diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py
index 56c008d1af70f4b5f6169ebe5174b08fcf8bc722..8c6dbd3b5ae5d8bcd8d0a136457c20003fd23ded 100644
--- a/python/paddle/fluid/inferencer.py
+++ b/python/paddle/fluid/inferencer.py
@@ -17,6 +17,7 @@ import core
 import executor
 import framework
 import io
+import parallel_executor
 import unique_name
 from trainer import check_and_get_place
 
@@ -24,7 +25,7 @@ __all__ = ['Inferencer', ]
 
 
 class Inferencer(object):
-    def __init__(self, infer_func, param_path, place=None):
+    def __init__(self, infer_func, param_path, place=None, parallel=False):
         """
         :param infer_func: a function that will return predict Variable
         :param param_path: the path where the inference model is saved by fluid.io.save_params
@@ -32,13 +33,20 @@ class Inferencer(object):
         """
         self.param_path = param_path
         self.scope = core.Scope()
+        self.parallel = parallel
+        self.place = check_and_get_place(place)
 
         self.inference_program = framework.Program()
         with framework.program_guard(self.inference_program):
             with unique_name.guard():
                 self.predict_var = infer_func()
 
-        self.exe = executor.Executor(check_and_get_place(place))
+        if parallel:
+            self.exe = parallel_executor.ParallelExecutor(
+                use_cuda=isinstance(self.place, core.CUDAPlace),
+                loss_name=self.predict_var.name)
+        else:
+            self.exe = executor.Executor(self.place)
         with executor.scope_guard(self.scope):
             # load params from param_path into scope
             io.load_params(self.exe, param_path, self.inference_program)
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index d158d586321833fdf046e4e061bfa8460b9a31b5..f4292208c949ea271a7a65267d0a71208e74e75f 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -12,18 +12,18 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import contextlib
 import os
+
 import core
-import framework
-import executor
+
 import data_feeder
-import contextlib
+import executor
+import framework
 import io
-import unique_name
-import parallel_executor
-
 # optimizer is same as the parameter of Trainer.__init__. Rename it to opt_module
 import optimizer as opt_module
+import parallel_executor
 from transpiler import distribute_transpiler
 
 __all__ = [