diff --git a/example/02_gemm_bilinear/gemm_bilinear_wmma_fp16.cpp b/example/02_gemm_bilinear/gemm_bilinear_wmma_fp16.cpp
index 18731e810e..b50925d711 100644
--- a/example/02_gemm_bilinear/gemm_bilinear_wmma_fp16.cpp
+++ b/example/02_gemm_bilinear/gemm_bilinear_wmma_fp16.cpp
@@ -21,7 +21,7 @@
 
 struct AlphaBetaAdd
 {
-    AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta){};
+    AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta) {};
 
     template <typename E, typename C, typename D>
     __host__ __device__ constexpr void operator()(E& e, const C& c, const D& d) const;
diff --git a/example/02_gemm_bilinear/gemm_bilinear_wmma_int8.cpp b/example/02_gemm_bilinear/gemm_bilinear_wmma_int8.cpp
index 87812369bd..a9eef9c6cb 100644
--- a/example/02_gemm_bilinear/gemm_bilinear_wmma_int8.cpp
+++ b/example/02_gemm_bilinear/gemm_bilinear_wmma_int8.cpp
@@ -21,7 +21,7 @@
 
 struct AlphaBetaAdd
 {
-    AlphaBetaAdd(int alpha, int beta) : alpha_(alpha), beta_(beta){};
+    AlphaBetaAdd(int alpha, int beta) : alpha_(alpha), beta_(beta) {};
 
     template <typename E, typename C, typename D>
     __host__ __device__ constexpr void operator()(E& e, const C& c, const D& d) const;
diff --git a/example/02_gemm_bilinear/gemm_bilinear_xdl_fp16.cpp b/example/02_gemm_bilinear/gemm_bilinear_xdl_fp16.cpp
index c3e6ef7d5d..aa39afe277 100644
--- a/example/02_gemm_bilinear/gemm_bilinear_xdl_fp16.cpp
+++ b/example/02_gemm_bilinear/gemm_bilinear_xdl_fp16.cpp
@@ -20,7 +20,7 @@
 
 struct AlphaBetaAdd
 {
-    AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta){};
+    AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta) {};
 
     template <typename E, typename C, typename D>
     __host__ __device__ constexpr void operator()(E& e, const C& c, const D& d) const;
diff --git a/example/60_gemm_multi_ABD/gemm_multi_ABD_xdl_fp16.cpp b/example/60_gemm_multi_ABD/gemm_multi_ABD_xdl_fp16.cpp
index 93034a8b70..9b218ed583 100644
--- a/example/60_gemm_multi_ABD/gemm_multi_ABD_xdl_fp16.cpp
+++ b/example/60_gemm_multi_ABD/gemm_multi_ABD_xdl_fp16.cpp
@@ -83,7 +83,7 @@ struct AddScale
 
 struct AlphaBetaAdd
 {
-    AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta){};
+    AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta) {};
 
     template <typename E, typename C, typename D>
     __host__ __device__ constexpr void operator()(E& e, const C& c, const D& d) const;
diff --git a/example/61_contraction_multi_ABD/contraction_multi_ABD_xdl_fp16.cpp b/example/61_contraction_multi_ABD/contraction_multi_ABD_xdl_fp16.cpp
index e7c1d6f0be..b50e876384 100644
--- a/example/61_contraction_multi_ABD/contraction_multi_ABD_xdl_fp16.cpp
+++ b/example/61_contraction_multi_ABD/contraction_multi_ABD_xdl_fp16.cpp
@@ -42,7 +42,7 @@ static constexpr ck::index_t NumDimK = 2;
 
 struct AlphaBetaAdd
 {
-    AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta){};
+    AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta) {};
 
     template <typename E, typename C, typename D>
     __host__ __device__ constexpr void operator()(E& e, const C& c, const D& d) const;
diff --git a/include/ck/library/utility/host_tensor_generator.hpp b/include/ck/library/utility/host_tensor_generator.hpp
index ab69412c15..bc376ffcdf 100644
--- a/include/ck/library/utility/host_tensor_generator.hpp
+++ b/include/ck/library/utility/host_tensor_generator.hpp
@@ -483,7 +483,7 @@ struct GeneratorTensor_4
     std::normal_distribution<float> distribution;
 
