Format

src/targets/gpu/kernels/include/migraphx/kernels/layernorm.hpp

@@ -41,9 +41,9 @@ __device__ void generic_binary_layernorm(
 {
     using reduce_output = reduce::with_axis<Input1, Axis>;
     reduce::block::run<reduce_output>([&](auto, auto r) {
-        using value_type = typename Input1::type;
+        using value_type         = typename Input1::type;
         constexpr auto relements = r.template elements<Input1>();
-        auto mean        = [&](auto f) {
+        auto mean                = [&](auto f) {
             return r.reduce(op::sum{}, 0, [&](auto x1, auto x2) {
                 return f(x1, x2) / value_type{relements};
             })(input1, input2);

src/targets/gpu/kernels/include/migraphx/kernels/reduce.hpp

@@ -225,11 +225,11 @@ struct block
             });
         }
 
-        template<class Input>
+        template <class Input>
         constexpr auto elements() const
         {
-            using reduce_type = decltype(slicer(Input{}));
-            using value_type = typename Input::type;
+            using reduce_type        = decltype(slicer(Input{}));
+            using value_type         = typename Input::type;
             constexpr auto relements = get_shape_c<reduce_type>{}.elements();
             if constexpr(vec_size<value_type>() > 1)
                 return relements * vec_size<value_type>();
@@ -294,7 +294,7 @@ struct lane
             });
         }
 
-        template<class Input>
+        template <class Input>
         constexpr auto elements() const
         {
             using reduce_type = decltype(slicer(Input{}));