l5.loss_fun = "cross_entropy"
cfg.nr_cl_10m_1d8_l5.task_dim = 5
cfg.nr_cl_10m_1d8_l5.split_mode = "random"
cfg.nr_cl_10m_1d8_l5.transductive = True
cfg.nr_cl_10m_1d8_l5.split_index = 0
cfg.nr_cl_10m_1d8_l5.feat_dim = 1
cfg.nr_cl_10m_1d8_l5.hidden_dim = 32
cfg.nr_cl_10m_1d8_l5.activate_fn = "torch.nn.ReLU()"
cfg.nr_cl_10m_1d8_l5.split = [0.6, 0.2, 0.2]
cfg.nr_cl_10m_1d8_l5.num_nodes = 10000000

cfg.nr_cox2.dataset_name = "COX2"
cfg.nr_cox2.format = "Network_repository"
cfg.nr_cox2.task = "node"
cfg.nr_cox2.task_type = "classification"
cfg.nr_cox2.loss_fun = "cross_entropy"
cfg.nr_cox2.task_dim = 35
cfg.nr_cox2.split_mode = "random"
cfg.nr_cox2.transductive = True
cfg.nr_cox2.split_index = 0
cfg.nr_cox2.feat_dim = 3
cfg.nr_cox2.hidden_dim = 32
cfg.nr_cox2.activate_fn = "torch.nn.ReLU()"
cfg.nr_cox2.split = [0.6, 0.2, 0.2]
cfg.nr_cox2.num_nodes = 19252

cfg.nr_dblp_v1.dataset_name = "DBLP-v1"
cfg.nr_dblp_v1.format = "Network_repository"
cfg.nr_dblp_v1.task = "node"
cfg.nr_dblp_v1.task_type = "classification"
cfg.nr_dblp_v1.loss_fun = "cross_entropy"
cfg.nr_dblp_v1.task_dim = 41324
cfg.nr_dblp_v1.split_mode = "random"
cfg.nr_dblp_v1.transductive = True
cfg.nr_dblp_v1.split_index = 0
cfg.nr_dblp_v1.feat_dim = 1
cfg.nr_dblp_v1.hidden_dim = 32
cfg.nr_dblp_v1.activate_fn = "torch.nn.ReLU()"
cfg.nr_dblp_v1.split = [0.6, 0.2, 0.2]
cfg.nr_dblp_v1.num_nodes = 203954

cfg.nr_dd.dataset_name = "DD"
cfg.nr_dd.format = "Network_repository"
cfg.nr_dd.task = "node"
cfg.nr_dd.task_type = "classification"
cfg.nr_dd.loss_fun = "cross_entropy"
cfg.nr_dd.task_dim = 89
cfg.nr_dd.split_mode = "random"
cfg.nr_dd.transductive = True
cfg.nr_dd.split_index = 0
cfg.nr_dd.feat_dim = 1
cfg.nr_dd.hidden_dim = 32
cfg.nr_dd.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd.split = [0.6, 0.2, 0.2]
cfg.nr_dd.num_nodes = 334925

cfg.nr_dd199.dataset_name = "DD199"
cfg.nr_dd199.format = "Network_repository"
cfg.nr_dd199.task = "node"
cfg.nr_dd199.task_type = "classification"
cfg.nr_dd199.loss_fun = "cross_entropy"
cfg.nr_dd199.task_dim = 20
cfg.nr_dd199.split_mode = "random"
cfg.nr_dd199.transductive = True
cfg.nr_dd199.split_index = 0
cfg.nr_dd199.feat_dim = 1
cfg.nr_dd199.hidden_dim = 32
cfg.nr_dd199.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd199.split = [0.6, 0.2, 0.2]
cfg.nr_dd199.num_nodes = 841

cfg.nr_dd21.dataset_name = "DD21"
cfg.nr_dd21.format = "Network_repository"
cfg.nr_dd21.task = "node"
cfg.nr_dd21.task_type = "classification"
cfg.nr_dd21.loss_fun = "cross_entropy"
cfg.nr_dd21.task_dim = 40
cfg.nr_dd21.split_mode = "random"
cfg.nr_dd21.transductive = True
cfg.nr_dd21.split_index = 0
cfg.nr_dd21.feat_dim = 1
cfg.nr_dd21.hidden_dim = 32
cfg.nr_dd21.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd21.split = [0.6, 0.2, 0.2]
cfg.nr_dd21.num_nodes = 5748

cfg.nr_dd242.dataset_name = "DD242"
cfg.nr_dd242.format = "Network_repository"
cfg.nr_dd242.task = "node"
cfg.nr_dd242.task_type = "classification"
cfg.nr_dd242.loss_fun = "cross_entropy"
cfg.nr_dd242.task_dim = 20
cfg.nr_dd242.split_mode = "random"
cfg.nr_dd242.transductive = True
cfg.nr_dd242.split_index = 0
cfg.nr_dd242.feat_dim = 1
cfg.nr_dd242.hidden_dim = 32
cfg.nr_dd242.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd242.split = [0.6, 0.2, 0.2]
cfg.nr_dd242.num_nodes = 1284

cfg.nr_dd244.dataset_name = "DD244"
cfg.nr_dd244.format = "Network_repository"
cfg.nr_dd244.task = "node"
cfg.nr_dd244.task_type = "classification"
cfg.nr_dd244.loss_fun = "cross_entropy"
cfg.nr_dd244.task_dim = 20
cfg.nr_dd244.split_mode = "random"
cfg.nr_dd244.transductive = True
cfg.nr_dd244.split_index = 0
cfg.nr_dd244.feat_dim = 1
cfg.nr_dd244.hidden_dim = 32
cfg.nr_dd244.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd244.split = [0.6, 0.2, 0.2]
cfg.nr_dd244.num_nodes = 291

cfg.nr_dd349.dataset_name = "DD349"
cfg.nr_dd349.format = "Network_repository"
cfg.nr_dd349.task = "node"
cfg.nr_dd349.task_type = "classification"
cfg.nr_dd349.loss_fun = "cross_entropy"
cfg.nr_dd349.task_dim = 20
cfg.nr_dd349.split_mode = "random"
cfg.nr_dd349.transductive = True
cfg.nr_dd349.split_index = 0
cfg.nr_dd349.feat_dim = 1
cfg.nr_dd349.hidden_dim = 32
cfg.nr_dd349.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd349.split = [0.6, 0.2, 0.2]
cfg.nr_dd349.num_nodes = 897

cfg.nr_dd497.dataset_name = "DD497"
cfg.nr_dd497.format = "Network_repository"
cfg.nr_dd497.task = "node"
cfg.nr_dd497.task_type = "classification"
cfg.nr_dd497.loss_fun = "cross_entropy"
cfg.nr_dd497.task_dim = 20
cfg.nr_dd497.split_mode = "random"
cfg.nr_dd497.transductive = True
cfg.nr_dd497.split_index = 0
cfg.nr_dd497.feat_dim = 1
cfg.nr_dd497.hidden_dim = 32
cfg.nr_dd497.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd497.split = [0.6, 0.2, 0.2]
cfg.nr_dd497.num_nodes = 903