     GeneratorTensor_4(float mean, float stddev, unsigned int seed = 1)
-        : generator(seed), distribution(mean, stddev){};
+        : generator(seed), distribution(mean, stddev) {};
 
     template <typename... Is>
     T operator()(Is...)
@@ -501,7 +501,7 @@ struct GeneratorTensor_4<ck::f4x2_pk_t>
     std::normal_distribution<float> distribution;
 
     GeneratorTensor_4(float mean, float stddev, unsigned int seed = 1)
-        : generator(seed), distribution(mean, stddev){};
+        : generator(seed), distribution(mean, stddev) {};
 
     template <typename... Is>
     ck::f4x2_pk_t operator()(Is...)
@@ -520,7 +520,7 @@ struct GeneratorTensor_4<ck::f6x32_pk_t>
     std::normal_distribution<float> distribution;
 
     GeneratorTensor_4(float mean, float stddev, unsigned int seed = 1)
-        : generator(seed), distribution(mean, stddev){};
+        : generator(seed), distribution(mean, stddev) {};
 
     template <typename... Is>
     ck::f6x32_pk_t operator()(Is...)
@@ -542,7 +542,7 @@ struct GeneratorTensor_4<ck::bf6x32_pk_t>
     std::normal_distribution<float> distribution;
 
     GeneratorTensor_4(float mean, float stddev, unsigned int seed = 1)
-        : generator(seed), distribution(mean, stddev){};
+        : generator(seed), distribution(mean, stddev) {};
 
     template <typename... Is>
     ck::bf6x32_pk_t operator()(Is...)
diff --git a/include/ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp b/include/ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp
index d86f01e255..f326c4a28d 100644
--- a/include/ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp
+++ b/include/ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp
@@ -279,7 +279,7 @@ struct Subtract
 
 struct Bilinear
 {
-    Bilinear(float alpha = 1.f, float beta = 1.f) : alpha_(alpha), beta_(beta){};
+    Bilinear(float alpha = 1.f, float beta = 1.f) : alpha_(alpha), beta_(beta) {};
 
     template <typename Y, typename X0, typename X1>
     __host__ __device__ constexpr void operator()(Y&, const X0&, const X1&) const;
@@ -354,7 +354,7 @@ struct Bilinear
 struct AddClamp
 {
     AddClamp(float floor = 0.f, float ceil = NumericLimits<float>::Max())
-        : floor_(floor), ceil_(ceil){};
+        : floor_(floor), ceil_(ceil) {};
 
     template <typename Y, typename X0, typename X1>
     __host__ __device__ constexpr void operator()(Y& y, const X0& x0, const X1& x1) const;
diff --git a/include/ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp b/include/ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp
index 4a87e8a277..80b8306a51 100644
--- a/include/ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp
+++ b/include/ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp
@@ -756,7 +756,7 @@ struct UnarySqrt
 struct Clamp
 {
     Clamp(float floor = 0.f, float ceil = NumericLimits<float>::Max())
-        : floor_(floor), ceil_(ceil){};
+        : floor_(floor), ceil_(ceil) {};
 
     template <typename Y, typename X>
     __host__ __device__ constexpr void operator()(Y& y, const X& x) const;
@@ -1324,7 +1324,7 @@ struct Swish
 
 struct SoftRelu
 {
-    SoftRelu(float alpha = 1.f) : alpha_(alpha){};
+    SoftRelu(float alpha = 1.f) : alpha_(alpha) {};
 
     template <typename T>
     __host__ __device__ void operator()(T& y, const T& x) const
@@ -1353,7 +1353,7 @@ struct SoftRelu
 struct Power
 {
     Power(float alpha = 0.f, float beta = 1.f, float gamma = 2.f)
-        : alpha_(alpha), beta_(beta), gamma_(gamma){};
+        : alpha_(alpha), beta_(beta), gamma_(gamma) {};
 
