And classes are declared as:
features.weight = nn.Parameter(torch.FloatTensor(feat).cuda(),
                              requires_grad=False)
agg1 = MeanAggregation(features,num=1,cuda=True)
enc1 = Encoder(features,b0_adj_matrix,embed_dim=1096,feature_dim=50,agg=agg1,cuda=True)#check feature_dim these things
agg2 = MeanAggregation(lambda nodes :enc1(nodes).t(),num=2,cuda=True)
enc2 = Encoder(lambda nodes:enc1(nodes).t(),b1_adj_matrix,embed_dim=1096,feature_dim=enc1.embed_dim,agg=agg2,cuda=True)#.cuda()
num_cls=121
graphsage = GraphSage(num_cls,enc2).cuda()
loss = graphsage.loss(train_nodes,train_label)
print(loss)