diff --git a/docs/source/quick_start/md/quick_start_for_heterGraph.md b/docs/source/quick_start/md/quick_start_for_heterGraph.md
index 37ac0de4c362a097518f775da340907408f9a31e..aae818c0be633a5708eb2ea29636077f3c919425 100644
--- a/docs/source/quick_start/md/quick_start_for_heterGraph.md
+++ b/docs/source/quick_start/md/quick_start_for_heterGraph.md
@@ -58,8 +58,8 @@ Now, we can build a heterogenous graph by using PGL.
 import paddle.fluid as fluid
 import paddle.fluid.layers as fl
 import pgl
-from pgl.contrib import heter_graph
-from pgl.contrib import heter_graph_wrapper
+from pgl import heter_graph
+from pgl import heter_graph_wrapper
 
 g = heter_graph.HeterGraph(num_nodes=num_nodes,
                             edges=edges,
@@ -160,8 +160,3 @@ for epoch in range(30):
     train_loss = exe.run(fluid.default_main_program(), feed=feed_dict, fetch_list=[loss], return_numpy=True)
     print('Epoch %d | Loss: %f'%(epoch, train_loss[0]))
 ```
-
-
-
-
-