deal with situation where num_layers equals 1 (#3066)

examples/pytorch/graphsage/model.py

@@ -17,10 +17,13 @@ class SAGE(nn.Module):
         self.n_hidden = n_hidden
         self.n_classes = n_classes
         self.layers = nn.ModuleList()
-        self.layers.append(dglnn.SAGEConv(in_feats, n_hidden, 'mean'))
-        for i in range(1, n_layers - 1):
-            self.layers.append(dglnn.SAGEConv(n_hidden, n_hidden, 'mean'))
-        self.layers.append(dglnn.SAGEConv(n_hidden, n_classes, 'mean'))
+        if n_layers > 1:
+            self.layers.append(dglnn.SAGEConv(in_feats, n_hidden, 'mean'))
+            for i in range(1, n_layers - 1):
+                self.layers.append(dglnn.SAGEConv(n_hidden, n_hidden, 'mean'))
+            self.layers.append(dglnn.SAGEConv(n_hidden, n_classes, 'mean'))
+        else:
+            self.layers.append(dglnn.SAGEConv(in_feats, n_classes, 'mean'))
         self.dropout = nn.Dropout(dropout)
         self.activation = activation