cfg.nr_dd6.dataset_name = "DD6"
cfg.nr_dd6.format = "Network_repository"
cfg.nr_dd6.task = "node"
cfg.nr_dd6.task_type = "classification"
cfg.nr_dd6.loss_fun = "cross_entropy"
cfg.nr_dd6.task_dim = 20
cfg.nr_dd6.split_mode = "random"
cfg.nr_dd6.transductive = True
cfg.nr_dd6.split_index = 0
cfg.nr_dd6.feat_dim = 1
cfg.nr_dd6.hidden_dim = 32
cfg.nr_dd6.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd6.split = [0.6, 0.2, 0.2]
cfg.nr_dd6.num_nodes = 4152

cfg.nr_dd68.dataset_name = "DD68"
cfg.nr_dd68.format = "Network_repository"
cfg.nr_dd68.task = "node"
cfg.nr_dd68.task_type = "classification"
cfg.nr_dd68.loss_fun = "cross_entropy"
cfg.nr_dd68.task_dim = 20
cfg.nr_dd68.split_mode = "random"
cfg.nr_dd68.transductive = True
cfg.nr_dd68.split_index = 0
cfg.nr_dd68.feat_dim = 1
cfg.nr_dd68.hidden_dim = 32
cfg.nr_dd68.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd68.split = [0.6, 0.2, 0.2]
cfg.nr_dd68.num_nodes = 775

cfg.nr_dd687.dataset_name = "DD687"
cfg.nr_dd687.format = "Network_repository"
cfg.nr_dd687.task = "node"
cfg.nr_dd687.task_type = "classification"
cfg.nr_dd687.loss_fun = "cross_entropy"
cfg.nr_dd687.task_dim = 20
cfg.nr_dd687.split_mode = "random"
cfg.nr_dd687.transductive = True
cfg.nr_dd687.split_index = 0
cfg.nr_dd687.feat_dim = 1
cfg.nr_dd687.hidden_dim = 32
cfg.nr_dd687.activate_fn = "torch.nn.ReLU()"
cfg.nr_dd687.split = [0.6, 0.2, 0.2]
cfg.nr_dd687.num_nodes = 725

cfg.nr_dhfr.dataset_name = "DHFR"
cfg.nr_dhfr.format = "Network_repository"
cfg.nr_dhfr.task = "node"
cfg.nr_dhfr.task_type = "classification"
cfg.nr_dhfr.loss_fun = "cross_entropy"
cfg.nr_dhfr.task_dim = 53
cfg.nr_dhfr.split_mode = "random"
cfg.nr_dhfr.transductive = True
cfg.nr_dhfr.split_index = 0
cfg.nr_dhfr.feat_dim = 3
cfg.nr_dhfr.hidden_dim = 32
cfg.nr_dhfr.activate_fn = "torch.nn.ReLU()"
cfg.nr_dhfr.split = [0.6, 0.2, 0.2]
cfg.nr_dhfr.num_nodes = 32075

cfg.nr_enzymes.dataset_name = "ENZYMES"
cfg.nr_enzymes.format = "Network_repository"
cfg.nr_enzymes.task = "node"
cfg.nr_enzymes.task_type = "classification"
cfg.nr_enzymes.loss_fun = "cross_entropy"
cfg.nr_enzymes.task_dim = 3
cfg.nr_enzymes.split_mode = "random"
cfg.nr_enzymes.transductive = True
cfg.nr_enzymes.split_index = 0
cfg.nr_enzymes.feat_dim = 18
cfg.nr_enzymes.hidden_dim = 32
cfg.nr_enzymes.activate_fn = "torch.nn.ReLU()"
cfg.nr_enzymes.split = [0.6, 0.2, 0.2]
cfg.nr_enzymes.num_nodes = 19580

cfg.nr_enzymes118.dataset_name = "ENZYMES118"
cfg.nr_enzymes118.format = "Network_repository"
cfg.nr_enzymes118.task = "node"
cfg.nr_enzymes118.task_type = "classification"
cfg.nr_enzymes118.loss_fun = "cross_entropy"
cfg.nr_enzymes118.task_dim = 2
cfg.nr_enzymes118.split_mode = "random"
cfg.nr_enzymes118.transductive = True
cfg.nr_enzymes118.split_index = 0
cfg.nr_enzymes118.feat_dim = 1
cfg.nr_enzymes118.hidden_dim = 32
cfg.nr_enzymes118.activate_fn = "torch.nn.ReLU()"
cfg.nr_enzymes118.split = [0.6, 0.2, 0.2]
cfg.nr_enzymes118.num_nodes = 96

cfg.nr_enzymes123.dataset_name = "ENZYMES123"
cfg.nr_enzymes123.format = "Network_repository"
cfg.nr_enzymes123.task = "node"
cfg.nr_enzymes123.task_type = "classification"
cfg.nr_enzymes123.loss_fun = "cross_entropy"
cfg.nr_enzymes123.task_dim = 2
cfg.nr_enzymes123.split_mode = "random"
cfg.nr_enzymes123.transductive = True
cfg.nr_enzymes123.split_index = 0
cfg.nr_enzymes123.feat_dim = 1
cfg.nr_enzymes123.hidden_dim = 32
cfg.nr_enzymes123.activate_fn = "torch.nn.ReLU()"
cfg.nr_enzymes123.split = [0.6, 0.2, 0.2]
cfg.nr_enzymes123.num_nodes = 90

cfg.nr_enzymes295.dataset_name = "ENZYMES295"
cfg.nr_enzymes295.format = "Network_repository"
cfg.nr_enzymes295.task = "node"
cfg.nr_enzymes295.task_type = "classification"
cfg.nr_enzymes295.loss_fun = "cross_entropy"
cfg.nr_enzymes295.task_dim = 2
cfg.nr_enzymes295.split_mode = "random"
cfg.nr_enzymes295.transductive = True
cfg.nr_enzymes295.split_index = 0
cfg.nr_enzymes295.feat_dim = 1
cfg.nr_enzymes295.hidden_dim = 32
cfg.nr_enzymes295.activate_fn = "torch.nn.ReLU()"
cfg.nr_enzymes295.split = [0.6, 0.2, 0.2]
cfg.nr_enzymes295.num_nodes = 124

cfg.nr_enzymes296.dataset_name = "ENZYMES296"
cfg.nr_enzymes296.format = "Network_repository"
cfg.nr_enzymes296.task = "node"
cfg.nr_enzymes296.task_type = "classification"
cfg.nr_enzymes296.loss_fun = "cross_entropy"
cfg.nr_enzymes296.task_dim = 2
cfg.nr_enzymes296.split_mode = "random"
cfg.nr_enzymes296.transductive = True
cfg.nr_enzymes296.split_index = 0
cfg.nr_enzymes296.feat_dim = 1
cfg.nr_enzymes296.hidden_dim = 32
cfg.nr_enzymes296.activate_fn = "torch.nn.ReLU()"
cfg.nr_enzymes296.split = [0.6, 0.2, 0.2]
cfg.nr_enzymes296.num_nodes = 126

