diff --git a/mindspore/ccsrc/kernel/hccl/hccl_kernel_metadata.cc b/mindspore/ccsrc/kernel/hccl/hccl_kernel_metadata.cc
index 601d5cf1ea1b40c86e767963cecaa59708f74b57..bfd13275486f8d98b9c7c9da0829792f96f05624 100755
--- a/mindspore/ccsrc/kernel/hccl/hccl_kernel_metadata.cc
+++ b/mindspore/ccsrc/kernel/hccl/hccl_kernel_metadata.cc
@@ -16,12 +16,30 @@
 
 #include "kernel/hccl/hccl_kernel_metadata.h"
 #include <memory>
+#include <set>
 #include "utils/utils.h"
 #include "kernel/hccl/hcom_util.h"
 #include "session/anf_runtime_algorithm.h"
 
 namespace mindspore {
 namespace kernel {
+namespace {
+std::string GetKernelFormat(const CNodePtr &kernel_node, size_t index) {
+  const std::set<std::string> kReduceNoSupportedSet = {kOpFormat_FRAC_Z, kOpFormat_FRACTAL_Z_C04, kOpFormat_C1HWNCoC0};
+  auto op_name = AnfAlgo::GetCNodeName(kernel_node);
+  auto format = AnfAlgo::GetPrevNodeOutputFormat(kernel_node, index);
+  if (op_name != kReduceScatter && op_name != kAllGatherOpName) {
+    return format;
+  }
+  if (format == kOpFormat_FRAC_NZ && AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, index).size() <= 2) {
+    return kOpFormat_DEFAULT;
+  }
+  if (kReduceNoSupportedSet.find(format) != kReduceNoSupportedSet.end()) {
+    return kOpFormat_DEFAULT;
+  }
+  return format;
+}
+}  // namespace
 void HcclMetadataInfo(const CNodePtr &kernel_node, std::vector<std::shared_ptr<KernelBuildInfo>> *kernel_info_list) {
   const std::vector<TypeId> kHcclSupportTypes = {kNumberTypeInt8, kNumberTypeInt32, kNumberTypeFloat16,
                                                  kNumberTypeFloat32, kNumberTypeInt16};
@@ -36,13 +54,13 @@ void HcclMetadataInfo(const CNodePtr &kernel_node, std::vector<std::shared_ptr<K
     std::vector<std::string> inputs_format{};
     std::vector<TypeId> inputs_type{};
     for (size_t input_index = 0; input_index < AnfAlgo::GetInputTensorNum(kernel_node); ++input_index) {
-      inputs_format.emplace_back(AnfAlgo::GetPrevNodeOutputFormat(kernel_node, input_index));
+      inputs_format.emplace_back(GetKernelFormat(kernel_node, input_index));
       inputs_type.push_back(type);
     }
     std::vector<std::string> outputs_format;
     std::vector<TypeId> outputs_type;
     for (size_t output_index = 0; output_index < AnfAlgo::GetOutputTensorNum(kernel_node); ++output_index) {
-      outputs_format.emplace_back(AnfAlgo::GetPrevNodeOutputFormat(kernel_node, output_index));
+      outputs_format.emplace_back(GetKernelFormat(kernel_node, output_index));
       outputs_type.push_back(type);
     }
     auto builder = KernelBuildInfo::KernelBuildInfoBuilder();
diff --git a/tests/st/pynative/test_pynative_resnet50.py b/tests/st/pynative/test_pynative_resnet50.py
index 21d761dfcc0c5f103ea8c1b7846028e66317c3b9..de9ecebb9cfa5619387dcbe5a7d4a098b945359d 100644
--- a/tests/st/pynative/test_pynative_resnet50.py
+++ b/tests/st/pynative/test_pynative_resnet50.py
@@ -428,5 +428,5 @@ def test_pynative_resnet50():
         cost_time = end_time - start_time
         print("======step: ", step, " loss: ", loss_output.asnumpy(), " cost time: ", cost_time)
         if step > 1:
-            assert cost_time < 0.5
+            assert cost_time < 0.3
         
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