diff --git a/onnxruntime/contrib_ops/cpu/skip_layer_norm.cc b/onnxruntime/contrib_ops/cpu/skip_layer_norm.cc
index b84635d082..6119bc20ee 100644
--- a/onnxruntime/contrib_ops/cpu/skip_layer_norm.cc
+++ b/onnxruntime/contrib_ops/cpu/skip_layer_norm.cc
@@ -98,36 +98,38 @@ Status SkipLayerNorm<T>::Compute(OpKernelContext* p_ctx) const {
 
   T* output_data = output->MutableData<T>();
 
-  concurrency::ThreadPool::TryBatchParallelFor(p_ctx->GetOperatorThreadPool(), static_cast<int32_t>(task_count),
-                                               [&](ptrdiff_t task_idx) {
-                                                 const T* p_input = input_data + task_idx * hidden_size;
-                                                 const T* p_skip = skip_data + task_idx * hidden_size;
-                                                 T* p_output = output_data + task_idx * hidden_size;
+  concurrency::ThreadPool::TryBatchParallelFor(
+      p_ctx->GetOperatorThreadPool(), static_cast<int32_t>(task_count),
+      [&](ptrdiff_t task_idx) {
+        const T* p_input = input_data + task_idx * hidden_size;
+        const T* p_skip = skip_data + task_idx * hidden_size;
+        T* p_output = output_data + task_idx * hidden_size;
 
-                                                 T mean = 0;
-                                                 T mean_square = 0;
+        T mean = 0;
+        T mean_square = 0;
 
-                                                 for (int64_t h = 0; h < hidden_size; h++) {
-                                                   T value = p_input[h] + p_skip[h];
-                                                   if (nullptr != bias_data) {
-                                                     value += bias_data[h];
-                                                   }
-                                                   p_output[h] = value;
-                                                   mean += value;
-                                                   mean_square += value * value;
-                                                 }
+        for (int64_t h = 0; h < hidden_size; h++) {
+          T value = p_input[h] + p_skip[h];
+          if (nullptr != bias_data) {
+            value += bias_data[h];
+          }
+          p_output[h] = value;
+          mean += value;
+          mean_square += value * value;
+        }
 
-                                                 mean = mean / hidden_size;
-                                                 mean_square = sqrt(mean_square / hidden_size - mean * mean + epsilon_);
+        mean = mean / hidden_size;
+        mean_square = sqrt(mean_square / hidden_size - mean * mean + epsilon_);
 
-                                                 for (int64_t h = 0; h < hidden_size; h++) {
-                                                   if (nullptr == beta_data) {
-                                                     p_output[h] = (p_output[h] - mean) / mean_square * gamma_data[h];
-                                                   } else {
-                                                     p_output[h] = (p_output[h] - mean) / mean_square * gamma_data[h] + beta_data[h];
-                                                   }
-                                                 }
-                                               }, 0);
+        for (int64_t h = 0; h < hidden_size; h++) {
+          if (nullptr == beta_data) {
+            p_output[h] = (p_output[h] - mean) / mean_square * gamma_data[h];
+          } else {
+            p_output[h] = (p_output[h] - mean) / mean_square * gamma_data[h] + beta_data[h];
+          }
+        }
+      },
+      0);
 
   return Status::OK();
 }