diff --git a/mindspore/ccsrc/pre_activate/ascend/ir_fission/bn_split.cc b/mindspore/ccsrc/pre_activate/ascend/ir_fission/bn_split.cc
index c8d92f7200f2b5adf9441c1ee01c6617cdbe7cf3..66ffa24bf122fd78b38c9d8f482d9a1e3db7cf6b 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ir_fission/bn_split.cc
+++ b/mindspore/ccsrc/pre_activate/ascend/ir_fission/bn_split.cc
@@ -28,14 +28,14 @@
 namespace mindspore {
 namespace opt {
 namespace {
-void CreateOutputsOfBNTrainingReduce(const FuncGraphPtr &graph, const CNodePtr &bn_cnode,
+bool CreateOutputsOfBNTrainingReduce(const FuncGraphPtr &graph, const CNodePtr &bn_cnode,
                                      std::vector<AnfNodePtr> *bn_training_reduce_outputs) {
   MS_EXCEPTION_IF_NULL(graph);
   MS_EXCEPTION_IF_NULL(bn_cnode);
   if (bn_cnode->inputs().size() != kBnInputNum) {
-    MS_LOG(EXCEPTION) << "BN node has wrong input size";
+    MS_LOG(INFO) << "FusedbatchNorm's input size less than " << kBnInputNum << ". " << bn_cnode->DebugString();
+    return false;
   }
-  // All the inputs of BNTrainingReduce are from the inputs of BN
   std::vector<AnfNodePtr> bn_training_reduce_inputs = {
     NewValueNode(std::make_shared<Primitive>(kBNTrainingReduceOpName))};
   bn_training_reduce_inputs.push_back(bn_cnode->input(1));
@@ -45,8 +45,9 @@ void CreateOutputsOfBNTrainingReduce(const FuncGraphPtr &graph, const CNodePtr &
   MS_EXCEPTION_IF_NULL(kernel_info);
   bn_training_reduce->set_kernel_info(kernel_info);
   std::vector<size_t> bn_shape_i0 = AnfAlgo::GetPrevNodeOutputInferShape(bn_cnode, 0);
-  if (bn_shape_i0.size() != kShape4dDims) {
-    MS_LOG(EXCEPTION) << "Get shape of FusedBatchNorm fail";
+  if (bn_shape_i0.size() < kShape2dDims) {
+    MS_LOG(INFO) << "The FusedBatchNorm's first input's shape dims less than " << kShape2dDims;
+    return false;
   }
   std::vector<size_t> bn_training_reduce_shape = {bn_shape_i0[1]};
   auto types = {kNumberTypeFloat32, kNumberTypeFloat32};
@@ -56,6 +57,7 @@ void CreateOutputsOfBNTrainingReduce(const FuncGraphPtr &graph, const CNodePtr &
   AnfAlgo::CopyNodeAttrs(bn_cnode, bn_training_reduce);
 
   CreateMultipleOutputsOfAnfNode(graph, bn_training_reduce, kBNTrainingReduceOutputNum, bn_training_reduce_outputs);
+  return true;
 }
 
 AnfNodePtr CreateOutputsOfBNTrainingUpdate(const FuncGraphPtr &graph, const CNodePtr &bn_cnode,
@@ -99,11 +101,15 @@ AnfNodePtr SplitFusedBatchNormForTBE(const FuncGraphPtr &func_graph, const AnfNo
   auto cnode = node->cast<CNodePtr>();
   MS_EXCEPTION_IF_NULL(cnode);
   if (cnode->inputs().size() < kBnInputNum) {
-    MS_LOG(EXCEPTION) << "op[FusedBatchNorm] has less than " << kBnInputNum << " inputs.";
+    MS_LOG(INFO) << "op[FusedBatchNorm] has less than " << kBnInputNum << " inputs.";
+    return nullptr;
   }
   // Create BNTrainingReduce node and get outputs of BNTrainingReduce
   std::vector<AnfNodePtr> bn_training_reduce_outputs;
-  CreateOutputsOfBNTrainingReduce(func_graph, cnode, &bn_training_reduce_outputs);
+  if (!CreateOutputsOfBNTrainingReduce(func_graph, cnode, &bn_training_reduce_outputs)) {
+    MS_LOG(WARNING) << "Create BNTrainingReduce fail, quit split";
+    return nullptr;
+  }
   if (bn_training_reduce_outputs.size() != kBN1OutputNum) {
     MS_LOG(EXCEPTION) << "make outputs of op BNTrainingReduce fail";
   }