diff --git a/mindspore/ccsrc/pipeline/pynative/pynative_execute.cc b/mindspore/ccsrc/pipeline/pynative/pynative_execute.cc
index f7e264555c9..d1946e7a0d3 100644
--- a/mindspore/ccsrc/pipeline/pynative/pynative_execute.cc
+++ b/mindspore/ccsrc/pipeline/pynative/pynative_execute.cc
@@ -269,9 +269,13 @@ void PynativeInfer(const PrimitivePyPtr &prim, const py::list &py_args, OpExecIn
   MS_LOG(DEBUG) << "Prim " << prim->name() << " infer result " << op_exec_info->abstract->ToString();
 }
 
-std::string GetSingleOpGraphInfo(const OpExecInfoPtr &op_exec_info,
-                                 const std::vector<tensor::TensorPtr> &input_tensors) {
+std::string GetSingleOpGraphInfo(const OpExecInfoPtr &op_exec_info, const std::vector<tensor::TensorPtr> &input_tensors,
+                                 const std::vector<int64_t> &tensors_mask) {
   MS_EXCEPTION_IF_NULL(op_exec_info);
+  if (input_tensors.size() != tensors_mask.size()) {
+    MS_LOG(EXCEPTION) << "Input tensors size " << input_tensors.size() << " should be equal to tensors mask size "
+                      << tensors_mask.size();
+  }
   std::string graph_info;
   // get input tensor info
   for (size_t index = 0; index < input_tensors.size(); ++index) {
@@ -292,7 +296,7 @@ std::string GetSingleOpGraphInfo(const OpExecInfoPtr &op_exec_info,
       (void)graph_info.append(std::dynamic_pointer_cast<device::DeviceAddress>(tensor_addr)->format());
       graph_info += "_";
     }
-    if (static_cast<int64_t>(op_exec_info->inputs_mask[index]) == kValueNodeTensorMask) {
+    if (tensors_mask[index] == kValueNodeTensorMask) {
       if (input_tensors[index]->Dtype()->type_id() == kNumberTypeInt64) {
         (void)graph_info.append(std::to_string(*reinterpret_cast<int *>(input_tensors[index]->data_c())));
         graph_info += "_";
@@ -1503,7 +1507,7 @@ py::object ForwardExecutor::RunOpInMs(const OpExecInfoPtr &op_exec_info, Pynativ
   ConstructInputTensor(op_exec_info, &tensors_mask, &input_tensors);
   ConvertAttrToUnifyMindIR(op_exec_info);
   // get graph info for checking it whether existing in the cache
-  std::string graph_info = GetSingleOpGraphInfo(op_exec_info, input_tensors);
+  std::string graph_info = GetSingleOpGraphInfo(op_exec_info, input_tensors, tensors_mask);
 #if defined(__APPLE__)
   session::OpRunInfo op_run_info = {op_exec_info->op_name,
                                     op_exec_info->py_primitive,
diff --git a/tests/st/networks/test_gpu_lenet.py b/tests/st/networks/test_gpu_lenet.py
index 325c2bf4948..c732ad44bfe 100644
--- a/tests/st/networks/test_gpu_lenet.py
+++ b/tests/st/networks/test_gpu_lenet.py
@@ -230,5 +230,5 @@ def test_train_lenet_with_new_interface(num_classes=10, epoch=20, batch_size=32)
         grads = F.identity(grads)
         optimizer(grads)
         losses.append(loss)
-    assert losses[-1].asnumpy() < 0.008
+    assert losses[-1].asnumpy() < 0.01
     assert losses[-1].asnumpy() > 0.001