diff --git a/python/examples/fit_a_line/benchmark.py b/python/examples/fit_a_line/benchmark.py
index 5cc094dc17f2b4519e076b34d4368f0f33b8f3eb..b1550b2ff5d40aa10e3f415c82235c06a4508012 100644
--- a/python/examples/fit_a_line/benchmark.py
+++ b/python/examples/fit_a_line/benchmark.py
@@ -25,19 +25,24 @@ args = benchmark_args()
 
 
 def single_func(idx, resource):
+    train_reader = paddle.batch(
+        paddle.reader.shuffle(
+            paddle.dataset.uci_housing.train(), buf_size=500),
+        batch_size=1)
+    total_number = sum(1 for _ in train_reader())
+
     if args.request == "rpc":
         client = Client()
         client.load_client_config(args.model)
         client.connect([args.endpoint])
-        train_reader = paddle.batch(
-            paddle.reader.shuffle(
-                paddle.dataset.uci_housing.train(), buf_size=500),
-            batch_size=1)
         start = time.time()
         for data in train_reader():
-            fetch_map = client.predict(feed={"x": data[0][0]}, fetch=["price"],batch=True)
+            #new_data = np.zeros((1, 13)).astype("float32")
+            #new_data[0] = data[0][0]
+            #fetch_map = client.predict(feed={"x": new_data}, fetch=["price"], batch=True)
+            fetch_map = client.predict(feed={"x": data[0][0]}, fetch=["price"])
         end = time.time()
-        return [[end - start]]
+        return [[end - start], [total_number]]
     elif args.request == "http":
         train_reader = paddle.batch(
             paddle.reader.shuffle(
@@ -49,7 +54,7 @@ def single_func(idx, resource):
                 'http://{}/uci/prediction'.format(args.endpoint),
                 data={"x": data[0]})
         end = time.time()
-        return [[end - start]]
+        return [[end - start], [total_number]]
 
 
 multi_thread_runner = MultiThreadRunner()