fix the back outputs of BNTrainingUpdateV3 may cover the front whitch is empty

mindspore/ccsrc/pre_activate/ascend/ir_fission/single_batch_norm_fission.cc

@@ -23,42 +23,8 @@
 namespace mindspore {
 namespace opt {
 namespace {
-const std::vector<int> kOutputIndex{0, 1, 2, 3, 4};
-constexpr size_t kBatchNormLeastOutputNum = 1;
 constexpr size_t kBatchNormRealInputNum = 3;
 
-bool GetBatchNormOutputs(const FuncGraphPtr &func_graph, const AnfNodePtr &bn, std::vector<AnfNodePtr> *bn_outputs) {
-  MS_EXCEPTION_IF_NULL(func_graph);
-  MS_EXCEPTION_IF_NULL(bn_outputs);
-  auto manager = func_graph->manager();
-  MS_EXCEPTION_IF_NULL(manager);
-  auto iter = manager->node_users().find(bn);
-  if (iter == manager->node_users().end()) {
-    return false;
-  }
-  size_t output_num = 0;
-  for (const auto &node_index : iter->second) {
-    AnfNodePtr output = node_index.first;
-    MS_EXCEPTION_IF_NULL(output);
-    if (!IsPrimitiveCNode(output, prim::kPrimTupleGetItem)) {
-      continue;
-    }
-    auto tuple_getiterm_cnode = output->cast<CNodePtr>();
-    MS_EXCEPTION_IF_NULL(tuple_getiterm_cnode);
-    auto index_node = tuple_getiterm_cnode->input(kInputNodeOutputIndexInTupleGetItem);
-    MS_EXCEPTION_IF_NULL(index_node);
-    auto value_node = index_node->cast<ValueNodePtr>();
-    MS_EXCEPTION_IF_NULL(value_node);
-    int index = GetValue<int>(value_node->value());
-    if (std::find(kOutputIndex.begin(), kOutputIndex.end(), index) == kOutputIndex.end()) {
-      return false;
-    }
-    bn_outputs->push_back(output);
-    output_num++;
-  }
-  return output_num >= kBatchNormLeastOutputNum;
-}
-
 AnfNodePtr CreateBNTrainingReduce(const FuncGraphPtr &func_graph, const AnfNodePtr &bn) {
   MS_EXCEPTION_IF_NULL(func_graph);
   MS_EXCEPTION_IF_NULL(bn);
@@ -140,34 +106,12 @@ const AnfNodePtr SingleBatchNormFission::Process(const FuncGraphPtr &func_graph,
     MS_LOG(INFO) << "is training should be true if do fusion";
     return nullptr;
   }
-  std::vector<AnfNodePtr> bn_outputs;
-  if (!GetBatchNormOutputs(func_graph, node, &bn_outputs)) {
-    MS_LOG(INFO) << "The BatchNorm node should only have output 0, 3 and 4. The node should not be changed";
-    return nullptr;
-  }
   AnfNodePtr bn_training_reduce = CreateBNTrainingReduce(func_graph, node);
   std::vector<AnfNodePtr> bn_training_reduce_outputs;
   CreateMultipleOutputsOfAnfNode(func_graph, bn_training_reduce, kBNTrainingReduceOutputNum,
                                  &bn_training_reduce_outputs);
 
-  AnfNodePtr bn_training_update_v3 = CreateBNTrainingUpdateV3(func_graph, node, bn_training_reduce_outputs);
-  std::vector<AnfNodePtr> bn_training_update_v3_outputs;
-  CreateMultipleOutputsOfAnfNode(func_graph, bn_training_update_v3, kBNTrainingUpdateV3OutputNum,
-                                 &bn_training_update_v3_outputs);
-  if (bn_training_update_v3_outputs.size() != kBNTrainingUpdateV3OutputNum) {
-    MS_LOG(EXCEPTION) << "The output size of node bn_training_reduce must be " << kBNTrainingUpdateV2OutputNum
-                      << ", but it is " << bn_training_update_v3_outputs.size();
-  }
-  auto manager = func_graph->manager();
-  MS_EXCEPTION_IF_NULL(manager);
-  sort(bn_outputs.begin(), bn_outputs.end(), CompareTupleGetitem);
-  size_t output_index = 0;
-  for (const auto &output : bn_outputs) {
-    (void)manager->Replace(output, bn_training_update_v3_outputs[output_index]);
-    output_index++;
-  }
-  // Return the new node for control depends.
-  return bn_training_update_v3;
+  return CreateBNTrainingUpdateV3(func_graph, node, bn_training_reduce_outputs);
 }
 }  // namespace opt
 }  // namespace mindspore