cfg.nr_enzymes297.dataset_name = "ENZYMES297"
cfg.nr_enzymes297.format = "Network_repository"
cfg.nr_enzymes297.task = "node"
cfg.nr_enzymes297.task_type = "classification"
cfg.nr_enzymes297.loss_fun = "cross_entropy"
cfg.nr_enzymes297.task_dim = 2
cfg.nr_enzymes297.split_mode = "random"
cfg.nr_enzymes297.transductive = True
cfg.nr_enzymes297.split_index = 0
cfg.nr_enzymes297.feat_dim = 1
cfg.nr_enzymes297.hidden_dim = 32
cfg.nr_enzymes297.activate_fn = "torch.nn.ReLU()"
cfg.nr_enzymes297.split = [0.6, 0.2, 0.2]
cfg.nr_enzymes297.num_nodes = 122

cfg.nr_enzymes8.dataset_name = "ENZYMES8"
cfg.nr_enzymes8.format = "Network_repository"
cfg.nr_enzymes8.task = "node"
cfg.nr_enzymes8.task_type = "classification"
cfg.nr_enzymes8.loss_fun = "cross_entropy"
cfg.nr_enzymes8.task_dim = 2
cfg.nr_enzymes8.split_mode = "random"
cfg.nr_enzymes8.transductive = True
cfg.nr_enzymes8.split_index = 0
cfg.nr_enzymes8.feat_dim = 1
cfg.nr_enzymes8.hidden_dim = 32
cfg.nr_enzymes8.activate_fn = "torch.nn.ReLU()"
cfg.nr_enzymes8.split = [0.6, 0.2, 0.2]
cfg.nr_enzymes8.num_nodes = 88

cfg.nr_er_avgdeg10_100k_l2.dataset_name = "ER-AvgDeg10-100K-L2"
cfg.nr_er_avgdeg10_100k_l2.format = "Network_repository"
cfg.nr_er_avgdeg10_100k_l2.task = "node"
cfg.nr_er_avgdeg10_100k_l2.task_type = "classification"
cfg.nr_er_avgdeg10_100k_l2.loss_fun = "cross_entropy"
cfg.nr_er_avgdeg10_100k_l2.task_dim = 2
cfg.nr_er_avgdeg10_100k_l2.split_mode = "random"
cfg.nr_er_avgdeg10_100k_l2.transductive = True
cfg.nr_er_avgdeg10_100k_l2.split_index = 0
cfg.nr_er_avgdeg10_100k_l2.feat_dim = 1
cfg.nr_er_avgdeg10_100k_l2.hidden_dim = 32
cfg.nr_er_avgdeg10_100k_l2.activate_fn = "torch.nn.ReLU()"
cfg.nr_er_avgdeg10_100k_l2.split = [0.6, 0.2, 0.2]
cfg.nr_er_avgdeg10_100k_l2.num_nodes = 99997

cfg.nr_er_avgdeg10_100k_l5.dataset_name = "ER-AvgDeg10-100K-L5"
cfg.nr_er_avgdeg10_100k_l5.format = "Network_repository"
cfg.nr_er_avgdeg10_100k_l5.task = "node"
cfg.nr_er_avgdeg10_100k_l5.task_type = "classification"
cfg.nr_er_avgdeg10_100k_l5.loss_fun = "cross_entropy"
cfg.nr_er_avgdeg10_100k_l5.task_dim = 5
cfg.nr_er_avgdeg10_100k_l5.split_mode = "random"
cfg.nr_er_avgdeg10_100k_l5.transductive = True
cfg.nr_er_avgdeg10_100k_l5.split_index = 0
cfg.nr_er_avgdeg10_100k_l5.feat_dim = 1
cfg.nr_er_avgdeg10_100k_l5.hidden_dim = 32
cfg.nr_er_avgdeg10_100k_l5.activate_fn = "torch.nn.ReLU()"
cfg.nr_er_avgdeg10_100k_l5.split = [0.6, 0.2, 0.2]
cfg.nr_er_avgdeg10_100k_l5.num_nodes = 99997

cfg.nr_er_avgdeg10_1m_l2.dataset_name = "ER-AvgDeg10-1M-L2"
cfg.nr_er_avgdeg10_1m_l2.format = "Network_repository"
cfg.nr_er_avgdeg10_1m_l2.task = "node"
cfg.nr_er_avgdeg10_1m_l2.task_type = "classification"
cfg.nr_er_avgdeg10_1m_l2.loss_fun = "cross_entropy"
cfg.nr_er_avgdeg10_1m_l2.task_dim = 2
cfg.nr_er_avgdeg10_1m_l2.split_mode = "random"
cfg.nr_er_avgdeg10_1m_l2.transductive = True
cfg.nr_er_avgdeg10_1m_l2.split_index = 0
cfg.nr_er_avgdeg10_1m_l2.feat_dim = 1
cfg.nr_er_avgdeg10_1m_l2.hidden_dim = 32
cfg.nr_er_avgdeg10_1m_l2.activate_fn = "torch.nn.ReLU()"
cfg.nr_er_avgdeg10_1m_l2.split = [0.6, 0.2, 0.2]
cfg.nr_er_avgdeg10_1m_l2.num_nodes = 999944

cfg.nr_er_avgdeg10_1m_l5.dataset_name = "ER-AvgDeg10-1M-L5"
cfg.nr_er_avgdeg10_1m_l5.format = "Network_repository"
cfg.nr_er_avgdeg10_1m_l5.task = "node"
cfg.nr_er_avgdeg10_1m_l5.task_type = "classification"
cfg.nr_er_avgdeg10_1m_l5.loss_fun = "cross_entropy"
cfg.nr_er_avgdeg10_1m_l5.task_dim = 5
cfg.nr_er_avgdeg10_1m_l5.split_mode = "random"
cfg.nr_er_avgdeg10_1m_l5.transductive = True
cfg.nr_er_avgdeg10_1m_l5.split_index = 0
cfg.nr_er_avgdeg10_1m_l5.feat_dim = 1
cfg.nr_er_avgdeg10_1m_l5.hidden_dim = 32
cfg.nr_er_avgdeg10_1m_l5.activate_fn = "torch.nn.ReLU()"
cfg.nr_er_avgdeg10_1m_l5.split = [0.6, 0.2, 0.2]
cfg.nr_er_avgdeg10_1m_l5.num_nodes = 999944

cfg.nr_kki.dataset_name = "KKI"
cfg.nr_kki.format = "Network_repository"
cfg.nr_kki.task = "node"
cfg.nr_kki.task_type = "classification"
cfg.nr_kki.loss_fun = "cross_entropy"
cfg.nr_kki.task_dim = 189
cfg.nr_kki.split_mode = "random"
cfg.nr_kki.transductive = True
cfg.nr_kki.split_index = 0
cfg.nr_kki.feat_dim = 1
cfg.nr_kki.hidden_dim = 32
cfg.nr_kki.activate_fn = "torch.nn.ReLU()"
cfg.nr_kki.split = [0.6, 0.2, 0.2]
cfg.nr_kki.num_nodes = 2238

cfg.nr_msrc_21.dataset_name = "MSRC-21"
cfg.nr_msrc_21.format = "Network_repository"
cfg.nr_msrc_21.task = "node"
cfg.nr_msrc_21.task_type = "classification"
cfg.nr_msrc_21.loss_fun = "cross_entropy"
cfg.nr_msrc_21.task_dim = 24
cfg.nr_msrc_21.split_mode = "random"
cfg.nr_msrc_21.transductive = True
cfg.nr_msrc_21.split_index = 0
cfg.nr_msrc_21.feat_dim = 1
cfg.nr_msrc_21.hidden_dim = 32
cfg.nr_msrc_21.activate_fn = "torch.nn.ReLU()"
cfg.nr_msrc_21.split = [0.6, 0.2, 0.2]
cfg.nr_msrc_21.num_nodes = 43644

