[c++] use constexpr instead of const (pytorch#93267)

As discussed in pytorch#93199 (comment). Pull Request resolved: pytorch#93267 Approved by: https://github.com/Skylion007
sands-lab · Jan 31, 2023 · aee5f84 · aee5f84
1 parent f9c08e2
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Showing 52 changed files with 82 additions and 82 deletions.
diff --git a/aten/src/ATen/native/cuda/AbsKernel.cu b/aten/src/ATen/native/cuda/AbsKernel.cu
@@ -15,7 +15,7 @@ struct AbsFunctor {
   }
 };
 
-const char abs_name[] = "abs_kernel";
+constexpr char abs_name[] = "abs_kernel";
 void abs_kernel_cuda(TensorIteratorBase& iter) {
   auto dtype = iter.dtype();
   if (at::isComplexType(dtype)) {

diff --git a/aten/src/ATen/native/cuda/BinaryDivTrueKernel.cu b/aten/src/ATen/native/cuda/BinaryDivTrueKernel.cu
@@ -16,7 +16,7 @@
 namespace at::native {
 namespace binary_internal {
 
-const char div_name[] = "div_kernel";
+constexpr char div_name[] = "div_kernel";
 void div_true_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (iter.common_dtype() == kComplexHalf) {

diff --git a/aten/src/ATen/native/cuda/BinaryLogicalOpsKernels.cu b/aten/src/ATen/native/cuda/BinaryLogicalOpsKernels.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char logical_and_name[] = "logical_and_kernel";
+constexpr char logical_and_name[] = "logical_and_kernel";
 void logical_and_kernel_cuda(TensorIterator& iter) {
   auto dtype = iter.common_dtype();
   if (at::isComplexType(dtype)) {
@@ -48,7 +48,7 @@ void logical_and_kernel_cuda(TensorIterator& iter) {
   }
 }
 
-const char logical_or_name[] = "logical_or_kernel";
+constexpr char logical_or_name[] = "logical_or_kernel";
 void logical_or_kernel_cuda(TensorIterator& iter) {
   auto dtype = iter.common_dtype();
   if (at::isComplexType(dtype)) {
@@ -84,7 +84,7 @@ void logical_or_kernel_cuda(TensorIterator& iter) {
   }
 }
 
-const char logical_xor_name[] = "logical_xor_kernel";
+constexpr char logical_xor_name[] = "logical_xor_kernel";
 void logical_xor_kernel_cuda(TensorIterator& iter) {
   auto dtype = iter.common_dtype();
   if (at::isComplexType(dtype)) {

diff --git a/aten/src/ATen/native/cuda/BinaryMiscBackwardOpsKernels.cu b/aten/src/ATen/native/cuda/BinaryMiscBackwardOpsKernels.cu
@@ -15,7 +15,7 @@
 
 namespace at::native {
 
-const char sigmoid_backward_name[] = "sigmoid_backward";
+constexpr char sigmoid_backward_name[] = "sigmoid_backward";
 void sigmoid_backward_kernel_cuda(TensorIteratorBase& iter) {
   auto dtype = iter.dtype();
   if(isComplexType(dtype)) {
@@ -86,7 +86,7 @@ void logit_backward_kernel_cuda(TensorIteratorBase& iter, const Scalar& eps_scal
       });
 }
 
-const char tanh_backward_name[] = "tanh_backward";
+constexpr char tanh_backward_name[] = "tanh_backward";
 void tanh_backward_kernel_cuda(TensorIteratorBase& iter) {
   auto dtype = iter.dtype();
   if(isComplexType(dtype)) {

diff --git a/aten/src/ATen/native/cuda/BinaryMulKernel.cu b/aten/src/ATen/native/cuda/BinaryMulKernel.cu
@@ -18,7 +18,7 @@
 
 namespace at::native {
 
-const char mul_name[] = "mul_kernel";
+constexpr char mul_name[] = "mul_kernel";
 void mul_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (common_dtype == kComplexHalf) {

diff --git a/aten/src/ATen/native/cuda/GcdLcmKernel.cu b/aten/src/ATen/native/cuda/GcdLcmKernel.cu
@@ -14,7 +14,7 @@
 namespace at::native {
 
