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use mlp for relgcn #316

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Merged
merged 1 commit into from
Jan 31, 2019
Merged

use mlp for relgcn #316

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4 changes: 2 additions & 2 deletions examples/molnet/train_molnet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -134,9 +134,9 @@ def set_up_predictor(method, n_unit, conv_layers, class_num):
elif method == 'relgcn':
print('Training an RelGCN predictor...')
num_edge_type = 4
relgcn = RelGCN(out_channels=class_num, num_edge_type=num_edge_type,
relgcn = RelGCN(out_channels=n_unit, num_edge_type=num_edge_type,
scale_adj=True)
return GraphConvPredictor(relgcn, None)
return GraphConvPredictor(relgcn, mlp)
elif method == 'relgat':
print('Train Relational GAT model...')
relgat = RelGAT(out_dim=n_unit, hidden_dim=n_unit,
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4 changes: 2 additions & 2 deletions examples/own_dataset/train_own_dataset.py
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Expand Up @@ -169,9 +169,9 @@ def set_up_predictor(method, n_unit, conv_layers, class_num):
elif method == 'relgcn':
print('Training an RelGCN predictor...')
num_edge_type = 4
relgcn = RelGCN(out_channels=class_num, num_edge_type=num_edge_type,
relgcn = RelGCN(out_channels=n_unit, num_edge_type=num_edge_type,
scale_adj=True)
predictor = GraphConvPredictor(relgcn, None)
predictor = GraphConvPredictor(relgcn, mlp)
elif method == 'relgat':
print('Training an RelGAT predictor...')
relgat = RelGAT(out_dim=n_unit, hidden_dim=n_unit,
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4 changes: 2 additions & 2 deletions examples/qm9/train_qm9.py
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Expand Up @@ -173,9 +173,9 @@ def set_up_predictor(method, n_unit, conv_layers, class_num, scaler):
elif method == 'relgcn':
print('Use Relational GCN predictor...')
num_edge_type = 4
relgcn = RelGCN(out_channels=class_num, num_edge_type=num_edge_type,
relgcn = RelGCN(out_channels=n_unit, num_edge_type=num_edge_type,
scale_adj=True)
predictor = GraphConvPredictor(relgcn, None, scaler)
predictor = GraphConvPredictor(relgcn, mlp, scaler)
elif method == 'relgat':
print('Train Relational GAT predictor...')
relgat = RelGAT(out_dim=n_unit, hidden_dim=n_unit,
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5 changes: 3 additions & 2 deletions examples/tox21/predictor.py
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Expand Up @@ -46,8 +46,9 @@ def build_predictor(method, n_unit, conv_layers, class_num):
print('Use Relational GCN predictor...')
num_edge_type = 4
predictor = GraphConvPredictor(
RelGCN(out_channels=class_num, num_edge_type=num_edge_type,
scale_adj=True))
RelGCN(out_channels=n_unit, num_edge_type=num_edge_type,
scale_adj=True),
MLP(out_dim=class_num, hidden_dim=n_unit))
elif method == 'relgat':
print('Use GAT predictor...')
predictor = GraphConvPredictor(
Expand Down