--- a
+++ b/gcn_model.py
@@ -0,0 +1,31 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Time    : 2021/8/8 16:20
+# @Author  : Li Xiao
+# @File    : gcn_model.py
+from torch import nn
+import torch.nn.functional as F
+from layer import GraphConvolution
+
+class GCN(nn.Module):
+    def __init__(self, n_in, n_hid, n_out, dropout=None):
+        super(GCN, self).__init__()
+        self.gc1 = GraphConvolution(n_in, n_hid)
+        self.gc2 = GraphConvolution(n_hid, n_hid)
+        self.dp1 = nn.Dropout(dropout)
+        self.dp2 = nn.Dropout(dropout)
+        #self.fc1 = nn.Linear(n_hid, n_hid)
+        self.fc = nn.Linear(n_hid, n_out)
+        self.dropout = dropout
+
+    def forward(self, input, adj):
+        x = self.gc1(input, adj)
+        x = F.elu(x)
+        x = self.dp1(x)
+        x = self.gc2(x, adj)
+        x = F.elu(x)
+        x = self.dp2(x)
+
+        x = self.fc(x)
+
+        return x
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