diff --git a/fluid/object_detection/train.py b/fluid/object_detection/train.py
index 806887edca06df3102bcaa09f4b83d9d7e6524ea..8bc3c24f53fc15fd9201b91f7f33560fcb57a7e1 100644
--- a/fluid/object_detection/train.py
+++ b/fluid/object_detection/train.py
@@ -88,25 +88,27 @@ def build_program(main_prog, startup_prog, train_params, is_train):
             image, gt_box, gt_label, difficult = fluid.layers.read_file(py_reader)
             locs, confs, box, box_var = mobile_net(class_num, image, image_shape)
             if is_train:
-                loss = fluid.layers.ssd_loss(locs, confs, gt_box, gt_label, box,
-                    box_var)
-                loss = fluid.layers.reduce_sum(loss)
-                optimizer = optimizer_setting(train_params)
-                optimizer.minimize(loss)
+                with fluid.unique_name.guard("train"):
+                    loss = fluid.layers.ssd_loss(locs, confs, gt_box, gt_label, box,
+                        box_var)
+                    loss = fluid.layers.reduce_sum(loss)
+                    optimizer = optimizer_setting(train_params)
+                    optimizer.minimize(loss)
             else:
 
-                nmsed_out = fluid.layers.detection_output(
-                    locs, confs, box, box_var, nms_threshold=0.45)
-                with fluid.program_guard(main_prog):
-                    loss = fluid.evaluator.DetectionMAP(
-                        nmsed_out,
-                        gt_label,
-                        gt_box,
-                        difficult,
-                        class_num,
-                        overlap_threshold=0.5,
-                        evaluate_difficult=False,
-                        ap_version=args.ap_version)
+                with fluid.unique_name.guard("inference"):
+                    nmsed_out = fluid.layers.detection_output(
+                        locs, confs, box, box_var, nms_threshold=0.45)
+                    with fluid.program_guard(main_prog):
+                        loss = fluid.evaluator.DetectionMAP(
+                            nmsed_out,
+                            gt_label,
+                            gt_box,
+                            difficult,
+                            class_num,
+                            overlap_threshold=0.5,
+                            evaluate_difficult=False,
+                            ap_version=args.ap_version)
     return py_reader, loss