cfg.nr_msrc_21c.dataset_name = "MSRC-21C"
cfg.nr_msrc_21c.format = "Network_repository"
cfg.nr_msrc_21c.task = "node"
cfg.nr_msrc_21c.task_type = "classification"
cfg.nr_msrc_21c.loss_fun = "cross_entropy"
cfg.nr_msrc_21c.task_dim = 22
cfg.nr_msrc_21c.split_mode = "random"
cfg.nr_msrc_21c.transductive = True
cfg.nr_msrc_21c.split_index = 0
cfg.nr_msrc_21c.feat_dim = 1
cfg.nr_msrc_21c.hidden_dim = 32
cfg.nr_msrc_21c.activate_fn = "torch.nn.ReLU()"
cfg.nr_msrc_21c.split = [0.6, 0.2, 0.2]
cfg.nr_msrc_21c.num_nodes = 8418

cfg.nr_msrc_9.dataset_name = "MSRC-9"
cfg.nr_msrc_9.format = "Network_repository"
cfg.nr_msrc_9.task = "node"
cfg.nr_msrc_9.task_type = "classification"
cfg.nr_msrc_9.loss_fun = "cross_entropy"
cfg.nr_msrc_9.task_dim = 10
cfg.nr_msrc_9.split_mode = "random"
cfg.nr_msrc_9.transductive = True
cfg.nr_msrc_9.split_index = 0
cfg.nr_msrc_9.feat_dim = 1
cfg.nr_msrc_9.hidden_dim = 32
cfg.nr_msrc_9.activate_fn = "torch.nn.ReLU()"
cfg.nr_msrc_9.split = [0.6, 0.2, 0.2]
cfg.nr_msrc_9.num_nodes = 8968

cfg.nr_mutagenicity.dataset_name = "Mutagenicity"
cfg.nr_mutagenicity.format = "Network_repository"
cfg.nr_mutagenicity.task = "node"
cfg.nr_mutagenicity.task_type = "classification"
cfg.nr_mutagenicity.loss_fun = "cross_entropy"
cfg.nr_mutagenicity.task_dim = 13
cfg.nr_mutagenicity.split_mode = "random"
cfg.nr_mutagenicity.transductive = True
cfg.nr_mutagenicity.split_index = 0
cfg.nr_mutagenicity.feat_dim = 1
cfg.nr_mutagenicity.hidden_dim = 32
cfg.nr_mutagenicity.activate_fn = "torch.nn.ReLU()"
cfg.nr_mutagenicity.split = [0.6, 0.2, 0.2]
cfg.nr_mutagenicity.num_nodes = 131488

cfg.nr_nci1.dataset_name = "NCI1"
cfg.nr_nci1.format = "Network_repository"
cfg.nr_nci1.task = "node"
cfg.nr_nci1.task_type = "classification"
cfg.nr_nci1.loss_fun = "cross_entropy"
cfg.nr_nci1.task_dim = 122750
cfg.nr_nci1.split_mode = "random"
cfg.nr_nci1.transductive = True
cfg.nr_nci1.split_index = 0
cfg.nr_nci1.feat_dim = 1
cfg.nr_nci1.hidden_dim = 32
cfg.nr_nci1.activate_fn = "torch.nn.ReLU()"
cfg.nr_nci1.split = [0.6, 0.2, 0.2]
cfg.nr_nci1.num_nodes = 122747

cfg.nr_nci109.dataset_name = "NCI109"
cfg.nr_nci109.format = "Network_repository"
cfg.nr_nci109.task = "node"
cfg.nr_nci109.task_type = "classification"
cfg.nr_nci109.loss_fun = "cross_entropy"
cfg.nr_nci109.task_dim = 38
cfg.nr_nci109.split_mode = "random"
cfg.nr_nci109.transductive = True
cfg.nr_nci109.split_index = 0
cfg.nr_nci109.feat_dim = 1
cfg.nr_nci109.hidden_dim = 32
cfg.nr_nci109.activate_fn = "torch.nn.ReLU()"
cfg.nr_nci109.split = [0.6, 0.2, 0.2]
cfg.nr_nci109.num_nodes = 122494

cfg.nr_ohsu.dataset_name = "OHSU"
cfg.nr_ohsu.format = "Network_repository"
cfg.nr_ohsu.task = "node"
cfg.nr_ohsu.task_type = "classification"
cfg.nr_ohsu.loss_fun = "cross_entropy"
cfg.nr_ohsu.task_dim = 189
cfg.nr_ohsu.split_mode = "random"
cfg.nr_ohsu.transductive = True
cfg.nr_ohsu.split_index = 0
cfg.nr_ohsu.feat_dim = 1
cfg.nr_ohsu.hidden_dim = 32
cfg.nr_ohsu.activate_fn = "torch.nn.ReLU()"
cfg.nr_ohsu.split = [0.6, 0.2, 0.2]
cfg.nr_ohsu.num_nodes = 6479

cfg.nr_plc_40_30_l5.dataset_name = "PLC-40-30-L5"
cfg.nr_plc_40_30_l5.format = "Network_repository"
cfg.nr_plc_40_30_l5.task = "node"
cfg.nr_plc_40_30_l5.task_type = "classification"
cfg.nr_plc_40_30_l5.loss_fun = "cross_entropy"
cfg.nr_plc_40_30_l5.task_dim = 5
cfg.nr_plc_40_30_l5.split_mode = "random"
cfg.nr_plc_40_30_l5.transductive = True
cfg.nr_plc_40_30_l5.split_index = 0
cfg.nr_plc_40_30_l5.feat_dim = 1
cfg.nr_plc_40_30_l5.hidden_dim = 32
cfg.nr_plc_40_30_l5.activate_fn = "torch.nn.ReLU()"
cfg.nr_plc_40_30_l5.split = [0.6, 0.2, 0.2]
cfg.nr_plc_40_30_l5.num_nodes = 11025

cfg.nr_plc_60_30_l2.dataset_name = "PLC-60-30-L2"
cfg.nr_plc_60_30_l2.format = "Network_repository"
cfg.nr_plc_60_30_l2.task = "node"
cfg.nr_plc_60_30_l2.task_type = "classification"
cfg.nr_plc_60_30_l2.loss_fun = "cross_entropy"
cfg.nr_plc_60_30_l2.task_dim = 2
cfg.nr_plc_60_30_l2.split_mode = "random"
cfg.nr_plc_60_30_l2.transductive = True
cfg.nr_plc_60_30_l2.split_index = 0
cfg.nr_plc_60_30_l2.feat_dim = 1
cfg.nr_plc_60_30_l2.hidden_dim = 32
cfg.nr_plc_60_30_l2.activate_fn = "torch.nn.ReLU()"
cfg.nr_plc_60_30_l2.split = [0.6, 0.2, 0.2]
cfg.nr_plc_60_30_l2.num_nodes = 117572

