diff --git a/python/paddle/distributed/auto_parallel/engine.py b/python/paddle/distributed/auto_parallel/engine.py
index 35ff882491a26487fac199df5d470ca3aebb14ac..11953aa085de2ededeee52c902dd720643f88fd0 100644
--- a/python/paddle/distributed/auto_parallel/engine.py
+++ b/python/paddle/distributed/auto_parallel/engine.py
@@ -189,9 +189,8 @@ class Engine:
             serial_main_prog = self._orig_main_prog.clone()
             serial_startup_prog = self._orig_startup_prog.clone()
             # FIXME to support grad clip
-            # with static.program_guard(serial_main_prog, serial_startup_prog), \
-            #     utils.unique_name.guard():
-            with static.program_guard(serial_main_prog, serial_startup_prog):
+            with static.program_guard(serial_main_prog, serial_startup_prog), \
+                utils.unique_name.guard():
                 inputs_spec = self.inputs_spec
                 labels_spec = self.labels_spec if self.labels_spec else []
                 inputs = [s._create_feed_layer() for s in inputs_spec]
diff --git a/python/paddle/fluid/contrib/mixed_precision/fp16_utils.py b/python/paddle/fluid/contrib/mixed_precision/fp16_utils.py
index e35dc901c8371d6b396e40fa83ddb64d841ef7ba..b23c94c7e499495aae14d3c0a11c9867b3029f4d 100644
--- a/python/paddle/fluid/contrib/mixed_precision/fp16_utils.py
+++ b/python/paddle/fluid/contrib/mixed_precision/fp16_utils.py
@@ -542,12 +542,9 @@ def cast_parameters_to_fp16(place, program, scope=None, to_fp16_var_names=None):
 
     fp16_var_names = to_fp16_var_names if to_fp16_var_names else set()
     var_scope = scope if scope else global_scope()
-    print(
-        "======================cast_parameters_to_fp16=============================="
-    )
     for param in all_parameters:
         if param.name in fp16_var_names:
-            print("---- cast {} to fp16 dtype ----".format(param.name))
+            _logger.debug("---- cast {} to fp16 dtype ----".format(param.name))
             param_t = var_scope.find_var(param.name).get_tensor()
             data = np.array(param_t)
             param_t.set(np.float16(data), place)