diff --git a/tf_adapter/python/npu_bridge/embedding/embedding_service.py b/tf_adapter/python/npu_bridge/embedding/embedding_service.py
index b109301e70b05c79f8334d588d6457a2315fddf9..79fb15aaefa8e381b530b7ba199a45a5f089e6fa 100644
--- a/tf_adapter/python/npu_bridge/embedding/embedding_service.py
+++ b/tf_adapter/python/npu_bridge/embedding/embedding_service.py
@@ -469,7 +469,7 @@ class ESWorker:
     # @param name str 类型
     # @param ids int64 类型
     # @return values float32 类型
-    def embedding_lookup_v2(self, name: str, ids: typing.Any):
+    def embedding_lookup(self, name: str, ids: typing.Any):
         """ Operator for look up in embedding table. """
         if (name is None) or (ids is None):
             raise ValueError("table name or ids must be specified.")
@@ -536,7 +536,7 @@ class ESWorker:
     # @param table_id int32 类型
     # @param input_ids int64 类型
     # @return values float32 类型
-    def embedding_lookup(self, table_id: int, input_ids: typing.Any):
+    def embedding_lookup_v1(self, table_id: int, input_ids: typing.Any):
         """ Operator for look up in embedding table. """
         if (table_id is None) or (input_ids is None):
             raise ValueError("table_id or input_ids must be specified.")
@@ -598,7 +598,7 @@ class ESWorker:
     # new version
     # 提供embedding update功能
     # @param loss 类型
-    def embedding_update_v2(self, loss):
+    def embedding_update(self, loss):
         """ Operator for update in embedding table. """
         params = self._ps_table_lookup_result
         input_ids_list = self._ps_table_lookup_key
@@ -640,7 +640,7 @@ class ESWorker:
     # @param params float32 类型
     # @param table_ids int32 类型
     # @param input_ids_list int64 类型
-    def embedding_update(self, loss, params, table_ids, input_ids_list):
+    def embedding_update_v1(self, loss, params, table_ids, input_ids_list):
         """ Operator for update in embedding table. """
         if (loss is None) or (params is None) or (table_ids is None) or (input_ids_list is None):
             raise ValueError("loss or params or table_ids or input_ids_list is None.")
@@ -809,7 +809,7 @@ class ESWorker:
                 output_slots[sid] = out_emb
         return output_slots
 
-    def save_embedding_v2(self, name: str, path: str):
+    def save_embedding(self, name: str, path: str):
         """ Operator for save values in table_id embedding table. """
         if path is None or name is None:
             raise ValueError("table name, embedding table path can not be None.")
@@ -873,7 +873,7 @@ class ESWorker:
                                                        table_name=self._ps_table_name_list)
             return tf.group([embedding_table_export])
 
-    def restore_embedding_v2(self, name: str, path: str):
+    def restore_embedding(self, name: str, path: str):
         if path is None or name is None:
             raise ValueError("table name, embedding table path can not be None.")
         if path[-1] == '/':
@@ -919,7 +919,7 @@ class ESWorker:
                                                        table_name=self._ps_table_name_list)
             return tf.group([embedding_table_import])
 
-    def save_checkpoint_v2(self, name: str, path: str):
+    def save_checkpoint(self, name: str, path: str):
         """ Operator for save values and optimizer params in table_id embedding table. """
         if path is None or name is None:
             raise ValueError("table name, embedding table path can not be None.")
@@ -1000,7 +1000,7 @@ class ESWorker:
                                                                  table_name=self._ps_table_name_list)
                 return tf.group([embedding_compute_var_export])
 
-    def restore_checkpoint_v2(self, name: str, path: str):
+    def restore_checkpoint(self, name: str, path: str):
         """ Operator for restore values and optimizer params in table_id embedding table. """
         if path is None or name is None:
             raise ValueError("name, embedding table path can not be None.")
@@ -1069,7 +1069,7 @@ class ESWorker:
                                                                  table_name=self._ps_table_name_list)
                 return tf.group([embedding_compute_var_import])
 
-    def save_incremental_embedding_v2(self, name: str, path: str):
+    def save_incremental_embedding(self, name: str, path: str):
         """ Operator for save incremental values in table_id embedding table. """
         if path is None or name is None:
             raise ValueError("table name, embedding table path can not be None.")
@@ -1133,7 +1133,7 @@ class ESWorker:
                                                        table_name=self._ps_table_name_list)
             return tf.group([embedding_table_export])
 
-    def restore_incremental_embedding_v2(self, name: str, path: str):
+    def restore_incremental_embedding(self, name: str, path: str):
         if path is None or name is None:
             raise ValueError("table name, embedding table path can not be None.")
         if path[-1] == '/':
@@ -1180,7 +1180,7 @@ class ESWorker:
             return tf.group([embedding_table_import])
 
     # old version
-    def save_embedding(self, path: str, table_id: int):
+    def save_embedding_v1(self, path: str, table_id: int):
         """ Operator for save values in table_id embedding table. """
         if path is None or table_id is None:
             raise ValueError("table_id, embedding table path can not be None.")
@@ -1210,7 +1210,7 @@ class ESWorker:
                                                        table_name=[self._table_id_to_name.get(table_id)])
             return tf.group([embedding_table_export])
 
-    def restore_embedding(self, path: str, table_id: int):
+    def restore_embedding_v1(self, path: str, table_id: int):
         if path is None or table_id is None:
             raise ValueError("table_id, embedding table path can not be None.")
         if path[-1] == '/':
@@ -1231,7 +1231,7 @@ class ESWorker:
                                                        table_name=[self._table_id_to_name.get(table_id)])
             return tf.group([embedding_table_import])
 
-    def save_checkpoint(self, path: str, table_id: int):
+    def save_checkpoint_v1(self, path: str, table_id: int):
         """ Operator for save values and optimizer params in table_id embedding table. """
         if path is None or table_id is None:
             raise ValueError("table_id, embedding table path can not be None.")
@@ -1269,7 +1269,7 @@ class ESWorker:
                                                                  table_name=[self._table_id_to_name.get(table_id)])
                 return tf.group([embedding_compute_var_export])
 
-    def restore_checkpoint(self, path: str, table_id: int):
+    def restore_checkpoint_v1(self, path: str, table_id: int):
         """ Operator for restore values and optimizer params in table_id embedding table. """
         if path is None or table_id is None:
             raise ValueError("table_id, embedding table path can not be None.")
@@ -1302,7 +1302,7 @@ class ESWorker:
                                                                  table_name=[self._table_id_to_name.get(table_id)])
                 return tf.group([embedding_compute_var_import])
 
-    def save_incremental_embedding(self, path: str, table_id: int):
+    def save_incremental_embedding_v1(self, path: str, table_id: int):
         """ Operator for save incremental values in table_id embedding table. """
         if path is None or table_id is None:
             raise ValueError("table_id, embedding table path can not be None.")
@@ -1332,7 +1332,7 @@ class ESWorker:
                                                        table_name=[self._table_id_to_name.get(table_id)])
             return tf.group([embedding_table_export])
 
-    def restore_incremental_embedding(self, path: str, table_id: int):
+    def restore_incremental_embedding_v1(self, path: str, table_id: int):
         if path is None or table_id is None:
             raise ValueError("table_id, embedding table path can not be None.")
         if path[-1] == '/':