cfg.nr_proteins_full.dataset_name = "PROTEINS-full"
cfg.nr_proteins_full.format = "Network_repository"
cfg.nr_proteins_full.task = "node"
cfg.nr_proteins_full.task_type = "classification"
cfg.nr_proteins_full.loss_fun = "cross_entropy"
cfg.nr_proteins_full.task_dim = 2
cfg.nr_proteins_full.split_mode = "random"
cfg.nr_proteins_full.transductive = True
cfg.nr_proteins_full.split_index = 0
cfg.nr_proteins_full.feat_dim = 29
cfg.nr_proteins_full.hidden_dim = 32
cfg.nr_proteins_full.activate_fn = "torch.nn.ReLU()"
cfg.nr_proteins_full.split = [0.6, 0.2, 0.2]
cfg.nr_proteins_full.num_nodes = 43471

cfg.nr_ptc_fm.dataset_name = "PTC-FM"
cfg.nr_ptc_fm.format = "Network_repository"
cfg.nr_ptc_fm.task = "node"
cfg.nr_ptc_fm.task_type = "classification"
cfg.nr_ptc_fm.loss_fun = "cross_entropy"
cfg.nr_ptc_fm.task_dim = 17
cfg.nr_ptc_fm.split_mode = "random"
cfg.nr_ptc_fm.transductive = True
cfg.nr_ptc_fm.split_index = 0
cfg.nr_ptc_fm.feat_dim = 1
cfg.nr_ptc_fm.hidden_dim = 32
cfg.nr_ptc_fm.activate_fn = "torch.nn.ReLU()"
cfg.nr_ptc_fm.split = [0.6, 0.2, 0.2]
cfg.nr_ptc_fm.num_nodes = 4925

cfg.nr_ptc_fr.dataset_name = "PTC-FR"
cfg.nr_ptc_fr.format = "Network_repository"
cfg.nr_ptc_fr.task = "node"
cfg.nr_ptc_fr.task_type = "classification"
cfg.nr_ptc_fr.loss_fun = "cross_entropy"
cfg.nr_ptc_fr.task_dim = 18
cfg.nr_ptc_fr.split_mode = "random"
cfg.nr_ptc_fr.transductive = True
cfg.nr_ptc_fr.split_index = 0
cfg.nr_ptc_fr.feat_dim = 1
cfg.nr_ptc_fr.hidden_dim = 32
cfg.nr_ptc_fr.activate_fn = "torch.nn.ReLU()"
cfg.nr_ptc_fr.split = [0.6, 0.2, 0.2]
cfg.nr_ptc_fr.num_nodes = 5110

cfg.nr_ptc_mm.dataset_name = "PTC-MM"
cfg.nr_ptc_mm.format = "Network_repository"
cfg.nr_ptc_mm.task = "node"
cfg.nr_ptc_mm.task_type = "classification"
cfg.nr_ptc_mm.loss_fun = "cross_entropy"
cfg.nr_ptc_mm.task_dim = 19
cfg.nr_ptc_mm.split_mode = "random"
cfg.nr_ptc_mm.transductive = True
cfg.nr_ptc_mm.split_index = 0
cfg.nr_ptc_mm.feat_dim = 1
cfg.nr_ptc_mm.hidden_dim = 32
cfg.nr_ptc_mm.activate_fn = "torch.nn.ReLU()"
cfg.nr_ptc_mm.split = [0.6, 0.2, 0.2]
cfg.nr_ptc_mm.num_nodes = 4695

cfg.nr_ptc_mr.dataset_name = "PTC-MR"
cfg.nr_ptc_mr.format = "Network_repository"
cfg.nr_ptc_mr.task = "node"
cfg.nr_ptc_mr.task_type = "classification"
cfg.nr_ptc_mr.loss_fun = "cross_entropy"
cfg.nr_ptc_mr.task_dim = 17
cfg.nr_ptc_mr.split_mode = "random"
cfg.nr_ptc_mr.transductive = True
cfg.nr_ptc_mr.split_index = 0
cfg.nr_ptc_mr.feat_dim = 1
cfg.nr_ptc_mr.hidden_dim = 32
cfg.nr_ptc_mr.activate_fn = "torch.nn.ReLU()"
cfg.nr_ptc_mr.split = [0.6, 0.2, 0.2]
cfg.nr_ptc_mr.num_nodes = 4915

cfg.nr_peking_1.dataset_name = "Peking-1"
cfg.nr_peking_1.format = "Network_repository"
cfg.nr_peking_1.task = "node"
cfg.nr_peking_1.task_type = "classification"
cfg.nr_peking_1.loss_fun = "cross_entropy"
cfg.nr_peking_1.task_dim = 189
cfg.nr_peking_1.split_mode = "random"
cfg.nr_peking_1.transductive = True
cfg.nr_peking_1.split_index = 0
cfg.nr_peking_1.feat_dim = 1
cfg.nr_peking_1.hidden_dim = 32
cfg.nr_peking_1.activate_fn = "torch.nn.ReLU()"
cfg.nr_peking_1.split = [0.6, 0.2, 0.2]
cfg.nr_peking_1.num_nodes = 3341

cfg.nr_pubmed.dataset_name = "PubMed"
cfg.nr_pubmed.format = "Network_repository"
cfg.nr_pubmed.task = "node"
cfg.nr_pubmed.task_type = "classification"
cfg.nr_pubmed.loss_fun = "cross_entropy"
cfg.nr_pubmed.task_dim = 3
cfg.nr_pubmed.split_mode = "random"
cfg.nr_pubmed.transductive = True
cfg.nr_pubmed.split_index = 0
cfg.nr_pubmed.feat_dim = 1
cfg.nr_pubmed.hidden_dim = 32
cfg.nr_pubmed.activate_fn = "torch.nn.ReLU()"
cfg.nr_pubmed.split = [0.6, 0.2, 0.2]
cfg.nr_pubmed.num_nodes = 20061360

cfg.nr_sw_10000_6_0d3_l2.dataset_name = "SW-10000-6-0d3-L2"
cfg.nr_sw_10000_6_0d3_l2.format = "Network_repository"
cfg.nr_sw_10000_6_0d3_l2.task = "node"
cfg.nr_sw_10000_6_0d3_l2.task_type = "classification"
cfg.nr_sw_10000_6_0d3_l2.loss_fun = "cross_entropy"
cfg.nr_sw_10000_6_0d3_l2.task_dim = 2
cfg.nr_sw_10000_6_0d3_l2.split_mode = "random"
cfg.nr_sw_10000_6_0d3_l2.transductive = True
cfg.nr_sw_10000_6_0d3_l2.split_index = 0
cfg.nr_sw_10000_6_0d3_l2.feat_dim = 1
cfg.nr_sw_10000_6_0d3_l2.hidden_dim = 32
cfg.nr_sw_10000_6_0d3_l2.activate_fn = "torch.nn.ReLU()"
cfg.nr_sw_10000_6_0d3_l2.split = [0.6, 0.2, 0.2]
cfg.nr_sw_10000_6_0d3_l2.num_nodes = 10000

