diff --git a/mindinsight/mindconverter/graph_based_converter/constant.py b/mindinsight/mindconverter/graph_based_converter/constant.py
index cc7ee4bc..0f6dfe85 100644
--- a/mindinsight/mindconverter/graph_based_converter/constant.py
+++ b/mindinsight/mindconverter/graph_based_converter/constant.py
@@ -27,7 +27,7 @@ FIRST_LEVEL_INDENT = BLANK_SYM * 4
 SECOND_LEVEL_INDENT = BLANK_SYM * 8
 NEW_LINE = "\n"
 
-MINI_FREQUENCEY = 4
+MINI_FREQUENCY = 4
 
 ONNX_TYPE_INT = 2
 ONNX_TYPE_INTS = 7
diff --git a/mindinsight/mindconverter/graph_based_converter/sub_graph_searcher/searcher.py b/mindinsight/mindconverter/graph_based_converter/sub_graph_searcher/searcher.py
index 8eb6e256..1e935e7f 100644
--- a/mindinsight/mindconverter/graph_based_converter/sub_graph_searcher/searcher.py
+++ b/mindinsight/mindconverter/graph_based_converter/sub_graph_searcher/searcher.py
@@ -17,13 +17,10 @@ from queue import PriorityQueue
 from typing import Dict, List
 
 from .common import context, DagGraph, gen_hash_key
-from ..constant import MINI_FREQUENCEY
+from ..constant import MINI_FREQUENCY
 from ..third_party_graph.onnx_utils import BaseNode
 from .search_path import SearchPath, Pattern, generate_pattern
 
-# Hold module name of current graph.
-module_name_mgr = dict()
-
 
 def _is_satisfied(path):
     """
@@ -81,7 +78,7 @@ def _search(init_pattern: Dict[str, Pattern], init_topo_order: List[BaseNode],
             break
 
         for _, cur_pattern in cur_path.new_pattern.items():
-            if cur_pattern.count < MINI_FREQUENCEY:
+            if cur_pattern.count < MINI_FREQUENCY:
                 available_path.append(cur_path)
                 break
             key = "/".join([cur_pattern.pattern, gen_hash_key(cur_topo_order)])
@@ -130,6 +127,8 @@ def _retrieve_scope_name(found_path):
     Args:
         found_path: Found path.
     """
+    module_name_mgr = dict()
+
     module_dict = dict()
     for module_path in found_path.recursion_path:
         key, val = _retrieve_operators(module_path, module_dict)
@@ -142,29 +141,31 @@ def _retrieve_scope_name(found_path):
     for node in found_path.topo_order_aft_repl:
         if module_dict.get(node.op_type):
             topo_order_with_scope_name += [f"Model/{item}" for item in _scope_name_deduplication(
-                node.op_type, module_dict[node.op_type])]
+                node.op_type, module_dict[node.op_type], module_name_mgr)]
         else:
             topo_order_with_scope_name.append(f"Model/{node.op_type}")
     return topo_order_with_scope_name
 
 
-def _scope_name_deduplication(key, scope_names) -> list:
+def _scope_name_deduplication(key, scope_names, memo) -> list:
     """
     Scope name deduplication.
 
     Args:
+        key (str): Module name.
         scope_names (list): Scope names.
+        memo (dict): Memo to record module name.
 
     Returns:
         list, renamed scope name.
     """
     result = []
-    if key not in module_name_mgr:
-        module_name_mgr[key] = 0
+    if key not in memo:
+        memo[key] = 0
     for item in scope_names:
-        item = item.replace(key, f"{key}_{module_name_mgr.get(key)}")
+        item = item.replace(key, f"{key}_{memo.get(key)}")
         result.append(item)
-    module_name_mgr[key] += 1
+    memo[key] += 1
     return result
 
 
@@ -179,12 +180,14 @@ def _retrieve_operators(module_path, module_dict):
     Returns:
         str: module_name, operators in module.
     """
-    global module_name_mgr
+    added_module = dict()
     node_in_pattern = module_path.pattern.pattern.split('->')
     node_list = []
     for node in node_in_pattern:
         if module_dict.get(node):
-            node_list += module_dict[node]
+            node_list += _scope_name_deduplication(node,
+                                                   module_dict[node],
+                                                   added_module)
         else:
             node_list.append(node)
     key = module_path.pattern.module_name