 // See note [Jiterator]
-const char gcd_name[] = "gcd";
+constexpr char gcd_name[] = "gcd";
 void gcd_kernel_cuda(TensorIteratorBase& iter) {
   #if AT_USE_JITERATOR()
     AT_DISPATCH_INTEGRAL_TYPES(iter.common_dtype(), "gcd_cuda", [&]() {
@@ -33,7 +33,7 @@ void gcd_kernel_cuda(TensorIteratorBase& iter) {
 }
 
 // See note [Jiterator]
-const char lcm_name[] = "lcm";
+constexpr char lcm_name[] = "lcm";
 void lcm_kernel_cuda(TensorIteratorBase& iter) {
   #if AT_USE_JITERATOR()
     AT_DISPATCH_INTEGRAL_TYPES(iter.common_dtype(), "lcm_cuda", [&]() {

diff --git a/aten/src/ATen/native/cuda/Lerp.cu b/aten/src/ATen/native/cuda/Lerp.cu
@@ -9,7 +9,7 @@
 namespace at::native {
 namespace {
 
-const char lerp_tensor_name[] = "lerp_tensor";
+constexpr char lerp_tensor_name[] = "lerp_tensor";
 void lerp_tensor_kernel(at::TensorIteratorBase& iter) {
   auto dtype = iter.common_dtype();
   if(at::isComplexType(dtype)) {
@@ -63,7 +63,7 @@ void lerp_tensor_kernel(at::TensorIteratorBase& iter) {
   }
 }
 
-const char lerp_scalar_name[] = "lerp_scalar";
+constexpr char lerp_scalar_name[] = "lerp_scalar";
 void lerp_scalar_kernel(at::TensorIteratorBase& iter, const c10::Scalar& weight) {
   auto dtype = iter.common_dtype();
   if (at::isComplexType(dtype)) {

diff --git a/aten/src/ATen/native/cuda/PointwiseOpsKernel.cu b/aten/src/ATen/native/cuda/PointwiseOpsKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char addcmul_name[] = "addcmul";
+constexpr char addcmul_name[] = "addcmul";
 void addcmul_cuda_kernel(TensorIteratorBase& iter, const Scalar& value) {
   auto dtype = iter.common_dtype();
   if (at::isComplexType(dtype)) {
@@ -56,7 +56,7 @@ void addcmul_cuda_kernel(TensorIteratorBase& iter, const Scalar& value) {
 }
 
 // return a + alpha * (b / static_cast<accscalar_t>(c));
-const char addcdiv_name[] = "addcdiv";
+constexpr char addcdiv_name[] = "addcdiv";
 void addcdiv_cuda_kernel(TensorIteratorBase& iter, const Scalar& value) {
   auto dtype = iter.common_dtype();
   if (at::isComplexType(dtype)) {

diff --git a/aten/src/ATen/native/cuda/PowKernel.cu b/aten/src/ATen/native/cuda/PowKernel.cu
@@ -38,7 +38,7 @@ void pow_scalar_tensor_impl(TensorIteratorBase& iter, c10::complex<value_t> base
 }
 
 /* complex<Half> support impl */
-const char pow_scalar_base_name[] = "pow_scalar_base_kernel";
+constexpr char pow_scalar_base_name[] = "pow_scalar_base_kernel";
 template <>
 void pow_scalar_tensor_impl(TensorIteratorBase& iter, c10::complex<at::Half> base) {
   using scalar_t = c10::complex<at::Half>;
@@ -68,7 +68,7 @@ namespace {
 
 #if AT_USE_JITERATOR()
 /* complex<Half> support impl */
-const char pow_name[] = "pow_kernel";
+constexpr char pow_name[] = "pow_kernel";
 static const auto pow_kernel_string =
     jiterator_stringify(template <typename T> T pow_kernel(T base, T exp) {
       return std::pow(base, exp);

diff --git a/aten/src/ATen/native/cuda/ReduceSumProdKernel.cu b/aten/src/ATen/native/cuda/ReduceSumProdKernel.cu
@@ -21,7 +21,7 @@ struct sum_functor {
 };
 
