save topology for chapter 1

01.fit_a_line/README.cn.md

@@ -128,6 +128,16 @@ y_predict = paddle.layer.fc(input=x,
 y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))
 cost = paddle.layer.mse_cost(input=y_predict, label=y)
 ```
+
+### 保存网络拓扑
+
+```python
+# Save the inference topology to protobuf.
+inference_topology = paddle.topology.Topology(layers=y_predict)
+with open("inference_topology.pkl", 'wb') as f:
+    inference_topology.serialize_for_inference(f)
+```
+
 ### 创建参数
 
 ```python

01.fit_a_line/README.md

@@ -134,6 +134,17 @@ y_predict = paddle.layer.fc(input=x,
 y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))
 cost = paddle.layer.mse_cost(input=y_predict, label=y)
 ```
+
+### Save Topology
+
+```python
+# Save the inference topology to protobuf.
+inference_topology = paddle.topology.Topology(layers=y_predict)
+with open("inference_topology.pkl", 'wb') as f:
+    inference_topology.serialize_for_inference(f)
+```
+
+
 ### Create Parameters
 
 ```python

01.fit_a_line/index.cn.html

@@ -170,6 +170,16 @@ y_predict = paddle.layer.fc(input=x,
 y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))
 cost = paddle.layer.mse_cost(input=y_predict, label=y)
 ```
+
+### 保存网络拓扑
+
+```python
+# Save the inference topology to protobuf.
+inference_topology = paddle.topology.Topology(layers=y_predict)
+with open("inference_topology.pkl", 'wb') as f:
+    inference_topology.serialize_for_inference(f)
+```
+
 ### 创建参数
 
 ```python

01.fit_a_line/index.html

@@ -176,6 +176,17 @@ y_predict = paddle.layer.fc(input=x,
 y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))
 cost = paddle.layer.mse_cost(input=y_predict, label=y)
 ```
+
+### Save Topology
+
+```python
+# Save the inference topology to protobuf.
+inference_topology = paddle.topology.Topology(layers=y_predict)
+with open("inference_topology.pkl", 'wb') as f:
+    inference_topology.serialize_for_inference(f)
+```
+
+
 ### Create Parameters
 
 ```python

01.fit_a_line/train.py

@@ -12,6 +12,11 @@ def main():
     y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))
     cost = paddle.layer.square_error_cost(input=y_predict, label=y)
 
+    # Save the inference topology to protobuf.
+    inference_topology = paddle.topology.Topology(layers=y_predict)
+    with open("inference_topology.pkl", 'wb') as f:
+        inference_topology.serialize_for_inference(f)
+
     # create parameters
     parameters = paddle.parameters.create(cost)
 
@@ -21,10 +26,6 @@ def main():
     trainer = paddle.trainer.SGD(
         cost=cost, parameters=parameters, update_equation=optimizer)
 
-    # save model proto as file
-    with open("model.proto", "w") as f:
-        f.write(str(trainer.__topology_in_proto__))
-
     feeding = {'x': 0, 'y': 1}
 
     # event_handler to print training and testing info