     template <typename T>
     __host__ __device__ void operator()(T& y, const T& x) const
@@ -1386,7 +1386,7 @@ struct Power
 
 struct ClippedRelu
 {
-    ClippedRelu(float alpha = 0.f, float beta = 1.f) : alpha_(alpha), beta_(beta){};
+    ClippedRelu(float alpha = 0.f, float beta = 1.f) : alpha_(alpha), beta_(beta) {};
 
     template <typename T>
     __host__ __device__ void operator()(T& y, const T& x) const
@@ -1415,7 +1415,7 @@ struct ClippedRelu
 
 struct LeakyRelu
 {
-    LeakyRelu(float alpha = 0.01f) : alpha_(alpha){};
+    LeakyRelu(float alpha = 0.01f) : alpha_(alpha) {};
 
     template <typename T>
     __host__ __device__ void operator()(T& y, const T& x) const
@@ -1442,7 +1442,7 @@ struct LeakyRelu
 
 struct Elu
 {
-    Elu(float alpha = 1.f) : alpha_(alpha){};
+    Elu(float alpha = 1.f) : alpha_(alpha) {};
 
     template <typename T>
     __host__ __device__ void operator()(T& y, const T& x) const
@@ -1469,7 +1469,7 @@ struct Elu
 
 struct Logistic
 {
-    Logistic(float alpha = 1.f) : alpha_(alpha){};
+    Logistic(float alpha = 1.f) : alpha_(alpha) {};
 
     template <typename T>
     __host__ __device__ void operator()(T& y, const T& x) const
diff --git a/include/ck_tile/core/config.hpp b/include/ck_tile/core/config.hpp
index 97c60cf062..5f83c97968 100644
--- a/include/ck_tile/core/config.hpp
+++ b/include/ck_tile/core/config.hpp
@@ -152,7 +152,7 @@
 // buffer atomic add: floating point
 #ifndef __HIP_DEVICE_COMPILE__ // for host code
 #define CK_TILE_USE_AMD_BUFFER_ATOMIC_ADD_FLOAT 1
-#elif defined(__gfx9__) || defined(__gfx12__)// for GPU code
+#elif defined(__gfx9__) || defined(__gfx12__) // for GPU code
 #define CK_TILE_USE_AMD_BUFFER_ATOMIC_ADD_FLOAT 1
 #else // for GPU code
 #define CK_TILE_USE_AMD_BUFFER_ATOMIC_ADD_FLOAT 0
diff --git a/include/ck_tile/ops/elementwise/unary_element_wise_operation.hpp b/include/ck_tile/ops/elementwise/unary_element_wise_operation.hpp
index 0e385901ed..8a97231030 100644
--- a/include/ck_tile/ops/elementwise/unary_element_wise_operation.hpp
+++ b/include/ck_tile/ops/elementwise/unary_element_wise_operation.hpp
@@ -1308,7 +1308,7 @@ struct Swish
 
 struct SoftRelu
 {
-    SoftRelu(float alpha = 1.f) : alpha_(alpha){};
+    SoftRelu(float alpha = 1.f) : alpha_(alpha) {};
 
     template <typename T>
     CK_TILE_HOST_DEVICE void operator()(T& y, const T& x) const
@@ -1327,7 +1327,7 @@ struct SoftRelu
 struct Power
 {
     Power(float alpha = 0.f, float beta = 1.f, float gamma = 2.f)
-        : alpha_(alpha), beta_(beta), gamma_(gamma){};
+        : alpha_(alpha), beta_(beta), gamma_(gamma) {};
 
     template <typename T>
     CK_TILE_HOST_DEVICE void operator()(T& y, const T& x) const
@@ -1349,7 +1349,7 @@ struct Power
 
