diff --git a/aten/src/ATen/core/PhiloxRNGEngine.h b/aten/src/ATen/core/PhiloxRNGEngine.h
index 413055d3fad6..e8bac545933c 100644
--- a/aten/src/ATen/core/PhiloxRNGEngine.h
+++ b/aten/src/ATen/core/PhiloxRNGEngine.h
@@ -229,10 +229,10 @@ private:
   }
 
 
-  static const uint32_t kPhilox10A = 0x9E3779B9;
-  static const uint32_t kPhilox10B = 0xBB67AE85;
-  static const uint32_t kPhiloxSA = 0xD2511F53;
-  static const uint32_t kPhiloxSB = 0xCD9E8D57;
+  static constexpr uint32_t kPhilox10A = 0x9E3779B9;
+  static constexpr uint32_t kPhilox10B = 0xBB67AE85;
+  static constexpr uint32_t kPhiloxSA = 0xD2511F53;
+  static constexpr uint32_t kPhiloxSB = 0xCD9E8D57;
 };
 
 typedef philox_engine Philox4_32;
diff --git a/aten/src/ATen/cuda/CUDAGeneratorImpl.cpp b/aten/src/ATen/cuda/CUDAGeneratorImpl.cpp
index 9f7c9ba881e9..2e387fbc264d 100644
--- a/aten/src/ATen/cuda/CUDAGeneratorImpl.cpp
+++ b/aten/src/ATen/cuda/CUDAGeneratorImpl.cpp
@@ -325,9 +325,9 @@ uint64_t CUDAGeneratorImpl::seed() {
  */
 c10::intrusive_ptr<c10::TensorImpl> CUDAGeneratorImpl::get_state() const {
   // The RNG state comprises the seed, and an offset used for Philox.
-  static const size_t seed_size = sizeof(uint64_t);
-  static const size_t offset_size = sizeof(int64_t);
-  static const size_t total_size = seed_size + offset_size;
+  constexpr size_t seed_size = sizeof(uint64_t);
+  constexpr size_t offset_size = sizeof(int64_t);
+  constexpr size_t total_size = seed_size + offset_size;
 
   auto state_tensor = at::detail::empty_cpu({(int64_t)total_size}, ScalarType::Byte, std::nullopt, std::nullopt, std::nullopt, std::nullopt);
   auto rng_state = state_tensor.data_ptr<uint8_t>();
@@ -346,9 +346,9 @@ c10::intrusive_ptr<c10::TensorImpl> CUDAGeneratorImpl::get_state() const {
  * and size of the internal state.
  */
 void CUDAGeneratorImpl::set_state(const c10::TensorImpl& new_state) {
-  static const size_t seed_size = sizeof(uint64_t);
-  static const size_t offset_size = sizeof(int64_t);
-  static const size_t total_size = seed_size + offset_size;
+  constexpr size_t seed_size = sizeof(uint64_t);
+  constexpr size_t offset_size = sizeof(int64_t);
+  constexpr size_t total_size = seed_size + offset_size;
 
   detail::check_rng_state(new_state);
 
diff --git a/aten/src/ATen/native/Activation.cpp b/aten/src/ATen/native/Activation.cpp
index 861c51f16097..c164120a1f3c 100644
--- a/aten/src/ATen/native/Activation.cpp
+++ b/aten/src/ATen/native/Activation.cpp
@@ -240,8 +240,8 @@ TORCH_META_FUNC(gelu_backward) (
 
 namespace at::native {
 
-static const double SELU_ALPHA = 1.6732632423543772848170429916717;
-static const double SELU_SCALE = 1.0507009873554804934193349852946;
+static constexpr double SELU_ALPHA = 1.6732632423543772848170429916717;
+static constexpr double SELU_SCALE = 1.0507009873554804934193349852946;
 
