diff --git a/mace/kernels/benchmark/batch_norm_benchmark.cc b/mace/kernels/benchmark/batch_norm_benchmark.cc
index a5e5279639dad37af4ed341068eeb74da3fd30ea..338255873861729b478fa9710a1eac67d29e265a 100644
--- a/mace/kernels/benchmark/batch_norm_benchmark.cc
+++ b/mace/kernels/benchmark/batch_norm_benchmark.cc
@@ -13,7 +13,7 @@ static void BatchNorm(int iters, int batch, int channels, int height, int width)
   std::mt19937 gen(rd());
   std::normal_distribution<float> nd(0, 1);
 
-  TIndex input_size = batch * channels * height * width;
+  index_t input_size = batch * channels * height * width;
   std::vector<T> input(input_size, 0.0);
   std::vector<T> scale(channels, 0.0);
   std::vector<T> offset(channels, 0.0);
@@ -50,7 +50,7 @@ static void BatchNorm(int iters, int batch, int channels, int height, int width)
 #define BM_BATCH_NORM_MACRO(N, C, H, W, TYPE, DEVICE)                  \
   static void BM_BATCH_NORM_##N##_##C##_##H##_##W##_##TYPE##_##DEVICE(  \
         int iters) {                                                    \
-    const int64 tot = static_cast<int64>(iters) * N * C * H * W;                        \
+    const int64_t tot = static_cast<int64_t>(iters) * N * C * H * W;                        \
     mace::testing::ItemsProcessed(tot);                                 \
     mace::testing::BytesProcessed(tot * (sizeof(TYPE)));\
     BatchNorm<DEVICE, TYPE>(iters, N, C, H, W);                         \
diff --git a/mace/kernels/test/batch_norm_neon_test.cc b/mace/kernels/test/batch_norm_neon_test.cc
index 32a6c1f9ad0c72c1c4ef54164e2613c3333f03cd..b33b316c109fe303d0e99e3e663f88712e0d770c 100644
--- a/mace/kernels/test/batch_norm_neon_test.cc
+++ b/mace/kernels/test/batch_norm_neon_test.cc
@@ -15,12 +15,12 @@ TEST(BatchNormNeonTest, Simple) {
   srand(time(NULL));
 
   // generate random input
-  TIndex batch = 1 + rand() % 128;
-  TIndex channels = 3;
-  TIndex height = 2 + rand() % 100;
-  TIndex width = 2 + rand() % 100;
+  index_t batch = 1 + rand() % 128;
+  index_t channels = 3;
+  index_t height = 2 + rand() % 100;
+  index_t width = 2 + rand() % 100;
 
-  TIndex input_size = batch * channels * height * width;
+  index_t input_size = batch * channels * height * width;
   std::vector<float> input(input_size, 0.0);
   std::vector<float> scale(channels, 0.0);
   std::vector<float> offset(channels, 0.0);
@@ -64,7 +64,7 @@ TEST(BatchNormNeonTest, Simple) {
           output_neon.get()
   );
 
-  for (TIndex i = 0; i < input_size; ++i) {
+  for (index_t i = 0; i < input_size; ++i) {
     EXPECT_FLOAT_EQ(output[i], output_neon[i]);
   }