miss format (#34771)

paddle/fluid/operators/math/bert_encoder_functor.cu

@@ -25,6 +25,14 @@ namespace paddle {
 namespace operators {
 namespace math {
 
+template <typename T>
+__device__ __forceinline__ T local_rsqrt(T num) {
+  return rsqrt(static_cast<float>(num));
+}
+#if CUDA_ARCH_FP16_SUPPORTED(__CUDA_ARCH__)
+__device__ __forceinline__ half local_rsqrt(half num) { return hrsqrt(num); }
+#endif
+
 template <typename T, int TPB>
 __device__ inline void LayerNormSmall(T val, const kvp<T> &thread_data,
                                       const int ld, const int idx,
@@ -39,7 +47,7 @@ __device__ inline void LayerNormSmall(T val, const kvp<T> &thread_data,
 
   if (threadIdx.x == 0) {
     mu = sum_kv.key;
-    rsigma = rsqrt(sum_kv.value - mu * mu + eps);
+    rsigma = local_rsqrt(sum_kv.value - mu * mu + eps);
   }
   __syncthreads();
 
@@ -63,7 +71,7 @@ __device__ inline void LayerNorm(const kvp<T> &thread_data, const int ld,
 
   if (threadIdx.x == 0) {
     mu = sum_kv.key;
-    rsigma = rsqrt(sum_kv.value - mu * mu + eps);
+    rsigma = local_rsqrt(sum_kv.value - mu * mu + eps);
   }
   __syncthreads();
 
@@ -89,7 +97,7 @@ __device__ inline void LayerNorm2(const kvp<T> &thread_data, const int ld,
 
   if (threadIdx.x == 0) {
     mu = sum_kv.key;
-    rsigma = rsqrt(sum_kv.value - mu * mu + eps);
+    rsigma = local_rsqrt(sum_kv.value - mu * mu + eps);
   }
   __syncthreads();