 DEFINE_DISPATCH(elu_stub);
 DEFINE_DISPATCH(elu_backward_stub);
diff --git a/aten/src/ATen/native/BlasKernel.cpp b/aten/src/ATen/native/BlasKernel.cpp
index a77604c535c1..b476ca3cff8f 100644
--- a/aten/src/ATen/native/BlasKernel.cpp
+++ b/aten/src/ATen/native/BlasKernel.cpp
@@ -286,7 +286,7 @@ template void scal_fast_path<scalar_t>(int *n, scalar_t *a, scalar_t *x, int *in
 #if AT_BUILD_WITH_BLAS()
 template <>
 bool scal_use_fast_path<double>(int64_t n, int64_t incx) {
-  auto intmax = std::numeric_limits<int>::max();
+  auto constexpr intmax = std::numeric_limits<int>::max();
   return n <= intmax && incx <= intmax;
 }
 
@@ -315,7 +315,7 @@ bool gemv_use_fast_path<float>(
     int64_t incx,
     [[maybe_unused]] float beta,
     int64_t incy) {
-  auto intmax = std::numeric_limits<int>::max();
+  auto constexpr intmax = std::numeric_limits<int>::max();
   return (m <= intmax) && (n <= intmax) && (lda <= intmax) &&
          (incx > 0) && (incx <= intmax) && (incy > 0) && (incy <= intmax);
 }
diff --git a/aten/src/ATen/native/Distributions.h b/aten/src/ATen/native/Distributions.h
index 1c9db44aebb0..ab7d82dbeab4 100644
--- a/aten/src/ATen/native/Distributions.h
+++ b/aten/src/ATen/native/Distributions.h
@@ -127,7 +127,7 @@ C10_DEVICE scalar_t sample_gamma(scalar_t alpha, BaseSampler<accscalar_t, unifor
 
 template<typename scalar_t>
 C10_DEVICE scalar_t stirling_approx_tail(scalar_t k) {
-  const static scalar_t kTailValues[] = {
+  constexpr static scalar_t kTailValues[] = {
     0.0810614667953272,
     0.0413406959554092,
     0.0276779256849983,
@@ -139,7 +139,7 @@ C10_DEVICE scalar_t stirling_approx_tail(scalar_t k) {
     0.00925546218271273,
     0.00833056343336287
   };
-  if (k <= 9) {
+  if (k <= sizeof(kTailValues)/sizeof(scalar_t)) {
     return kTailValues[static_cast<size_t>(k)];
   }
   scalar_t kp1sq = (k + 1) * (k + 1);
diff --git a/aten/src/ATen/native/Math.h b/aten/src/ATen/native/Math.h
index b261da5fe54e..4677542706f6 100644
--- a/aten/src/ATen/native/Math.h
+++ b/aten/src/ATen/native/Math.h
@@ -581,7 +581,7 @@ scalar_t ratevl(scalar_t x, const scalar_t num[], int64_t M,
 template <typename scalar_t>
 static scalar_t lanczos_sum_expg_scaled(scalar_t x) {
   // lanczos approximation
-  static const scalar_t lanczos_sum_expg_scaled_num[13] = {
+  static constexpr scalar_t lanczos_sum_expg_scaled_num[13] = {
     0.006061842346248906525783753964555936883222,
     0.5098416655656676188125178644804694509993,
     19.51992788247617482847860966235652136208,
@@ -596,7 +596,7 @@ static scalar_t lanczos_sum_expg_scaled(scalar_t x) {
     103794043.1163445451906271053616070238554,
     56906521.91347156388090791033559122686859
   };
-  static const scalar_t lanczos_sum_expg_scaled_denom[13] = {
+  static constexpr scalar_t lanczos_sum_expg_scaled_denom[13] = {
     1.,
     66.,
     1925.,
@@ -712,7 +712,7 @@ static scalar_t _igamc_helper_series(scalar_t a, scalar_t x) {
 template <typename scalar_t>
 static scalar_t _igam_helper_asymptotic_series(scalar_t a, scalar_t x, bool igam) {
   // Compute igam/igamc using DLMF 8.12.3/8.12.4 [igam1]
-  static const scalar_t d[25][25] =
+  static constexpr scalar_t d[25][25] =
     {{-3.3333333333333333e-1, 8.3333333333333333e-2, -1.4814814814814815e-2,
       1.1574074074074074e-3, 3.527336860670194e-4, -1.7875514403292181e-4,
       3.9192631785224378e-5, -2.1854485106799922e-6, -1.85406221071516e-6,
diff --git a/aten/src/ATen/native/Normalization.cpp b/aten/src/ATen/native/Normalization.cpp
index 86941806d307..72526162d133 100644
--- a/aten/src/ATen/native/Normalization.cpp
+++ b/aten/src/ATen/native/Normalization.cpp
@@ -62,7 +62,7 @@
 #include <utility>
 #include <vector>
 
