13importtorch14fromtorchimportnn1516fromlabmlimportexperiment17fromlabml.configsimportoption18fromlabml\_helpers.moduleimportModule19fromlabml\_nn.graphs.gat.experimentimportConfigsasGATConfigs20fromlabml\_nn.graphs.gatv2importGraphAttentionV2Layer

23classGATv2(Module):

30def\_\_init\_\_(self,in\_features:int,n\_hidden:int,n\_classes:int,n\_heads:int,dropout:float,31share\_weights:bool=True):

40super().\_\_init\_\_()

43self.layer1=GraphAttentionV2Layer(in\_features,n\_hidden,n\_heads,44is\_concat=True,dropout=dropout,share\_weights=share\_weights)

46self.activation=nn.ELU()

48self.output=GraphAttentionV2Layer(n\_hidden,n\_classes,1,49is\_concat=False,dropout=dropout,share\_weights=share\_weights)

51self.dropout=nn.Dropout(dropout)

53defforward(self,x:torch.Tensor,adj\_mat:torch.Tensor):

60x=self.dropout(x)

62x=self.layer1(x,adj\_mat)

64x=self.activation(x)

66x=self.dropout(x)

68returnself.output(x,adj\_mat)

71classConfigs(GATConfigs):

80share\_weights:bool=False

82model:GATv2='gat\_v2\_model'

85@option(Configs.model)86defgat\_v2\_model(c:Configs):

90returnGATv2(c.in\_features,c.n\_hidden,c.n\_classes,c.n\_heads,c.dropout,c.share\_weights).to(c.device)

93defmain():

95conf=Configs()

97experiment.create(name='gatv2')

99experiment.configs(conf,{

101'optimizer.optimizer':'Adam',102'optimizer.learning\_rate':5e-3,103'optimizer.weight\_decay':5e-4,104105'dropout':0.7,106})

109withexperiment.start():

111conf.run()

115if\_\_name\_\_=='\_\_main\_\_':116main()