cfg.nr_sw_10000_6_0d3_l5.dataset_name = "SW-10000-6-0d3-L5"
cfg.nr_sw_10000_6_0d3_l5.format = "Network_repository"
cfg.nr_sw_10000_6_0d3_l5.task = "node"
cfg.nr_sw_10000_6_0d3_l5.task_type = "classification"
cfg.nr_sw_10000_6_0d3_l5.loss_fun = "cross_entropy"
cfg.nr_sw_10000_6_0d3_l5.task_dim = 5
cfg.nr_sw_10000_6_0d3_l5.split_mode = "random"
cfg.nr_sw_10000_6_0d3_l5.transductive = True
cfg.nr_sw_10000_6_0d3_l5.split_index = 0
cfg.nr_sw_10000_6_0d3_l5.feat_dim = 1
cfg.nr_sw_10000_6_0d3_l5.hidden_dim = 32
cfg.nr_sw_10000_6_0d3_l5.activate_fn = "torch.nn.ReLU()"
cfg.nr_sw_10000_6_0d3_l5.split = [0.6, 0.2, 0.2]
cfg.nr_sw_10000_6_0d3_l5.num_nodes = 10000

cfg.nr_synthetic.dataset_name = "SYNTHETIC"
cfg.nr_synthetic.format = "Network_repository"
cfg.nr_synthetic.task = "node"
cfg.nr_synthetic.task_type = "classification"
cfg.nr_synthetic.loss_fun = "cross_entropy"
cfg.nr_synthetic.task_dim = 8
cfg.nr_synthetic.split_mode = "random"
cfg.nr_synthetic.transductive = True
cfg.nr_synthetic.split_index = 0
cfg.nr_synthetic.feat_dim = 1
cfg.nr_synthetic.hidden_dim = 32
cfg.nr_synthetic.activate_fn = "torch.nn.ReLU()"
cfg.nr_synthetic.split = [0.6, 0.2, 0.2]
cfg.nr_synthetic.num_nodes = 30000

cfg.nr_terroristrel.dataset_name = "TerroristRel"
cfg.nr_terroristrel.format = "Network_repository"
cfg.nr_terroristrel.task = "node"
cfg.nr_terroristrel.task_type = "classification"
cfg.nr_terroristrel.loss_fun = "cross_entropy"
cfg.nr_terroristrel.task_dim = 2
cfg.nr_terroristrel.split_mode = "random"
cfg.nr_terroristrel.transductive = True
cfg.nr_terroristrel.split_index = 0
cfg.nr_terroristrel.feat_dim = 1
cfg.nr_terroristrel.hidden_dim = 32
cfg.nr_terroristrel.activate_fn = "torch.nn.ReLU()"
cfg.nr_terroristrel.split = [0.6, 0.2, 0.2]
cfg.nr_terroristrel.num_nodes = 881

cfg.nr_tox21_ahr.dataset_name = "Tox21-AHR"
cfg.nr_tox21_ahr.format = "Network_repository"
cfg.nr_tox21_ahr.task = "node"
cfg.nr_tox21_ahr.task_type = "classification"
cfg.nr_tox21_ahr.loss_fun = "cross_entropy"
cfg.nr_tox21_ahr.task_dim = 48
cfg.nr_tox21_ahr.split_mode = "random"
cfg.nr_tox21_ahr.transductive = True
cfg.nr_tox21_ahr.split_index = 0
cfg.nr_tox21_ahr.feat_dim = 1
cfg.nr_tox21_ahr.hidden_dim = 32
cfg.nr_tox21_ahr.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_ahr.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_ahr.num_nodes = 147772

cfg.nr_tox21_ar.dataset_name = "Tox21-AR"
cfg.nr_tox21_ar.format = "Network_repository"
cfg.nr_tox21_ar.task = "node"
cfg.nr_tox21_ar.task_type = "classification"
cfg.nr_tox21_ar.loss_fun = "cross_entropy"
cfg.nr_tox21_ar.task_dim = 48
cfg.nr_tox21_ar.split_mode = "random"
cfg.nr_tox21_ar.transductive = True
cfg.nr_tox21_ar.split_index = 0
cfg.nr_tox21_ar.feat_dim = 1
cfg.nr_tox21_ar.hidden_dim = 32
cfg.nr_tox21_ar.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_ar.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_ar.num_nodes = 172175

cfg.nr_tox21_ar_lbd.dataset_name = "Tox21-AR-LBD"
cfg.nr_tox21_ar_lbd.format = "Network_repository"
cfg.nr_tox21_ar_lbd.task = "node"
cfg.nr_tox21_ar_lbd.task_type = "classification"
cfg.nr_tox21_ar_lbd.loss_fun = "cross_entropy"
cfg.nr_tox21_ar_lbd.task_dim = 47
cfg.nr_tox21_ar_lbd.split_mode = "random"
cfg.nr_tox21_ar_lbd.transductive = True
cfg.nr_tox21_ar_lbd.split_index = 0
cfg.nr_tox21_ar_lbd.feat_dim = 1
cfg.nr_tox21_ar_lbd.hidden_dim = 32
cfg.nr_tox21_ar_lbd.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_ar_lbd.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_ar_lbd.num_nodes = 152773

cfg.nr_tox21_are.dataset_name = "Tox21-ARE"
cfg.nr_tox21_are.format = "Network_repository"
cfg.nr_tox21_are.task = "node"
cfg.nr_tox21_are.task_type = "classification"
cfg.nr_tox21_are.loss_fun = "cross_entropy"
cfg.nr_tox21_are.task_dim = 45
cfg.nr_tox21_are.split_mode = "random"
cfg.nr_tox21_are.transductive = True
cfg.nr_tox21_are.split_index = 0
cfg.nr_tox21_are.feat_dim = 1
cfg.nr_tox21_are.hidden_dim = 32
cfg.nr_tox21_are.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_are.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_are.num_nodes = 116670

cfg.nr_tox21_atad5.dataset_name = "Tox21-ATAD5"
cfg.nr_tox21_atad5.format = "Network_repository"
cfg.nr_tox21_atad5.task = "node"
cfg.nr_tox21_atad5.task_type = "classification"
cfg.nr_tox21_atad5.loss_fun = "cross_entropy"
cfg.nr_tox21_atad5.task_dim = 162650
cfg.nr_tox21_atad5.split_mode = "random"
cfg.nr_tox21_atad5.transductive = True
cfg.nr_tox21_atad5.split_index = 0
cfg.nr_tox21_atad5.feat_dim = 1
cfg.nr_tox21_atad5.hidden_dim = 32
cfg.nr_tox21_atad5.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_atad5.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_atad5.num_nodes = 162647

cfg.nr_tox21_er.dataset_name = "Tox21-ER"
cfg.nr_tox21_er.format = "Network_repository"
cfg.nr_tox21_er.task = "node"
cfg.nr_tox21_er.task_type = "classification"
cfg.nr_tox21_er.loss_fun = "cross_entropy"
cfg.nr_tox21_er.task_dim = 47
cfg.nr_tox21_er.split_mode = "random"
cfg.nr_tox21_er.transductive = True
cfg.nr_tox21_er.split_index = 0
cfg.nr_tox21_er.feat_dim = 1
cfg.nr_tox21_er.hidden_dim = 32
cfg.nr_tox21_er.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_er.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_er.num_nodes = 135276