-static const int MIOPEN_DIM_MAX = 5;
+static constexpr int MIOPEN_DIM_MAX = 5;
 
 namespace at::meta {
 
diff --git a/aten/src/ATen/native/cpu/UpSampleKernel.cpp b/aten/src/ATen/native/cpu/UpSampleKernel.cpp
index bd421aad111d..e59e5985bf7f 100644
--- a/aten/src/ATen/native/cpu/UpSampleKernel.cpp
+++ b/aten/src/ATen/native/cpu/UpSampleKernel.cpp
@@ -1038,7 +1038,7 @@ struct HelperInterpNearest : public HelperInterpBase {
   // We keep this structure for BC and consider as deprecated.
   // See HelperInterpNearestExact as replacement
 
-  static const int interp_size = 1;
+  static constexpr int interp_size = 1;
 
   static inline void init_indices_weights(
     at::ScalarType output_type,
@@ -1155,7 +1155,7 @@ struct HelperInterpNearestExact : public HelperInterpNearest {
 
 struct HelperInterpLinear : public HelperInterpBase {
 
-  static const int interp_size = 2;
+  static constexpr int interp_size = 2;
 
   // Compute indices and weights for each interpolated dimension
   // indices_weights = {
@@ -1275,7 +1275,7 @@ struct HelperInterpLinear : public HelperInterpBase {
 
 struct HelperInterpCubic : public HelperInterpBase {
 
-  static const int interp_size = 4;
+  static constexpr int interp_size = 4;
 
   // Compute indices and weights for each interpolated dimension
   // indices_weights = {
diff --git a/aten/src/ATen/native/cuda/DilatedMaxPool2d.cu b/aten/src/ATen/native/cuda/DilatedMaxPool2d.cu
index edb502688860..344906a2a4df 100644
--- a/aten/src/ATen/native/cuda/DilatedMaxPool2d.cu
+++ b/aten/src/ATen/native/cuda/DilatedMaxPool2d.cu
@@ -249,7 +249,7 @@ __global__ void max_pool_forward_nhwc(
 }
 
 
-static const int BLOCK_THREADS = 256;
+static constexpr int BLOCK_THREADS = 256;
 
 template <typename scalar_t, typename accscalar_t>
 #if defined (USE_ROCM)
diff --git a/aten/src/ATen/native/cuda/Embedding.cu b/aten/src/ATen/native/cuda/Embedding.cu
index 602dfd6e5288..adc300a5a9ef 100644
--- a/aten/src/ATen/native/cuda/Embedding.cu
+++ b/aten/src/ATen/native/cuda/Embedding.cu
@@ -36,9 +36,9 @@ namespace at::native {
 namespace {
 
 #if defined(USE_ROCM)
-static const int BLOCKDIMY = 16;
+static constexpr int BLOCKDIMY = 16;
 #else
-static const int BLOCKDIMY = 32;
+static constexpr int BLOCKDIMY = 32;
 #endif
 
 template
diff --git a/aten/src/ATen/native/cuda/IGammaKernel.cu b/aten/src/ATen/native/cuda/IGammaKernel.cu
index 624f080d9f6e..73db6272be9e 100644
--- a/aten/src/ATen/native/cuda/IGammaKernel.cu
+++ b/aten/src/ATen/native/cuda/IGammaKernel.cu
@@ -82,7 +82,7 @@ __host__ __device__ scalar_t lanczos_sum_expg_scaled(scalar_t x) {
   // lanczos approximation
   using accscalar_t = at::acc_type<scalar_t, /*is_cuda=*/true>;
 
