[Doc] Update doc tutorials (#352)

THUDM · Jun 7, 2022 · e585a0d · e585a0d
1 parent 398f931
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diff --git a/docs/source/tutorial/custom_gnn.rst b/docs/source/tutorial/custom_gnn.rst
@@ -34,7 +34,7 @@ JKNet collects the output of all layers and concatenate them together to get the
             super(JKNet, self).__init__()
             shapes = [in_feats] + [hidden_size] * num_layers
             self.layers = nn.ModuleList([
-                GCNLayer(shape[i], shape[i+1])
+                GCNLayer(shapes[i], shapes[i+1])
                 for i in range(num_layers)
             ])
             self.fc = nn.Linear(hidden_size * num_layers, out_feats)
@@ -45,7 +45,7 @@ JKNet collects the output of all layers and concatenate them together to get the
             h = graph.x
             out = []
             for layer in self.layers:
-                h = layer(x)
+                h = layer(graph,h)
                 out.append(h)
             out = torch.cat(out, dim=1)
             return self.fc(out)
@@ -102,7 +102,7 @@ Now that you have defined your own GNN, you can use dataset/task in CogDL to imm
 
 .. code-block:: python
 
-    data = dataset.data
+    data = build_dataset_from_name("cora")[0]
     # Use the JKNet model as defined above
     model = JKNet(data.num_features, data.num_classes, 32, 4)
     experiment(model=model, dataset="cora", mw="node_classification_mw", dw="node_classification_dw")

diff --git a/docs/source/tutorial/graph.rst b/docs/source/tutorial/graph.rst
@@ -95,9 +95,9 @@ We also implement commonly used operations in ``Graph``:
     from cogdl.datasets import build_dataset_from_name
     g = build_dataset_from_name("cora")[0]
     g.num_nodes
-    >> 2707
+    >> 2708
     g.num_edges
-    >> 10184
+    >> 10556
     # Get a subgraph contaning nodes [0, .., 99]
     sub_g = g.subgraph(torch.arange(100))
     >> Graph(x=[100, 1433], edge_index=[2, 18], y=[100])
@@ -134,7 +134,7 @@ and others(node features, labels) are concatenated in node dimension. ``cogdl.da
 
     dataset = build_dataset_from_name("mutag")
     >> MUTAGDataset(188)
-    dataswet[0]
+    dataset[0]
     >> Graph(x=[17, 7], y=[1], edge_index=[2, 38])
     loader = DataLoader(dataset, batch_size=8)
     for batch in loader:
@@ -179,15 +179,15 @@ reflect to the original graph. However, in-place operation will affect the origi
 
     graph = build_dataset_from_name("cora")[0]
     graph.num_edges
-    >> 10184
+    >> 10556
     with graph.local_graph():
         mask = torch.arange(100)
         row, col = graph.edge_index
         graph.edge_index = (row[mask], col[mask])
         graph.num_edges
         >> 100
     graph.num_edges
-    >> 10184
+    >> 10556
 
     graph.edge_weight
     >> tensor([1.,...,1.])