text: import torch.nn as nn
  import torch.nn.functional as F
  import torch
  from layers import Graphsn_GCN
  
  class GNN(nn.Module):
      def __init__(self, nfeat, nhid, nclass, dropout):
          super(GNN, self).__init__()
          
          self.gc1 = Graphsn_GCN(nfeat, nhid)
          self.gc2 = Graphsn_GCN(nhid, nclass)
          self.dropout = dropout
  
      def forward(self, x, adj):
          
          x = F.relu(self.gc1(x, adj)) #F.celu(self.gc1(x, adj), alpha=2e-5)
          x = F.dropout(x, self.dropout, training=self.training)
          x = self.gc2(x, adj)
          
          return F.log_softmax(x, dim=-1)