 // jiterated specialization for `complex<Half>`
-const char sum_name[] = "sum";
+constexpr char sum_name[] = "sum";
 template <>
 struct sum_functor<c10::complex<at::Half>> {
 // jiterator reduction fails on windows
@@ -57,7 +57,7 @@ struct nansum_functor {
   }
 };
 
-const char prod_name[] = "prod";
+constexpr char prod_name[] = "prod";
 
 template <typename scalar_t, typename acc_t = scalar_t, typename out_t = scalar_t>
 struct prod_functor {

diff --git a/aten/src/ATen/native/cuda/UnaryComplexKernels.cu b/aten/src/ATen/native/cuda/UnaryComplexKernels.cu
@@ -25,7 +25,7 @@ __host__ __device__ static inline c10::complex<T> angle_wrapper(c10::complex<T>
   return c10::complex<T>{std::arg(v), 0};
 }
 
-const char angle_name[] = "angle_kernel";
+constexpr char angle_name[] = "angle_kernel";
 void angle_kernel_cuda(TensorIteratorBase& iter) {
   auto dtype = iter.common_dtype();
   if (at::isComplexType(dtype)) {
@@ -60,7 +60,7 @@ void angle_kernel_cuda(TensorIteratorBase& iter) {
 }
 
 // NB: Ignores the negative bit on tensors
-const char conj_name[] = "conj_kernel";
+constexpr char conj_name[] = "conj_kernel";
 void conj_kernel_cuda(TensorIteratorBase& iter) {
   auto conj_chalf = [&] {
     using scalar_t = c10::complex<at::Half>;

diff --git a/aten/src/ATen/native/cuda/UnaryGammaKernels.cu b/aten/src/ATen/native/cuda/UnaryGammaKernels.cu
@@ -13,7 +13,7 @@
 namespace at::native {
 
 // See note [Jiterator]
-const char digamma_name[] = "digamma";
+constexpr char digamma_name[] = "digamma";
 void digamma_kernel_cuda(TensorIteratorBase& iter) {
   #if AT_USE_JITERATOR()
     AT_DISPATCH_FLOATING_TYPES_AND_HALF(iter.common_dtype(), "digamma_cuda", [&]() {
@@ -32,7 +32,7 @@ void digamma_kernel_cuda(TensorIteratorBase& iter) {
 }
 
 // See note [Jiterator]
-const char trigamma_name[] = "trigamma";
+constexpr char trigamma_name[] = "trigamma";
 void trigamma_kernel_cuda(TensorIteratorBase& iter) {
   #if AT_USE_JITERATOR()
     AT_DISPATCH_FLOATING_TYPES_AND_HALF(iter.common_dtype(), "trigamma_cuda", [&]() {
@@ -50,7 +50,7 @@ void trigamma_kernel_cuda(TensorIteratorBase& iter) {
   #endif // AT_USE_JITERATOR()
 }
 
-const char polygamma_name[] = "polygamma";
+constexpr char polygamma_name[] = "polygamma";
 void polygamma_kernel_cuda(TensorIteratorBase& iter, int64_t n) {
   if (n == 0) {
     digamma_kernel_cuda(iter);
@@ -83,7 +83,7 @@ void polygamma_kernel_cuda(TensorIteratorBase& iter, int64_t n) {
   }
 }
 
