diff --git a/core/trainers/framework/runner.py b/core/trainers/framework/runner.py
index 449e288777b4b1519b19457dbc7a3d1ab68ce93e..839e3ed4d6e04b13f69e6c2cfc463e83aef130f7 100644
--- a/core/trainers/framework/runner.py
+++ b/core/trainers/framework/runner.py
@@ -212,11 +212,9 @@ class RunnerBase(object):
                         if context["fleet_mode"].upper() == "PS":
                             train_prog = context["model"][model_dict["name"]][
                                 "main_program"]
-                            print("condition 1")
                         else:
                             train_prog = context["model"][model_dict["name"]][
                                 "default_main_program"]
-                            print("condition 2")
                         startup_prog = context["model"][model_dict["name"]][
                             "startup_program"]
                         with fluid.program_guard(train_prog, startup_prog):
diff --git a/models/rank/dnn/config.yaml b/models/rank/dnn/config.yaml
index f0c82462485cfda69882894d16cdfadffb872c89..75826684dbc0734e4acf40983bbc837c7b97ac84 100755
--- a/models/rank/dnn/config.yaml
+++ b/models/rank/dnn/config.yaml
@@ -114,15 +114,13 @@ runner:
   print_interval: 1
   phases: [phase1]
 
-- name: local_ps_train
-  class: local_cluster_train
+- name: single_multi_gpu_train
+  class: train
   # num of epochs
   epochs: 1
   # device to run training or infer
-  device: cpu
-  selected_gpus: "0" # 选择多卡执行训练
-  work_num: 1
-  server_num: 1
+  device: gpu
+  selected_gpus: "0,1" # 选择多卡执行训练
   save_checkpoint_interval: 1 # save model interval of epochs
   save_inference_interval: 4 # save inference
   save_step_interval: 1