diff --git a/python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_stage2.py b/python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_stage2.py
index f800b43f9d282004e763293afbb2e811bbed0e4b..5a96be60e21e758469703113b32931164d77738c 100644
--- a/python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_stage2.py
+++ b/python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_stage2.py
@@ -539,14 +539,6 @@ class GroupShardedStage2(nn.Layer):
                 self._has_grad_storage[index] = True
             else:
                 self._param_grads.append(param.name)
-                print(
-                    "Can not add param: {}, param's shape: {}, param align: {}, grad_storages fill: {}, ".format(
-                        param.name,
-                        param.shape,
-                        self._trainable_param2align[param.name],
-                        self._grad_storages[param.dtype][dst_rank]._fill,
-                    )
-                )
 
         for dtype in self._grad_storages.keys():
             self._grad_storage_list.extend(
diff --git a/python/paddle/distributed/fleet/utils/hybrid_parallel_util.py b/python/paddle/distributed/fleet/utils/hybrid_parallel_util.py
index f67e52cbc5ea8b583bc5d2f7c7d4ac5a2a15fa35..8df7e69ea0b6fc98998d38d20c1f188850a4700e 100644
--- a/python/paddle/distributed/fleet/utils/hybrid_parallel_util.py
+++ b/python/paddle/distributed/fleet/utils/hybrid_parallel_util.py
@@ -159,7 +159,7 @@ def broadcast_input_data(hcg, *inputs, **kwargs):
                     v_gpu._share_buffer_to(v)
                 _broadcast_data_help(v, v.shape, v.dtype, hcg)
         else:
-            logger.error("it doesn't support data type {}".format(type(v)))
+            logger.warning("it doesn't support data type {}".format(type(v)))
 
     for k, v in kwargs.items():
         if isinstance(v, (core.VarBase, core.eager.Tensor)):
@@ -171,7 +171,7 @@ def broadcast_input_data(hcg, *inputs, **kwargs):
                 _broadcast_data_help(v, v.shape, v.dtype, hcg)
             kwargs[k] = v
         else:
-            logger.error("it doesn't support data type {}".format(type(v)))
+            logger.warning("it doesn't support data type {}".format(type(v)))
     return inputs, kwargs