diff --git a/paddle/phi/kernels/gpu/gaussian_random_kernel.cu b/paddle/phi/kernels/gpu/gaussian_random_kernel.cu
index d5acc60a36097f02c579671860c0b480199ae09a..da16800ad02af19c19f8d0fd4f776739324e5959 100644
--- a/paddle/phi/kernels/gpu/gaussian_random_kernel.cu
+++ b/paddle/phi/kernels/gpu/gaussian_random_kernel.cu
@@ -81,22 +81,25 @@ void GaussianRandomKernel(const Context& dev_ctx,
   int device_id = dev_ctx.GetPlace().GetDeviceId();
   auto gen_cuda = paddle::framework::GetDefaultCUDAGenerator(device_id);
 
-  using MT = typename phi::kps::details::MPTypeTrait<T>::Type;
   if (gen_cuda->GetIsInitPy() && seed_flag) {
     if (FLAGS_use_curand) {
+      using MT = typename phi::kps::details::MPTypeTrait<T>::Type;
       funcs::normal_distribution<MT> dist;
       funcs::normal_transform<MT> trans(mean, std);
       funcs::distribution_and_transform<T>(dev_ctx, tensor, dist, trans);
     } else {
       auto seed_offset = gen_cuda->IncrementOffset(1);
       int64_t gen_offset = size * seed_offset.second;
-      auto func =
-          GaussianGenerator<MT>(mean, std, seed_offset.first, gen_offset);
-      IndexKernel<T, GaussianGenerator<MT>>(dev_ctx, tensor, func);
+      auto func = GaussianGenerator<T>(static_cast<T>(mean),
+                                       static_cast<T>(std),
+                                       seed_offset.first,
+                                       gen_offset);
+      IndexKernel<T, GaussianGenerator<T>>(dev_ctx, tensor, func);
     }
   } else {
-    auto func = GaussianGenerator<MT>(mean, std, seed);
-    IndexKernel<T, GaussianGenerator<MT>>(dev_ctx, tensor, func);
+    auto func =
+        GaussianGenerator<T>(static_cast<T>(mean), static_cast<T>(std), seed);
+    IndexKernel<T, GaussianGenerator<T>>(dev_ctx, tensor, func);
   }
 }