 struct ClippedRelu
 {
-    ClippedRelu(float alpha = 0.f, float beta = 1.f) : alpha_(alpha), beta_(beta){};
+    ClippedRelu(float alpha = 0.f, float beta = 1.f) : alpha_(alpha), beta_(beta) {};
 
     template <typename T>
     CK_TILE_HOST_DEVICE void operator()(T& y, const T& x) const
@@ -1368,7 +1368,7 @@ struct ClippedRelu
 
 struct LeakyRelu
 {
-    LeakyRelu(float alpha = 0.01f) : alpha_(alpha){};
+    LeakyRelu(float alpha = 0.01f) : alpha_(alpha) {};
 
     template <typename T>
     CK_TILE_HOST_DEVICE void operator()(T& y, const T& x) const
@@ -1385,7 +1385,7 @@ struct LeakyRelu
 
 struct Elu
 {
-    Elu(float alpha = 1.f) : alpha_(alpha){};
+    Elu(float alpha = 1.f) : alpha_(alpha) {};
 
     template <typename T>
     CK_TILE_HOST_DEVICE void operator()(T& y, const T& x) const
@@ -1402,7 +1402,7 @@ struct Elu
 
 struct Logistic
 {
-    Logistic(float alpha = 1.f) : alpha_(alpha){};
+    Logistic(float alpha = 1.f) : alpha_(alpha) {};
 
     template <typename T>
     CK_TILE_HOST_DEVICE void operator()(T& y, const T& x) const
diff --git a/include/ck_tile/ops/gemm/warp/warp_gemm_attribute_wmma_impl.hpp b/include/ck_tile/ops/gemm/warp/warp_gemm_attribute_wmma_impl.hpp
index 4e5b9adc53..13727d41b1 100644
--- a/include/ck_tile/ops/gemm/warp/warp_gemm_attribute_wmma_impl.hpp
+++ b/include/ck_tile/ops/gemm/warp/warp_gemm_attribute_wmma_impl.hpp
@@ -77,32 +77,14 @@ struct WarpGemmAttributeWmmaImpl
 };
 
 using DeviceIp = remove_cvref_t<decltype(ck_tile::get_device_arch())>;
-using WarpGemmAttributeWmmaImpl_f32_16x16x16_f16_f16 = WarpGemmAttributeWmmaImpl<WmmaTraits<
-    DeviceIp,
-    fp16_t,
-    fp16_t,
-    float,
-    16,
-    16,
-    16>>;
+using WarpGemmAttributeWmmaImpl_f32_16x16x16_f16_f16 =
+    WarpGemmAttributeWmmaImpl<WmmaTraits<DeviceIp, fp16_t, fp16_t, float, 16, 16, 16>>;
 
-using WarpGemmAttributeWmmaImpl_f32_16x16x16_bf16_bf16 = WarpGemmAttributeWmmaImpl<WmmaTraits<
-    DeviceIp,
-    bf16_t,
-    bf16_t,
-    float,
-    16,
-    16,
-    16>>;
+using WarpGemmAttributeWmmaImpl_f32_16x16x16_bf16_bf16 =
+    WarpGemmAttributeWmmaImpl<WmmaTraits<DeviceIp, bf16_t, bf16_t, float, 16, 16, 16>>;
 
-using WarpGemmAttributeWmmaImpl_i32_16x16x16_i8_i8 = WarpGemmAttributeWmmaImpl<WmmaTraits<
-    DeviceIp,
-    int8_t,
-    int8_t,
-    int32_t,
-    16,
-    16,
-    16>>;
+using WarpGemmAttributeWmmaImpl_i32_16x16x16_i8_i8 =
+    WarpGemmAttributeWmmaImpl<WmmaTraits<DeviceIp, int8_t, int8_t, int32_t, 16, 16, 16>>;
 
 using WarpGemmAttributeWmmaImpl_f32_16x16x16_f8_f8 =
     WarpGemmAttributeWmmaImpl<WmmaTraits<gfx12_t, fp8_t, fp8_t, float, 16, 16, 16>>;