Format

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

@@ -47,15 +47,12 @@ __device__ void generic_binary_layernorm(
 {
     using reduce_output = reduce::with_axis<Input1, Axis>;
     reduce::block::run<reduce_output>([&](auto, auto r) {
-        auto input = r.inner([&](auto x1, auto x2) {
-            return op(x1, x2);
-        })(input1, input2);
-        using value_type         = typename Input1::type;
+        auto input       = r.inner([&](auto x1, auto x2) { return op(x1, x2); })(input1, input2);
+        using value_type = typename Input1::type;
         constexpr auto relements = r.template elements<Input1>();
-        auto means =
-            r.reduce(op::sum{}, make_array<vec_type<value_type>>(0, 0), [&](auto x) {
-                return make_array(x, x * x) * vec_type<value_type>{1.0 / relements};
-            })(input);
+        auto means = r.reduce(op::sum{}, make_array<vec_type<value_type>>(0, 0), [&](auto x) {
+            return make_array(x, x * x) * vec_type<value_type>{1.0 / relements};
+        })(input);
 
         auto mean_x        = means[0];
         auto mean_x2       = means[1];

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

@@ -171,7 +171,7 @@ struct inner_storage_tag
 {
 };
 
-template<class T>
+template <class T>
 using is_inner_storage = is_base_of<inner_storage_tag, remove_cv_t<remove_reference_t<T>>>;
 
 template <class R, class F>