diff --git a/paddle/fluid/framework/details/build_strategy.cc b/paddle/fluid/framework/details/build_strategy.cc
index 010c8dee6c414027c0a5665f69692f21b298d297..a6359402f8dc40b3006ba6a21370a3af84ba0f9c 100644
--- a/paddle/fluid/framework/details/build_strategy.cc
+++ b/paddle/fluid/framework/details/build_strategy.cc
@@ -133,15 +133,15 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
   void AppendMultiDevPass(const BuildStrategy &strategy) {
     ir::Pass *multi_devices_pass;
     if (strategy_.is_distribution_) {
-      VLOG(3) << "multi device dist train mode";
+      VLOG(3) << "multi device parameter server mode";
       multi_devices_pass = AppendPass("dist_multi_devices_pass").get();
     } else {
       if (strategy.reduce_ == BuildStrategy::ReduceStrategy::kAllReduce) {
-        VLOG(3) << "multi device allreduce mode";
+        VLOG(3) << "multi devices collective mode with allreduce";
         multi_devices_pass =
             AppendPass("allreduce_mode_multi_devices_pass").get();
       } else if (strategy.reduce_ == BuildStrategy::ReduceStrategy::kReduce) {
-        VLOG(3) << "multi device reduce mode";
+        VLOG(3) << "multi deivces collective mode with reduce";
         multi_devices_pass = AppendPass("reduce_mode_multi_devices_pass").get();
       } else {
         PADDLE_THROW("Unknown reduce strategy.");
diff --git a/python/paddle/fluid/compiler.py b/python/paddle/fluid/compiler.py
index 2b69fd89a2c19f933a7ff7bb3bcc4bbb2c49e7e9..d253f0cca8eecbd97aa033ec7209b6fcdb36aa08 100644
--- a/python/paddle/fluid/compiler.py
+++ b/python/paddle/fluid/compiler.py
@@ -35,15 +35,6 @@ def _place_obj(place):
     return p
 
 
-def _is_pserver_mode(main_program):
-    main = main_program if main_program \
-        else framework.default_main_program()
-    for op in main.global_block().ops:
-        if op.type in ["send", "recv"]:
-            return True
-    return False
-
-
 class CompiledProgram(object):
     """
     Compiles a Program for execution.
@@ -120,7 +111,8 @@ class CompiledProgram(object):
             self._exec_strategy = ExecutionStrategy()
         if self._build_strategy is None:
             self._build_strategy = BuildStrategy()
-        self._build_strategy.is_distribution = _is_pserver_mode(self._program)
+        self._build_strategy.is_distribution = framework.is_pserver_mode(
+            self._program)
         return self
 
     def with_inference_optimize(self, config):
diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py
index 832c97c7deb49b4e118e15989ab7a34da6ce57a0..162e94ec59434bfcf018d73e0c49f9cc21e81185 100644
--- a/python/paddle/fluid/framework.py
+++ b/python/paddle/fluid/framework.py
@@ -85,6 +85,15 @@ def _current_expected_place():
     return _imperative_current_expected_place_
 
 
+def is_pserver_mode(main_program):
+    main = main_program if main_program \
+        else default_main_program()
+    for op in main.global_block().ops:
+        if op.type in ["send", "recv"]:
+            return True
+    return False
+
+
 class NameScope(object):
     def __init__(self, name="", parent=None):
         self._children = dict()
diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index 22212ae9a216acaab3f295f1f8d091829a0aa471..9bff3599a04799d208b3d91bf65a30914c3e80aa 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -29,15 +29,6 @@ ExecutionStrategy = core.ParallelExecutor.ExecutionStrategy
 BuildStrategy = core.ParallelExecutor.BuildStrategy
 
 
-def _is_pserver_mode(main_program):
-    main = main_program if main_program \
-        else framework.default_main_program()
-    for op in main.global_block().ops:
-        if op.type in ["send", "recv"]:
-            return True
-    return False
-
-
 class ParallelExecutor(object):
     """
     ParallelExecutor is designed for data parallelism, which focuses on distributing
@@ -140,7 +131,7 @@ class ParallelExecutor(object):
         # FIXME(zcd): is_distribution_ is a temporary field, because in pserver mode,
         # num_trainers is 1, so the current fields of build_strategy doesn't tell if
         # it's distributed model.
-        build_strategy.is_distribution = _is_pserver_mode(
+        build_strategy.is_distribution = framework.is_pserver_mode(
             main_program) or num_trainers > 1
 
         # step4: get main_program, scope, local_scopes