diff --git a/mindspore/lite/nnacl/fp32_grad/batch_norm.c b/mindspore/lite/nnacl/fp32_grad/batch_norm.c
index bee4bf433d..a6d2b20ed8 100644
--- a/mindspore/lite/nnacl/fp32_grad/batch_norm.c
+++ b/mindspore/lite/nnacl/fp32_grad/batch_norm.c
@@ -33,13 +33,13 @@ static void meanVar(const float *in, int size, int ch, float eps, float *mean, f
   for (int f = 0; f < ch; ++f) {
     mean[f] /= N;
   }
-  for (int f=0; f< ch; f++) {
+  for (int f = 0; f < ch; f++) {
     float tvar = 0;
-    for (int i =0; i< N; i++) {
-      float x = in[i*ch +f];
-      tvar += (x-mean[f]) *(x-mean[f]);
+    for (int i = 0; i < N; i++) {
+      float x = in[i * ch + f];
+      tvar += (x - mean[f]) * (x - mean[f]);
     }
-    invar[f] = 1.0f/(sqrt(tvar/N+eps));
+    invar[f] = 1.0f / (sqrt(tvar / N + eps));
   }
 }
 
diff --git a/mindspore/lite/nnacl/fp32_grad/softmax_grad.c b/mindspore/lite/nnacl/fp32_grad/softmax_grad.c
index 8e21a02909..21bcc14188 100644
--- a/mindspore/lite/nnacl/fp32_grad/softmax_grad.c
+++ b/mindspore/lite/nnacl/fp32_grad/softmax_grad.c
@@ -39,9 +39,9 @@ void SoftmaxGrad(const float *input_ptr, const float *yt_ptr, float *output_ptr,
   dim /= outter_size;
   memcpy(output_ptr, yt_ptr, ele_size * sizeof(float));
 
-  int M = input_shape[axis];
-  int N = inner_size;
-  int K = 1;
+  const int M = input_shape[axis];
+  const int N = inner_size;
+  const int K = 1;
   for (int i = 0; i < outter_size; i++) {
     int outter_offset = i * dim;
     memset(sum_data, 0.0f, inner_size * sizeof(float));
diff --git a/mindspore/lite/src/executor.cc b/mindspore/lite/src/executor.cc
index fcd53a46a1..62948814bb 100644
--- a/mindspore/lite/src/executor.cc
+++ b/mindspore/lite/src/executor.cc
@@ -51,6 +51,7 @@ int Executor::Run(std::vector<Tensor *> &in_tensors, std::vector<Tensor *> &out_
         MS_LOG(ERROR) << "run kernel before_callback failed, name: " << kernel->name();
       }
     }
+
     auto ret = kernel->Run();
     if (0 != ret) {
       MS_LOG(ERROR) << "run kernel failed, name: " << kernel->name();