change manager logic to faster combine_like step

mindspore/ccsrc/pipeline/action.cc

@@ -130,7 +130,7 @@ bool ParseAction(const ResourcePtr &res) {
 // This step do this optimize: graph1(x){xx(fv1),xxx(fv2)}, graph2(x){xxx(fv3),xxx(fv4)}->
 // graph1(x){base_graph(x, fv1, fv2)}, graph1(x){base_graph(x, fv3, fv4)}, base_graph(x, fv...){xxx,xxx}
 // all obj_map's graph shared base_graph
-bool CombineLikeGraphs(const ResourcePtr &) {
+bool CombineLikeGraphs(const ResourcePtr &res) {
   auto &obj_map = parse::data_converter::GetObjGraphs();
 
   for (auto it : obj_map) {
@@ -147,13 +147,15 @@ bool CombineLikeGraphs(const ResourcePtr &) {
     if (fg->paramter_obj_nodes().size() == 0 || graphs.size() <= 1) {
       continue;
     }
-    auto mng = Manage(base_graph, false);
     for (auto &fv : fg->paramter_obj_nodes()) {
       TraceManager::DebugTrace(std::make_shared<TraceCombileLikeGraphs>(fv->debug_info()));
       auto param = base_graph->add_parameter();
       TraceManager::EndTrace();
-      auto repl_node = (*cloner->cloned_node())[fv];
-      (void)mng->Replace(repl_node, param);
+      auto &node_users = res->manager()->node_users()[fv];
+      for (auto &n : node_users) {
+        auto repl_n = (*cloner->cloned_node())[n.first]->cast<CNodePtr>();
+        repl_n->set_input(n.second, param);
+      }
     }
     MS_LOG(DEBUG) << "Fg0 paramter_obj_nodes size :" << fg->paramter_obj_nodes().size();
 

tests/st/control/test_multigraph_sink.py

@@ -24,9 +24,7 @@ from mindspore.ops import operations as P
 
 
 def setup_module(module):
-    context.set_context(mode = context.PYNATIVE_MODE, save_graphs = True, device_target = "Ascend")
-    context.set_context(enable_task_sink = True, device_id = 0)
-
+    context.set_context(mode = context.PYNATIVE_MODE, device_target = "Ascend")
 
 c1 = Tensor([2], mstype.int32)
 c2 = Tensor([14], mstype.int32)
@@ -135,6 +133,10 @@ def while_in_while_in_while(x, y, z):
     return out
 
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_onecard
 def test_simple_if():
     output = simple_if(c1, c2, c3)
     expect = Tensor([6], mstype.int32)
@@ -153,30 +155,49 @@ def test_if_in_if():
     assert output == expect
 
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_onecard
 def test_simple_while():
     output = simple_while(c1, c2, c3)
     expect = Tensor([21], mstype.int32)
     assert output == expect
 
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_onecard
 def test_while_by_while():
     output = while_by_while(c1, c2, c3)
     expect = Tensor([28], mstype.int32)
     assert output == expect
 
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_onecard
 def test_while_in_while():
     output = while_in_while(c1, c2, c3)
     expect = Tensor([1274], mstype.int32)
     assert output == expect
 
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_onecard
 def test_while_by_while_in_while():
     output = while_by_while_in_while(c1, c2, c3)
     expect = Tensor([350], mstype.int32)
     assert output == expect
 
-
+@pytest.mark.level0
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_onecard
 def test_while_in_while_in_while():
     output = while_in_while_in_while(c1, c2, c3)
     expect = Tensor([2534], mstype.int32)