From 4113df0e211ae39724d2d76106a34a64df7e2ee5 Mon Sep 17 00:00:00 2001
From: Weixing Zhang <weixingzhang@users.noreply.github.com>
Date: Tue, 20 Sep 2022 14:34:33 -0700
Subject: [PATCH] use constexpr (#12953)

---
 .../orttraining/test/training_ops/cuda/layer_norm_test.cc | 8 ++++----
 .../orttraining/training_ops/cuda/nn/layer_norm.cc        | 4 ++--
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/orttraining/orttraining/test/training_ops/cuda/layer_norm_test.cc b/orttraining/orttraining/test/training_ops/cuda/layer_norm_test.cc
index 16aecafaad..9b6f2eceaa 100644
--- a/orttraining/orttraining/test/training_ops/cuda/layer_norm_test.cc
+++ b/orttraining/orttraining/test/training_ops/cuda/layer_norm_test.cc
@@ -101,7 +101,7 @@ TEST(CudaKernelTest, LayerNormGrad_SmallSizeTensor) {
 
 TEST(CudaKernelTest, LayerNormGrad_SmallSizeTensor_IntermediateAxis) {
   const std::vector<int64_t> X_dims{4, 20, 16, 8};
-  const int64_t axis = -2;
+  constexpr int64_t axis = -2;
   TestLayerNormGrad(X_dims, LAYER_NORM_GRAD_OP, axis);
 }
 
@@ -122,7 +122,7 @@ TEST(CudaKernelTest, SimplifiedLayerNormGrad_SmallSizeTensor) {
 
 TEST(CudaKernelTest, SimplifiedLayerNormGrad_SmallSizeTensor_IntermediateAxis) {
   const std::vector<int64_t> X_dims{4, 20, 16, 8};
-  const int64_t axis = -2;
+  constexpr int64_t axis = -2;
   TestLayerNormGrad(X_dims, SIMPLIFIED_LAYER_NORM_GRAD_OP, axis);
 }
 
@@ -239,7 +239,7 @@ TEST(CudaKernelTest, InvertibleLayerNormGrad_SmallSizeTensor) {
 
 TEST(CudaKernelTest, InvertibleLayerNormGrad_SmallSizeTensor_IntermediateAxis) {
   const std::vector<int64_t> X_dims{4, 20, 16, 8};
-  const int64_t axis = -2;
+  constexpr int64_t axis = -2;
   TestInvertibleLayerNormGrad(X_dims, axis);
 }
 
@@ -260,7 +260,7 @@ TEST(CudaKernelTest, InvertibleLayerNormGrad_SmallSizeTensor_FP16) {
 
 TEST(CudaKernelTest, InvertibleLayerNormGrad_SmallSizeTensor_IntermediateAxis_FP16) {
   const std::vector<int64_t> X_dims{4, 20, 16, 8};
-  const int64_t axis = -2;
+  constexpr int64_t axis = -2;
   TestInvertibleLayerNormGrad(X_dims, axis, 2e-3, true);
 }
 
diff --git a/orttraining/orttraining/training_ops/cuda/nn/layer_norm.cc b/orttraining/orttraining/training_ops/cuda/nn/layer_norm.cc
index 1d27bbd07d..c46b32791a 100644
--- a/orttraining/orttraining/training_ops/cuda/nn/layer_norm.cc
+++ b/orttraining/orttraining/training_ops/cuda/nn/layer_norm.cc
@@ -135,10 +135,10 @@ Status InvertibleLayerNormGrad<T, U, V>::ComputeInternal(OpKernelContext* p_op_k
   auto bias_grad_data = reinterpret_cast<CudaV*>(bias_grad->template MutableData<V>());
 
   #ifndef USE_ROCM
-  const int part_size = 16;
+  constexpr int part_size = 16;
   #else
   // Optimization for ROCm MI100
-  const int part_size = 64;
+  constexpr int part_size = 64;
   #endif
   auto part_grad_gamma = GetScratchBuffer<CudaU>(part_size * n2);
   auto part_grad_beta = GetScratchBuffer<CudaU>(part_size * n2);