-  static const accscalar_t lanczos_sum_expg_scaled_num[13] = {
+  constexpr accscalar_t lanczos_sum_expg_scaled_num[13] = {
     0.006061842346248906525783753964555936883222,
     0.5098416655656676188125178644804694509993,
     19.51992788247617482847860966235652136208,
@@ -97,7 +97,7 @@ __host__ __device__ scalar_t lanczos_sum_expg_scaled(scalar_t x) {
     103794043.1163445451906271053616070238554,
     56906521.91347156388090791033559122686859
   };
-  static const accscalar_t lanczos_sum_expg_scaled_denom[13] = {
+  constexpr accscalar_t lanczos_sum_expg_scaled_denom[13] = {
     1.,
     66.,
     1925.,
@@ -126,10 +126,10 @@ __host__ __device__ scalar_t _igam_helper_fac(scalar_t a, scalar_t x) {
 
   using accscalar_t = at::acc_type<scalar_t, /*is_cuda=*/true>;
   accscalar_t ax, fac, res, num, numfac;
-  static const accscalar_t MAXLOG = std::is_same_v<accscalar_t,double> ?
+  constexpr accscalar_t MAXLOG = std::is_same_v<accscalar_t,double> ?
     7.09782712893383996843E2 : 88.72283905206835;
-  static const accscalar_t EXP1 = 2.718281828459045;
-  static const accscalar_t lanczos_g = 6.024680040776729583740234375;
+  constexpr accscalar_t EXP1 = 2.718281828459045;
+  constexpr accscalar_t lanczos_g = 6.024680040776729583740234375;
 
   if (::fabs(a - x) > 0.4 * ::fabs(a)) {
     ax = a * ::log(x) - x - ::lgamma(a);
@@ -158,9 +158,9 @@ __host__ __device__ scalar_t _igam_helper_series(scalar_t a, scalar_t x) {
   // Compute igam using DLMF 8.11.4. [igam1]
 
   using accscalar_t = at::acc_type<scalar_t, /*is_cuda=*/true>;
-  static const accscalar_t MACHEP = std::is_same_v<accscalar_t, double> ?
+  constexpr accscalar_t MACHEP = std::is_same_v<accscalar_t, double> ?
     1.11022302462515654042E-16 : 5.9604644775390625E-8;
-  static const int MAXITER = 2000;
+  constexpr int MAXITER = 2000;
 
   int i;
   accscalar_t ans, ax, c, r;
@@ -196,8 +196,8 @@ __host__ __device__ scalar_t _igamc_helper_series(scalar_t a, scalar_t x) {
   accscalar_t fac = 1;
   accscalar_t sum = 0;
   accscalar_t term, logx;
-  static const int MAXITER = 2000;
-  static const accscalar_t MACHEP = std::is_same_v<accscalar_t, double> ?
+  constexpr int MAXITER = 2000;
+  constexpr accscalar_t MACHEP = std::is_same_v<accscalar_t, double> ?
     1.11022302462515654042E-16 : 5.9604644775390625E-8;
 
   for (n = 1; n < MAXITER; n++) {
@@ -219,7 +219,7 @@ __host__ __device__ scalar_t _igam_helper_asymptotic_series(scalar_t a, scalar_t
   // Compute igam/igamc using DLMF 8.12.3/8.12.4 [igam1]
 
