Update README.md

README.md

@@ -27,40 +27,36 @@ pip install paddle-serving-server
 ``` python
 import sys
 import paddle
-import paddle.fluid as fluid
 
 train_reader = paddle.batch(paddle.reader.shuffle(
     paddle.dataset.uci_housing.train(), buf_size=500), batch_size=16)
 
-test_reader = paddle.batch(paddle.reader.shuffle(
-    paddle.dataset.uci_housing.test(), buf_size=500), batch_size=16)
-
-x = fluid.data(name='x', shape=[None, 13], dtype='float32')
-y = fluid.data(name='y', shape=[None, 1], dtype='float32')
+x = paddle.fluid.data(name='x', shape=[None, 13], dtype='float32')
+y = paddle.fluid.data(name='y', shape=[None, 1], dtype='float32')
 
-y_predict = fluid.layers.fc(input=x, size=1, act=None)
-cost = fluid.layers.square_error_cost(input=y_predict, label=y)
-avg_loss = fluid.layers.mean(cost)
-sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.01)
+y_predict = paddle.fluid.layers.fc(input=x, size=1, act=None)
+cost = paddle.fluid.layers.square_error_cost(input=y_predict, label=y)
+avg_loss = paddle.fluid.layers.mean(cost)
+sgd_optimizer = paddle.fluid.optimizer.SGD(learning_rate=0.01)
 sgd_optimizer.minimize(avg_loss)
 
-place = fluid.CPUPlace()
-feeder = fluid.DataFeeder(place=place, feed_list=[x, y])
-exe = fluid.Executor(place)
-exe.run(fluid.default_startup_program())
+place = paddle.fluid.CPUPlace()
+feeder = paddle.fluid.DataFeeder(place=place, feed_list=[x, y])
+exe = paddle.fluid.Executor(place)
+exe.run(paddle.fluid.default_startup_program())
 
 import paddle_serving_client.io as serving_io
 
 for pass_id in range(30):
     for data_train in train_reader():
         avg_loss_value, = exe.run(
-            fluid.default_main_program(),
+            paddle.fluid.default_main_program(),
             feed=feeder.feed(data_train),
             fetch_list=[avg_loss])
 
 serving_io.save_model(
     "serving_server_model", "serving_client_conf",
-    {"x": x}, {"y": y_predict}, fluid.default_main_program())
+    {"x": x}, {"y": y_predict}, paddle.fluid.default_main_program())
 ```