cfg.nr_tox21_er_lbd.dataset_name = "Tox21-ER-LBD"
cfg.nr_tox21_er_lbd.format = "Network_repository"
cfg.nr_tox21_er_lbd.task = "node"
cfg.nr_tox21_er_lbd.task_type = "classification"
cfg.nr_tox21_er_lbd.loss_fun = "cross_entropy"
cfg.nr_tox21_er_lbd.task_dim = 47
cfg.nr_tox21_er_lbd.split_mode = "random"
cfg.nr_tox21_er_lbd.transductive = True
cfg.nr_tox21_er_lbd.split_index = 0
cfg.nr_tox21_er_lbd.feat_dim = 1
cfg.nr_tox21_er_lbd.hidden_dim = 32
cfg.nr_tox21_er_lbd.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_er_lbd.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_er_lbd.num_nodes = 158058

cfg.nr_tox21_hse.dataset_name = "Tox21-HSE"
cfg.nr_tox21_hse.format = "Network_repository"
cfg.nr_tox21_hse.task = "node"
cfg.nr_tox21_hse.task_type = "classification"
cfg.nr_tox21_hse.loss_fun = "cross_entropy"
cfg.nr_tox21_hse.task_dim = 46
cfg.nr_tox21_hse.split_mode = "random"
cfg.nr_tox21_hse.transductive = True
cfg.nr_tox21_hse.split_index = 0
cfg.nr_tox21_hse.feat_dim = 1
cfg.nr_tox21_hse.hidden_dim = 32
cfg.nr_tox21_hse.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_hse.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_hse.num_nodes = 136239

cfg.nr_tox21_mmp.dataset_name = "Tox21-MMP"
cfg.nr_tox21_mmp.format = "Network_repository"
cfg.nr_tox21_mmp.task = "node"
cfg.nr_tox21_mmp.task_type = "classification"
cfg.nr_tox21_mmp.loss_fun = "cross_entropy"
cfg.nr_tox21_mmp.task_dim = 46
cfg.nr_tox21_mmp.split_mode = "random"
cfg.nr_tox21_mmp.transductive = True
cfg.nr_tox21_mmp.split_index = 0
cfg.nr_tox21_mmp.feat_dim = 1
cfg.nr_tox21_mmp.hidden_dim = 32
cfg.nr_tox21_mmp.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_mmp.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_mmp.num_nodes = 127998

cfg.nr_tox21_ppar_gamma.dataset_name = "Tox21-PPAR-gamma"
cfg.nr_tox21_ppar_gamma.format = "Network_repository"
cfg.nr_tox21_ppar_gamma.task = "node"
cfg.nr_tox21_ppar_gamma.task_type = "classification"
cfg.nr_tox21_ppar_gamma.loss_fun = "cross_entropy"
cfg.nr_tox21_ppar_gamma.task_dim = 45
cfg.nr_tox21_ppar_gamma.split_mode = "random"
cfg.nr_tox21_ppar_gamma.transductive = True
cfg.nr_tox21_ppar_gamma.split_index = 0
cfg.nr_tox21_ppar_gamma.feat_dim = 1
cfg.nr_tox21_ppar_gamma.hidden_dim = 32
cfg.nr_tox21_ppar_gamma.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_ppar_gamma.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_ppar_gamma.num_nodes = 140999

cfg.nr_tox21_aromatase.dataset_name = "Tox21-aromatase"
cfg.nr_tox21_aromatase.format = "Network_repository"
cfg.nr_tox21_aromatase.task = "node"
cfg.nr_tox21_aromatase.task_type = "classification"
cfg.nr_tox21_aromatase.loss_fun = "cross_entropy"
cfg.nr_tox21_aromatase.task_dim = 45
cfg.nr_tox21_aromatase.split_mode = "random"
cfg.nr_tox21_aromatase.transductive = True
cfg.nr_tox21_aromatase.split_index = 0
cfg.nr_tox21_aromatase.feat_dim = 1
cfg.nr_tox21_aromatase.hidden_dim = 32
cfg.nr_tox21_aromatase.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_aromatase.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_aromatase.num_nodes = 126483

cfg.nr_tox21_p53.dataset_name = "Tox21-p53"
cfg.nr_tox21_p53.format = "Network_repository"
cfg.nr_tox21_p53.task = "node"
cfg.nr_tox21_p53.task_type = "classification"
cfg.nr_tox21_p53.loss_fun = "cross_entropy"
cfg.nr_tox21_p53.task_dim = 46
cfg.nr_tox21_p53.split_mode = "random"
cfg.nr_tox21_p53.transductive = True
cfg.nr_tox21_p53.split_index = 0
cfg.nr_tox21_p53.feat_dim = 1
cfg.nr_tox21_p53.hidden_dim = 32
cfg.nr_tox21_p53.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_p53.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_p53.num_nodes = 153563

cfg.nr_tox21_p53.dataset_name = "Tox21_p53"
cfg.nr_tox21_p53.format = "Network_repository"
cfg.nr_tox21_p53.task = "node"
cfg.nr_tox21_p53.task_type = "classification"
cfg.nr_tox21_p53.loss_fun = "cross_entropy"
cfg.nr_tox21_p53.task_dim = 46
cfg.nr_tox21_p53.split_mode = "random"
cfg.nr_tox21_p53.transductive = True
cfg.nr_tox21_p53.split_index = 0
cfg.nr_tox21_p53.feat_dim = 1
cfg.nr_tox21_p53.hidden_dim = 32
cfg.nr_tox21_p53.activate_fn = "torch.nn.ReLU()"
cfg.nr_tox21_p53.split = [0.6, 0.2, 0.2]
cfg.nr_tox21_p53.num_nodes = 153563

cfg.nr_cora.dataset_name = "cora"
cfg.nr_cora.format = "Network_repository"
cfg.nr_cora.task = "node"
cfg.nr_cora.task_type = "classification"
cfg.nr_cora.loss_fun = "cross_entropy"
cfg.nr_cora.task_dim = 7
cfg.nr_cora.split_mode = "random"
cfg.nr_cora.transductive = True
cfg.nr_cora.split_index = 0
cfg.nr_cora.feat_dim = 1
cfg.nr_cora.hidden_dim = 32
cfg.nr_cora.activate_fn = "torch.nn.ReLU()"
cfg.nr_cora.split = [0.6, 0.2, 0.2]
cfg.nr_cora.num_nodes = 2708

cfg.nr_fb_cmu_carnegie49.dataset_name = "fb-CMU-Carnegie49"
cfg.nr_fb_cmu_carnegie49.format = "Network_repository"
cfg.nr_fb_cmu_carnegie49.task = "node"
cfg.nr_fb_cmu_carnegie49.task_type = "classification"
cfg.nr_fb_cmu_carnegie49.loss_fun = "cross_entropy"
cfg.nr_fb_cmu_carnegie49.task_dim = 3
cfg.nr_fb_cmu_carnegie49.split_mode = "random"
cfg.nr_fb_cmu_carnegie49.transductive = True
cfg.nr_fb_cmu_carnegie49.split_index = 0
cfg.nr_fb_cmu_carnegie49.feat_dim = 1
cfg.nr_fb_cmu_carnegie49.hidden_dim = 32
cfg.nr_fb_cmu_carnegie49.activate_fn = "torch.nn.ReLU()"
cfg.nr_fb_cmu_carnegie49.split = [0.6, 0.2, 0.2]
cfg.nr_fb_cmu_carnegie49.num_nodes = 6637