   using accscalar_t = at::acc_type<scalar_t, /*is_cuda=*/true>;
-  static const accscalar_t d[25][25] =
+  constexpr accscalar_t d[25][25] =
     {{-3.3333333333333333e-1, 8.3333333333333333e-2, -1.4814814814814815e-2, 1.1574074074074074e-3, 3.527336860670194e-4, -1.7875514403292181e-4, 3.9192631785224378e-5, -2.1854485106799922e-6, -1.85406221071516e-6, 8.296711340953086e-7, -1.7665952736826079e-7, 6.7078535434014986e-9, 1.0261809784240308e-8, -4.3820360184533532e-9, 9.1476995822367902e-10, -2.551419399494625e-11, -5.8307721325504251e-11, 2.4361948020667416e-11, -5.0276692801141756e-12, 1.1004392031956135e-13, 3.3717632624009854e-13, -1.3923887224181621e-13, 2.8534893807047443e-14, -5.1391118342425726e-16, -1.9752288294349443e-15},
     {-1.8518518518518519e-3, -3.4722222222222222e-3, 2.6455026455026455e-3, -9.9022633744855967e-4, 2.0576131687242798e-4, -4.0187757201646091e-7, -1.8098550334489978e-5, 7.6491609160811101e-6, -1.6120900894563446e-6, 4.6471278028074343e-9, 1.378633446915721e-7, -5.752545603517705e-8, 1.1951628599778147e-8, -1.7543241719747648e-11, -1.0091543710600413e-9, 4.1627929918425826e-10, -8.5639070264929806e-11, 6.0672151016047586e-14, 7.1624989648114854e-12, -2.9331866437714371e-12, 5.9966963656836887e-13, -2.1671786527323314e-16, -4.9783399723692616e-14, 2.0291628823713425e-14, -4.13125571381061e-15},
     {4.1335978835978836e-3, -2.6813271604938272e-3, 7.7160493827160494e-4, 2.0093878600823045e-6, -1.0736653226365161e-4, 5.2923448829120125e-5, -1.2760635188618728e-5, 3.4235787340961381e-8, 1.3721957309062933e-6, -6.298992138380055e-7, 1.4280614206064242e-7, -2.0477098421990866e-10, -1.4092529910867521e-8, 6.228974084922022e-9, -1.3670488396617113e-9, 9.4283561590146782e-13, 1.2872252400089318e-10, -5.5645956134363321e-11, 1.1975935546366981e-11, -4.1689782251838635e-15, -1.0940640427884594e-12, 4.6622399463901357e-13, -9.905105763906906e-14, 1.8931876768373515e-17, 8.8592218725911273e-15},
@@ -248,7 +248,7 @@ __host__ __device__ scalar_t _igam_helper_asymptotic_series(scalar_t a, scalar_t
 
   int k, n, sgn;
   int maxpow = 0;
-  static const accscalar_t MACHEP = std::is_same_v<accscalar_t, double> ?
+  constexpr accscalar_t MACHEP = std::is_same_v<accscalar_t, double> ?
     1.11022302462515654042E-16 : 5.9604644775390625E-8;
   accscalar_t lambda = x / a;
   accscalar_t sigma = (x - a) / a;
@@ -314,12 +314,12 @@ __host__ __device__ scalar_t _igamc_helper_continued_fraction(scalar_t a, scalar
   int i;
   accscalar_t ans, ax, c, yc, r, t, y, z;
   accscalar_t pk, pkm1, pkm2, qk, qkm1, qkm2;
-  static const int MAXITER = 2000;
-  static const accscalar_t MACHEP = std::is_same_v<accscalar_t, double> ?
+  constexpr int MAXITER = 2000;
+  constexpr accscalar_t MACHEP = std::is_same_v<accscalar_t, double> ?
     1.11022302462515654042E-16 : 5.9604644775390625E-8;
-  static const accscalar_t BIG = std::is_same_v<accscalar_t,double> ?
+  constexpr accscalar_t BIG = std::is_same_v<accscalar_t,double> ?
     4.503599627370496e15 : 16777216.;
-  static const accscalar_t BIGINV = std::is_same_v<accscalar_t,double> ?
+  constexpr accscalar_t BIGINV = std::is_same_v<accscalar_t,double> ?
     2.22044604925031308085e-16 : 5.9604644775390625E-8;
 
   ax = _igam_helper_fac(a, x);
@@ -385,10 +385,10 @@ __noinline__ __host__ __device__ scalar_t calc_igammac(scalar_t a, scalar_t x) {
   using accscalar_t = at::acc_type<scalar_t, /*is_cuda=*/true>;
   accscalar_t absxma_a;
 