-const char lgamma_name[] = "lgamma_kernel";
+constexpr char lgamma_name[] = "lgamma_kernel";
 void lgamma_kernel_cuda(TensorIteratorBase& iter) {
   #if AT_USE_JITERATOR()
     AT_DISPATCH_FLOATING_TYPES_AND_HALF(iter.common_dtype(), "lgamma_cuda", [&]() {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricAcosKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricAcosKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char acos_name[] = "acos";
+constexpr char acos_name[] = "acos";
 void acos_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricAcoshKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricAcoshKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char acosh_name[] = "acosh";
+constexpr char acosh_name[] = "acosh";
 void acosh_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if(at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricAsinKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricAsinKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char asin_name[] = "asin";
+constexpr char asin_name[] = "asin";
 void asin_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricAsinhKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricAsinhKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char asinh_name[] = "asinh";
+constexpr char asinh_name[] = "asinh";
 void asinh_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricAtanKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricAtanKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char atan_name[] = "atan";
+constexpr char atan_name[] = "atan";
 void atan_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricAtanhKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricAtanhKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char atanh_name[] = "atanh";
+constexpr char atanh_name[] = "atanh";
 void atanh_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricCosKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricCosKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char cos_name[] = "cos";
+constexpr char cos_name[] = "cos";
 void cos_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricCoshKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricCoshKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char cosh_name[] = "cosh";
+constexpr char cosh_name[] = "cosh";
 void cosh_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricSinKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricSinKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char sin_name[] = "sin";
+constexpr char sin_name[] = "sin";
 void sin_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricSinhKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricSinhKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char sinh_name[] = "sinh";
+constexpr char sinh_name[] = "sinh";
 void sinh_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricTanKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricTanKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char tan_name[] = "tan";
+constexpr char tan_name[] = "tan";
 void tan_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryGeometricTanhKernel.cu b/aten/src/ATen/native/cuda/UnaryGeometricTanhKernel.cu
@@ -11,7 +11,7 @@
 
 namespace at::native {
 
-const char tanh_name[] = "tanh";
+constexpr char tanh_name[] = "tanh";
 void tanh_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryLogKernels.cu b/aten/src/ATen/native/cuda/UnaryLogKernels.cu
@@ -12,7 +12,7 @@
 
 namespace at::native {
 
-const char log_name[] = "log_kernel";
+constexpr char log_name[] = "log_kernel";
 void log_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {
@@ -44,7 +44,7 @@ void log_kernel_cuda(TensorIteratorBase& iter) {
   }
 }
 
-const char log10_name[] = "log10_kernel";
+constexpr char log10_name[] = "log10_kernel";
 void log10_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {
@@ -81,7 +81,7 @@ void log1p_kernel_cuda(TensorIteratorBase& iter) {
   });
 }
 
-const char log2_name[] = "log2_kernel";
+constexpr char log2_name[] = "log2_kernel";
 void log2_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnaryOpsKernel.cu b/aten/src/ATen/native/cuda/UnaryOpsKernel.cu
@@ -34,7 +34,7 @@ void bitwise_not_kernel_cuda(TensorIteratorBase& iter) {
   }
 }
 
-const char exp_name[] = "exp_kernel";
+constexpr char exp_name[] = "exp_kernel";
 void exp_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {
@@ -92,7 +92,7 @@ C10_HOST_DEVICE static inline c10::complex<T> rsqrt_wrapper(c10::complex<T> v) {
   return one / ::sqrt(v);
 }
 
-const char rsqrt_name[] = "rsqrt_kernel";
+constexpr char rsqrt_name[] = "rsqrt_kernel";
 void rsqrt_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {
@@ -131,7 +131,7 @@ void rsqrt_kernel_cuda(TensorIteratorBase& iter) {
   }
 }
 
-const char sqrt_name[] = "sqrt_kernel";
+constexpr char sqrt_name[] = "sqrt_kernel";
 void sqrt_kernel_cuda(TensorIteratorBase& iter) {
   auto common_dtype = iter.common_dtype();
   if (at::isComplexType(common_dtype)) {

diff --git a/aten/src/ATen/native/cuda/UnarySignKernels.cu b/aten/src/ATen/native/cuda/UnarySignKernels.cu
@@ -25,7 +25,7 @@ void logical_not_kernel_cuda(TensorIteratorBase& iter) {
 }
 
 // NB: Ignores the negative bit on tensors
-const char neg_name[] = "neg_kernel";
+constexpr char neg_name[] = "neg_kernel";
 void neg_kernel_cuda(TensorIteratorBase& iter) {
   auto dtype = iter.dtype();
   if (at::isComplexType(dtype)) {
@@ -96,7 +96,7 @@ C10_HOST_DEVICE static inline c10::complex<T> sgn_wrapper(c10::complex<T> z) {
   }
 }
 
-const char sgn_name[] = "sgn_kernel";
+constexpr char sgn_name[] = "sgn_kernel";
 void sgn_kernel_cuda(TensorIteratorBase& iter){
   auto dtype = iter.dtype();
   #if AT_USE_JITERATOR()