diff --git a/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_optimizer.py b/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_optimizer.py
index 978899604eaf8c2ee45c03f866f2d5a081a7e502..824225fd776d1363d79e2218959507df8668bcee 100644
--- a/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_optimizer.py
+++ b/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_optimizer.py
@@ -214,7 +214,8 @@ class AscendOptimizer(Optimizer):
                  parameter_list=None,
                  no_grad_set=None,
                  auto_dp=False,
-                 rank_table_file=None):
+                 rank_table_file=None,
+                 precision_mode="must_keep_origin_dtype"):
         minimized = None
         if self.inner_opt:
             minimized = self.inner_opt.minimize(
@@ -234,7 +235,7 @@ class AscendOptimizer(Optimizer):
         config = {
             "ge.exec.deviceId": str(fleet.local_device_ids()),
             "ge.graphRunMode": "1",
-            "ge.exec.precision_mode": "must_keep_origin_dtype",
+            "ge.exec.precision_mode": precision_mode,
         }
         # if multi trainers
         if rank_table_file and fleet.world_size() > 1:
diff --git a/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py b/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py
index d7ba61a8e40144fd5f75156788a95c4b4cb235ea..e191776ffe41e7e9291b1fb5f3d560e8f81fc880 100644
--- a/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py
+++ b/python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py
@@ -203,7 +203,8 @@ class AscendParserBase(object):
     def _accumulated_op_id(self):
         global global_cnt
         global_cnt += 1
-        return "." + str(global_cnt)
+        name = "." + str(global_cnt)
+        return name
 
     def _create_ge_tensor(self, shape, dtype, value):
         tensor_desc = core.GETensorDesc(
@@ -1630,10 +1631,14 @@ class MulGradParser(AscendParserBase):
                     "unsqueeze" + self._accumulated_op_id(),
                     "Unsqueeze").set_input("x",
                                            y).set_attr_vec_int32("axes", [0])
+                y_stack = core.GEOperatorFactory.create_operator(
+                    "stack" + self._accumulated_op_id(),
+                    "TileWithAxis").set_input("x", y_unsqueeze).set_attr_int32(
+                        "axis", 0).set_attr_int32("tiles", shape_out_grad[0])
                 x_grad = core.GEOperatorFactory.create_operator(
                     self.parser_name + self._accumulated_op_id(),
                     "BatchMatMul").set_input("x1", out_grad).set_input(
-                        "x2", y_unsqueeze).set_attr_bool(
+                        "x2", y_stack).set_attr_bool(
                             "adj_x1", False).set_attr_bool("adj_x2", True)
                 y_grad = core.GEOperatorFactory.create_operator(
                     self.parser_name + self._accumulated_op_id(),