-  static const accscalar_t SMALL = 20.0;
-  static const accscalar_t LARGE = 200.0;
-  static const accscalar_t SMALLRATIO = 0.3;
-  static const accscalar_t LARGERATIO = 4.5;
+  constexpr accscalar_t SMALL = 20.0;
+  constexpr accscalar_t LARGE = 200.0;
+  constexpr accscalar_t SMALLRATIO = 0.3;
+  constexpr accscalar_t LARGERATIO = 4.5;
 
   if ((x < 0) || (a < 0)) {
     // out of defined-region of the function
@@ -467,10 +467,10 @@ __noinline__ __host__ __device__ scalar_t calc_igamma(scalar_t a, scalar_t x) {
 
   using accscalar_t = at::acc_type<scalar_t, /*is_cuda=*/true>;
   accscalar_t absxma_a;
-  static const accscalar_t SMALL = 20.0;
-  static const accscalar_t LARGE = 200.0;
-  static const accscalar_t SMALLRATIO = 0.3;
-  static const accscalar_t LARGERATIO = 4.5;
+  constexpr accscalar_t SMALL = 20.0;
+  constexpr accscalar_t LARGE = 200.0;
+  constexpr accscalar_t SMALLRATIO = 0.3;
+  constexpr accscalar_t LARGERATIO = 4.5;
 
   // boundary values following SciPy
   if ((x < 0) || (a < 0)) {
diff --git a/aten/src/ATen/native/cuda/Math.cuh b/aten/src/ATen/native/cuda/Math.cuh
index 1d603132e689..1fa245af1a4d 100644
--- a/aten/src/ATen/native/cuda/Math.cuh
+++ b/aten/src/ATen/native/cuda/Math.cuh
@@ -231,7 +231,7 @@ const auto lcm_string = jiterator_stringify(
 const auto digamma_string = jiterator_stringify(
   template <typename T>
   T digamma(T x) {
-    static const double PI_f64 = 3.14159265358979323846;
+    static constexpr double PI_f64 = 3.14159265358979323846;
 
     // Short-circuits if x is +/- 0 and returns -/+ ∞ per the C++ standard
     if (x == 0) {
@@ -3072,9 +3072,9 @@ template <typename scalar_t>
 static inline C10_HOST_DEVICE scalar_t calc_digamma(scalar_t in) {
   // [C++ Standard Reference: Gamma Function] https://en.cppreference.com/w/cpp/numeric/math/tgamma
   using accscalar_t = at::acc_type<scalar_t, /*is_cuda=*/true>;
-  static const double PI_f64 = 3.14159265358979323846;
-  const accscalar_t PSI_10 = 2.25175258906672110764;
-  const accscalar_t A[] = {
+  static constexpr double PI_f64 = 3.14159265358979323846;
+  constexpr accscalar_t PSI_10 = 2.25175258906672110764;
+  constexpr accscalar_t A[] = {
       8.33333333333333333333E-2,
       -2.10927960927960927961E-2,
       7.57575757575757575758E-3,
diff --git a/aten/src/ATen/native/cuda/UpSample.cuh b/aten/src/ATen/native/cuda/UpSample.cuh
index 50428b377da8..09e094ea2bf0 100644
--- a/aten/src/ATen/native/cuda/UpSample.cuh
+++ b/aten/src/ATen/native/cuda/UpSample.cuh
@@ -277,7 +277,7 @@ struct BilinearFilterFunctor {
     return 0;
   }
 
-  static const int size = 2;
+  static constexpr int size = 2;
 };
 
 // taken from
@@ -301,7 +301,7 @@ struct BicubicFilterFunctor {
     return 0;
   }
 
-  static const int size = 4;
+  static constexpr int size = 4;
 };
 
