Format

src/targets/gpu/jit/reduce.cpp

@@ -125,7 +125,7 @@ struct reduce_compiler : compiler<reduce_compiler>
             // Vectorize if the axis is a reduction axis
             if(options.virtual_inputs.back().lens()[faxis] == 1)
                 vec = vectorize::elements(ctx, faxis, options.virtual_inputs);
-            auto relements = get_reduce_elements(options.virtual_inputs) / vec.size;
+            auto relements  = get_reduce_elements(options.virtual_inputs) / vec.size;
             auto block_size = compute_block_size(relements, 256);
             options.set_launch_params(
                 v, compute_global_for(ctx, nelements * block_size, 256), block_size);

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

@@ -460,7 +460,7 @@ struct lane
             }
         };
 
-        template<class Size, class F>
+        template <class Size, class F>
         constexpr inner_storage<Size, F> make_inner_storage(Size, F f)
         {
             return {f};
@@ -496,9 +496,7 @@ struct lane
         template <class R, class F, class N, class... Ts>
         __device__ auto inner_impl(F f, N n, Ts&&... xs) const
         {
-            return make_inner_storage(n, [=](auto j, auto d) {
-                return f(xs(j, d)...);
-            });
+            return make_inner_storage(n, [=](auto j, auto d) { return f(xs(j, d)...); });
         }
     };
     template <class Slicer>