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model.txt
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model.txt
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(model): GCN(
(pre_mp): GeneralMultiLayer(
(Layer_0): GeneralLayer(
(layer): Linear(
(model): Linear(in_features=32, out_features=256, bias=False)
)
(post_layer): Sequential(
(0): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(1): ReLU()
)
)
(Layer_1): GeneralLayer(
(layer): Linear(
(model): Linear(in_features=256, out_features=256, bias=False)
)
(post_layer): Sequential(
(0): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(1): ReLU()
)
)
(Layer_2): GeneralLayer(
(layer): Linear(
(model): Linear(in_features=256, out_features=256, bias=False)
)
(post_layer): Sequential(
(0): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(1): ReLU()
)
)
)
(mp): GNNStackStage(
(layer0): GeneralLayer(
(layer): SAGEConv(
(model): SAGEConv(256, 256, aggr=max)
)
(post_layer): Sequential(
(0): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(1): ReLU()
)
)
)
(post_mp): GNNGraphHead(
(layer_post_mp): MLP(
(model): Sequential(
(0): GeneralMultiLayer(
(Layer_0): GeneralLayer(
(layer): Linear(
(model): Linear(in_features=256, out_features=256, bias=False)
)
(post_layer): Sequential(
(0): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(1): ReLU()
)
)
(Layer_1): GeneralLayer(
(layer): Linear(
(model): Linear(in_features=256, out_features=256, bias=False)
)
(post_layer): Sequential(
(0): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(1): ReLU()
)
)
)
(1): Linear(
(model): Linear(in_features=256, out_features=1, bias=True)
)
)
)
)