 template <typename accscalar_t>
diff --git a/aten/src/ATen/native/mkldnn/Matmul.cpp b/aten/src/ATen/native/mkldnn/Matmul.cpp
index 740c056a7f23..fbc8294f45cf 100644
--- a/aten/src/ATen/native/mkldnn/Matmul.cpp
+++ b/aten/src/ATen/native/mkldnn/Matmul.cpp
@@ -416,7 +416,7 @@ static inline bool checksize(const Tensor& mat1, const Tensor& mat2){
   // else if dim = 3, mat1's size = (b * m * n), mat2's size = (b * n * k)
   // else called from aten::mv, mat1.size = (m * n), mat2.size = (n)
   // only m * n * b * k(if exist) are large enough we can get benefit from mkldnn optimized gemm kernel
-  static const int64_t mkldnn_gemm_min_size = 16 * 16 * 16;
+  constexpr int64_t mkldnn_gemm_min_size = 16 * 16 * 16;
   if (mat1.dim() == 1 && mat2.dim() == 1) {
     // aten::dot
     return mat1.size(0) > mkldnn_gemm_min_size;
diff --git a/aten/src/ATen/native/quantized/cpu/kernels/QuantizedOpKernels.cpp b/aten/src/ATen/native/quantized/cpu/kernels/QuantizedOpKernels.cpp
index 028047e4d6ac..293dfb20b9bf 100644
--- a/aten/src/ATen/native/quantized/cpu/kernels/QuantizedOpKernels.cpp
+++ b/aten/src/ATen/native/quantized/cpu/kernels/QuantizedOpKernels.cpp
@@ -3551,7 +3551,7 @@ void dequantize_tensor_per_tensor_affine_cpu(
 
 #if defined(__ARM_NEON__) || defined(__aarch64__)
 
-const static int PARALLEL_THRESHOLD = 1 << 20;
+constexpr static int PARALLEL_THRESHOLD = 1 << 20;
 
 // Generic template defaults to naive quantize implementation
 template <typename T>
diff --git a/aten/src/ATen/native/quantized/cpu/qlinear.cpp b/aten/src/ATen/native/quantized/cpu/qlinear.cpp
index 897eefd91d21..7a80b166f8cb 100644
--- a/aten/src/ATen/native/quantized/cpu/qlinear.cpp
+++ b/aten/src/ATen/native/quantized/cpu/qlinear.cpp
@@ -1388,7 +1388,7 @@ namespace at::native {
     TORCH_CHECK(act_scale.numel() == 1 && act_zero_point.numel() <= 1,
         "onednn int8 linear: act scale/zp size should be 1/<=1");
     static std::optional<at::Tensor> other = std::nullopt;
-    static const std::string_view binary_post_op = "none";
+    constexpr std::string_view binary_post_op = "none";
     int64_t act_zp = act_zero_point.numel() == 1 ? act_zero_point.item().toLong() : 0;
     return linear_int8_with_onednn_weight(
         act, act_scale.item().toDouble(), act_zp,
diff --git a/aten/src/ATen/native/quantized/cpu/qsoftmax.cpp b/aten/src/ATen/native/quantized/cpu/qsoftmax.cpp
index cd00a351b0e3..31221cd9bf26 100644
--- a/aten/src/ATen/native/quantized/cpu/qsoftmax.cpp
+++ b/aten/src/ATen/native/quantized/cpu/qsoftmax.cpp
@@ -16,8 +16,8 @@ namespace {
 
 #ifdef USE_PYTORCH_QNNPACK
 
-const static float qnnpack_softmax_output_scale = 0x1.0p-8f;
-const static int qnnpack_softmax_output_zero_point = 0;
+constexpr static float qnnpack_softmax_output_scale = 0x1.0p-8f;
+constexpr static int qnnpack_softmax_output_zero_point = 0;
 
 bool is_qnnpack_compatible(
     const Tensor& qx,
diff --git a/aten/src/ATen/native/transformers/cuda/mem_eff_attention/epilogue/epilogue_thread_apply_logsumexp.h b/aten/src/ATen/native/transformers/cuda/mem_eff_attention/epilogue/epilogue_thread_apply_logsumexp.h
index e3dc0778e46b..156034954d9e 100644
--- a/aten/src/ATen/native/transformers/cuda/mem_eff_attention/epilogue/epilogue_thread_apply_logsumexp.h
+++ b/aten/src/ATen/native/transformers/cuda/mem_eff_attention/epilogue/epilogue_thread_apply_logsumexp.h
@@ -110,9 +110,9 @@ class ApplyLogSumExp {
   using ElementCompute = ElementCompute_;
   using ElementLSE = ElementLSE_;
 
