diff --git a/python/examples/pipeline/imdb_model_ensemble/config.yml b/python/examples/pipeline/imdb_model_ensemble/config.yml
index 7dac6eec2a2d7d90be3d4684f2aaaec7496249d9..13a85d068e2a1bbea5caa2a552ce4f26cb3b0316 100644
--- a/python/examples/pipeline/imdb_model_ensemble/config.yml
+++ b/python/examples/pipeline/imdb_model_ensemble/config.yml
@@ -1,8 +1,8 @@
 port: 18080
-worker_num: 1
+worker_num: 4
 build_dag_each_worker: false
 dag:
-    is_thread_op: true
+    is_thread_op: false
     client_type: brpc
     retry: 1
     use_profile: false
diff --git a/python/examples/pipeline/imdb_model_ensemble/test_pipeline_client.py b/python/examples/pipeline/imdb_model_ensemble/test_pipeline_client.py
index 9cf476c4705c2267aa42337f90970d9fd051b7fd..aefc8dfd8463ad75d287e4d91b501fc19f7b8220 100644
--- a/python/examples/pipeline/imdb_model_ensemble/test_pipeline_client.py
+++ b/python/examples/pipeline/imdb_model_ensemble/test_pipeline_client.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from paddle_serving_client.pipeline import PipelineClient
+from paddle_serving_server_gpu.pipeline import PipelineClient
 import numpy as np
 
 client = PipelineClient()
@@ -20,12 +20,16 @@ client.connect(['127.0.0.1:18080'])
 words = 'i am very sad | 0'
 
 futures = []
-for i in range(100):
+for i in range(4):
     futures.append(
         client.predict(
-            feed_dict={"words": words}, fetch=["prediction"], asyn=True))
+            feed_dict={"words": words},
+            fetch=["prediction"],
+            asyn=True,
+            profile=False))
 
 for f in futures:
     res = f.result()
     if res["ecode"] != 0:
         print("predict failed: {}".format(res))
+    print(res)
diff --git a/python/examples/pipeline/imdb_model_ensemble/test_pipeline_server.py b/python/examples/pipeline/imdb_model_ensemble/test_pipeline_server.py
index 884f7476a12aadfe990c42365c42a3a4e6fafd3d..3c1f890477643402457f28144759310bc8cde587 100644
--- a/python/examples/pipeline/imdb_model_ensemble/test_pipeline_server.py
+++ b/python/examples/pipeline/imdb_model_ensemble/test_pipeline_server.py
@@ -14,8 +14,9 @@
 # pylint: disable=doc-string-missing
 
 import logging
-logging.basicConfig(format='%(levelname)s:%(asctime)s:%(message)s',
-                    level=logging.INFO)
+logging.basicConfig(
+    format="[%(process)d](%(threadName)s) %(levelname)s %(asctime)s [%(funcName)s:%(lineno)d] %(message)s",
+    level=logging.INFO)
 
 from paddle_serving_server_gpu.pipeline import Op, RequestOp, ResponseOp
 from paddle_serving_server_gpu.pipeline import PipelineServer
@@ -26,6 +27,7 @@ from paddle_serving_app.reader import IMDBDataset
 
 _LOGGER = logging.getLogger()
 
+
 class ImdbRequestOp(RequestOp):
     def init_op(self):
         self.imdb_dataset = IMDBDataset()
@@ -51,6 +53,7 @@ class CombineOp(Op):
         data = {"prediction": combined_prediction / 2}
         return data
 
+
 class ImdbResponseOp(ResponseOp):
     # Here ImdbResponseOp is consistent with the default ResponseOp implementation
     def pack_response_package(self, channeldata):
@@ -75,7 +78,9 @@ bow_op = Op(name="bow",
             client_config="imdb_bow_client_conf/serving_client_conf.prototxt",
             concurrency=1,
             timeout=-1,
-            retry=1)
+            retry=1,
+            batch_size=3,
+            auto_batching_timeout=1)
 cnn_op = Op(name="cnn",
             input_ops=[read_op],
             server_endpoints=["127.0.0.1:9292"],
@@ -83,13 +88,17 @@ cnn_op = Op(name="cnn",
             client_config="imdb_cnn_client_conf/serving_client_conf.prototxt",
             concurrency=1,
             timeout=-1,
-            retry=1)
+            retry=1,
+            batch_size=1,
+            auto_batching_timeout=None)
 combine_op = CombineOp(
     name="combine",
     input_ops=[bow_op, cnn_op],
-    concurrency=5,
+    concurrency=1,
     timeout=-1,
-    retry=1)
+    retry=1,
+    batch_size=2,
+    auto_batching_timeout=None)
 
 # fetch output of bow_op
 # response_op = ImdbResponseOp(input_ops=[bow_op])