cfg.nr_gene.dataset_name = "gene"
cfg.nr_gene.format = "Network_repository"
cfg.nr_gene.task = "node"
cfg.nr_gene.task_type = "classification"
cfg.nr_gene.loss_fun = "cross_entropy"
cfg.nr_gene.task_dim = 2
cfg.nr_gene.split_mode = "random"
cfg.nr_gene.transductive = True
cfg.nr_gene.split_index = 0
cfg.nr_gene.feat_dim = 1
cfg.nr_gene.hidden_dim = 32
cfg.nr_gene.activate_fn = "torch.nn.ReLU()"
cfg.nr_gene.split = [0.6, 0.2, 0.2]
cfg.nr_gene.num_nodes = 1103

cfg.nr_proteins_all.dataset_name = "proteins-all"
cfg.nr_proteins_all.format = "Network_repository"
cfg.nr_proteins_all.task = "node"
cfg.nr_proteins_all.task_type = "classification"
cfg.nr_proteins_all.loss_fun = "cross_entropy"
cfg.nr_proteins_all.task_dim = 3
cfg.nr_proteins_all.split_mode = "random"
cfg.nr_proteins_all.transductive = True
cfg.nr_proteins_all.split_index = 0
cfg.nr_proteins_all.feat_dim = 1
cfg.nr_proteins_all.hidden_dim = 32
cfg.nr_proteins_all.activate_fn = "torch.nn.ReLU()"
cfg.nr_proteins_all.split = [0.6, 0.2, 0.2]
cfg.nr_proteins_all.num_nodes = 43471

cfg.nr_reality_call.dataset_name = "reality-call"
cfg.nr_reality_call.format = "Network_repository"
cfg.nr_reality_call.task = "node"
cfg.nr_reality_call.task_type = "classification"
cfg.nr_reality_call.loss_fun = "cross_entropy"
cfg.nr_reality_call.task_dim = 2
cfg.nr_reality_call.split_mode = "random"
cfg.nr_reality_call.transductive = True
cfg.nr_reality_call.split_index = 0
cfg.nr_reality_call.feat_dim = 1
cfg.nr_reality_call.hidden_dim = 32
cfg.nr_reality_call.activate_fn = "torch.nn.ReLU()"
cfg.nr_reality_call.split = [0.6, 0.2, 0.2]
cfg.nr_reality_call.num_nodes = 27058

cfg.nr_soc_blogcatalog_asu.dataset_name = "soc-BlogCatalog-ASU"
cfg.nr_soc_blogcatalog_asu.format = "Network_repository"
cfg.nr_soc_blogcatalog_asu.task = "node"
cfg.nr_soc_blogcatalog_asu.task_type = "classification"
cfg.nr_soc_blogcatalog_asu.loss_fun = "cross_entropy"
cfg.nr_soc_blogcatalog_asu.task_dim = 39
cfg.nr_soc_blogcatalog_asu.split_mode = "random"
cfg.nr_soc_blogcatalog_asu.transductive = True
cfg.nr_soc_blogcatalog_asu.split_index = 0
cfg.nr_soc_blogcatalog_asu.feat_dim = 1
cfg.nr_soc_blogcatalog_asu.hidden_dim = 32
cfg.nr_soc_blogcatalog_asu.activate_fn = "torch.nn.ReLU()"
cfg.nr_soc_blogcatalog_asu.split = [0.6, 0.2, 0.2]
cfg.nr_soc_blogcatalog_asu.num_nodes = 10312

cfg.nr_soc_flickr_asu.dataset_name = "soc-Flickr-ASU"
cfg.nr_soc_flickr_asu.format = "Network_repository"
cfg.nr_soc_flickr_asu.task = "node"
cfg.nr_soc_flickr_asu.task_type = "classification"
cfg.nr_soc_flickr_asu.loss_fun = "cross_entropy"
cfg.nr_soc_flickr_asu.task_dim = 195
cfg.nr_soc_flickr_asu.split_mode = "random"
cfg.nr_soc_flickr_asu.transductive = True
cfg.nr_soc_flickr_asu.split_index = 0
cfg.nr_soc_flickr_asu.feat_dim = 1
cfg.nr_soc_flickr_asu.hidden_dim = 32
cfg.nr_soc_flickr_asu.activate_fn = "torch.nn.ReLU()"
cfg.nr_soc_flickr_asu.split = [0.6, 0.2, 0.2]
cfg.nr_soc_flickr_asu.num_nodes = 80513

cfg.nr_soc_youtube_asu.dataset_name = "soc-YouTube-ASU"
cfg.nr_soc_youtube_asu.format = "Network_repository"
cfg.nr_soc_youtube_asu.task = "node"
cfg.nr_soc_youtube_asu.task_type = "classification"
cfg.nr_soc_youtube_asu.loss_fun = "cross_entropy"
cfg.nr_soc_youtube_asu.task_dim = 47
cfg.nr_soc_youtube_asu.split_mode = "random"
cfg.nr_soc_youtube_asu.transductive = True
cfg.nr_soc_youtube_asu.split_index = 0
cfg.nr_soc_youtube_asu.feat_dim = 1
cfg.nr_soc_youtube_asu.hidden_dim = 32
cfg.nr_soc_youtube_asu.activate_fn = "torch.nn.ReLU()"
cfg.nr_soc_youtube_asu.split = [0.6, 0.2, 0.2]
cfg.nr_soc_youtube_asu.num_nodes = 644063

cfg.nr_soc_political_retweet.dataset_name = "soc-political-retweet"
cfg.nr_soc_political_retweet.format = "Network_repository"
cfg.nr_soc_political_retweet.task = "node"
cfg.nr_soc_political_retweet.task_type = "classification"
cfg.nr_soc_political_retweet.loss_fun = "cross_entropy"
cfg.nr_soc_political_retweet.task_dim = 2
cfg.nr_soc_political_retweet.split_mode = "random"
cfg.nr_soc_political_retweet.transductive = True
cfg.nr_soc_political_retweet.split_index = 0
cfg.nr_soc_political_retweet.feat_dim = 1
cfg.nr_soc_political_retweet.hidden_dim = 32
cfg.nr_soc_political_retweet.activate_fn = "torch.nn.ReLU()"
cfg.nr_soc_political_retweet.split = [0.6, 0.2, 0.2]
cfg.nr_soc_political_retweet.num_nodes = 18469

cfg.nr_webkb_wisc.dataset_name = "webkb-wisc"
cfg.nr_webkb_wisc.format = "Network_repository"
cfg.nr_webkb_wisc.task = "node"
cfg.nr_webkb_wisc.task_type = "classification"
cfg.nr_webkb_wisc.loss_fun = "cross_entropy"
cfg.nr_webkb_wisc.task_dim = 5
cfg.nr_webkb_wisc.split_mode = "random"
cfg.nr_webkb_wisc.transductive = True
cfg.nr_webkb_wisc.split_index = 0
cfg.nr_webkb_wisc.feat_dim = 1
cfg.nr_webkb_wisc.hidden_dim = 32
cfg.nr_webkb_wisc.activate_fn = "torch.nn.ReLU()"
cfg.nr_webkb_wisc.split = [0.6, 0.2, 0.2]
cfg.nr_webkb_wisc.num_nodes = 265