-  static int const kElementsPerAccess = ElementsPerAccess;
-  static int const kCount = kElementsPerAccess;
-  static const ScaleType::Kind kScale =
+  static int constexpr kElementsPerAccess = ElementsPerAccess;
+  static int constexpr kCount = kElementsPerAccess;
+  static constexpr ScaleType::Kind kScale =
       cutlass::epilogue::thread::ScaleType::NoBetaScaling;
 
   using FragmentOutput = Array<ElementOutput, kCount>;
diff --git a/aten/src/ATen/test/pow_test.cpp b/aten/src/ATen/test/pow_test.cpp
index 95bb48b341f5..6391c3c8228c 100644
--- a/aten/src/ATen/test/pow_test.cpp
+++ b/aten/src/ATen/test/pow_test.cpp
@@ -14,16 +14,16 @@ using namespace at;
 
 namespace {
 
-const auto int_min = std::numeric_limits<int>::min();
-const auto int_max = std::numeric_limits<int>::max();
-const auto long_min = std::numeric_limits<int64_t>::min();
-const auto long_max = std::numeric_limits<int64_t>::max();
-const auto float_lowest = std::numeric_limits<float>::lowest();
-const auto float_min = std::numeric_limits<float>::min();
-const auto float_max = std::numeric_limits<float>::max();
-const auto double_lowest = std::numeric_limits<double>::lowest();
-const auto double_min = std::numeric_limits<double>::min();
-const auto double_max = std::numeric_limits<double>::max();
+constexpr auto int_min = std::numeric_limits<int>::min();
+constexpr auto int_max = std::numeric_limits<int>::max();
+constexpr auto long_min = std::numeric_limits<int64_t>::min();
+constexpr auto long_max = std::numeric_limits<int64_t>::max();
+constexpr auto float_lowest = std::numeric_limits<float>::lowest();
+constexpr auto float_min = std::numeric_limits<float>::min();
+constexpr auto float_max = std::numeric_limits<float>::max();
+constexpr auto double_lowest = std::numeric_limits<double>::lowest();
+constexpr auto double_min = std::numeric_limits<double>::min();
+constexpr auto double_max = std::numeric_limits<double>::max();
 
 const std::vector<int> ints {
   int_min,
diff --git a/aten/src/ATen/xpu/XPUGeneratorImpl.cpp b/aten/src/ATen/xpu/XPUGeneratorImpl.cpp
index 14f3059cc2b3..7a0859671ba7 100644
--- a/aten/src/ATen/xpu/XPUGeneratorImpl.cpp
+++ b/aten/src/ATen/xpu/XPUGeneratorImpl.cpp
@@ -146,9 +146,9 @@ uint64_t XPUGeneratorImpl::seed() {
 
 c10::intrusive_ptr<c10::TensorImpl> XPUGeneratorImpl::get_state() const {
   // The RNG state comprises the seed, and an offset used for Philox.
-  static const size_t seed_size = sizeof(uint64_t);
-  static const size_t offset_size = sizeof(uint64_t);
-  static const size_t total_size = seed_size + offset_size;
+  constexpr size_t seed_size = sizeof(uint64_t);
+  constexpr size_t offset_size = sizeof(uint64_t);
+  constexpr size_t total_size = seed_size + offset_size;
 
   // The internal state is returned as a CPU byte tensor.
   auto state_tensor = at::detail::empty_cpu(
@@ -170,9 +170,9 @@ c10::intrusive_ptr<c10::TensorImpl> XPUGeneratorImpl::get_state() const {
 void XPUGeneratorImpl::set_state(const c10::TensorImpl& new_state) {
   at::xpu::assertNotCapturing(
       "Please ensure to utilize the XPUGeneratorImpl::set_state_index method during capturing.");
-  static const size_t seed_size = sizeof(uint64_t);
-  static const size_t offset_size = sizeof(uint64_t);
-  static const size_t total_size = seed_size + offset_size;
+  constexpr size_t seed_size = sizeof(uint64_t);
+  constexpr size_t offset_size = sizeof(uint64_t);
+  constexpr size_t total_size = seed_size + offset_size;
 
   at::detail::check_rng_state(new_state);