Formatting

src/targets/gpu/device/include/migraphx/gpu/device/nary.hpp

@@ -119,7 +119,8 @@ void nary_broadcast_impl(hipStream_t stream, F f, argument result, argument barg
 }
 
 template <class F, class... Arguments>
-void nary_double_broadcast_impl(hipStream_t stream, F f, argument result, argument barg1, argument barg2, Arguments... args)
+void nary_double_broadcast_impl(
+    hipStream_t stream, F f, argument result, argument barg1, argument barg2, Arguments... args)
 {
     const auto& output_shape = result.get_shape();
     const auto& b_shape      = barg1.get_shape();
@@ -135,30 +136,31 @@ void nary_double_broadcast_impl(hipStream_t stream, F f, argument result, argume
     const std::size_t nlocal  = 1024;
     const std::size_t nglobal = 256 * nlocal;
     std::size_t nelements     = result.get_shape().elements();
-    hip_visit_all(result, barg1, barg2, args...)([&](auto output, auto binput1, auto binput2, auto... inputs) {
-        using type = typename decltype(output)::value_type;
-        launch(stream, nglobal, nlocal)([=](auto idx) __device__ {
-            MIGRAPHX_DEVICE_SHARED type buffer[2048];
-            // Load bias into LDS
-            for(size_t i = idx.local; i < bdim_len; i += nlocal)
-            {
-                buffer[i] = binput1.data()[i];
-            }
-            for(size_t i = idx.local; i < bdim_len; i += nlocal)
-            {
-                buffer[i+bdim_len] = binput2.data()[i+bdim_len];
-            }
-            __syncthreads();
-            // Process the data
-            for(size_t i = idx.global; i < nelements; i += nglobal)
-            {
-                auto bidx        = (i % bdim_next_stride) / bdim_stride;
-                auto b1           = buffer[bidx];
-                auto b2           = buffer[bidx+bdim_len];
-                output.data()[i] = f(inputs.data()[i]..., b1, b2);
-            }
+    hip_visit_all(result, barg1, barg2, args...)(
+        [&](auto output, auto binput1, auto binput2, auto... inputs) {
+            using type = typename decltype(output)::value_type;
+            launch(stream, nglobal, nlocal)([=](auto idx) __device__ {
+                MIGRAPHX_DEVICE_SHARED type buffer[2048];
+                // Load bias into LDS
+                for(size_t i = idx.local; i < bdim_len; i += nlocal)
+                {
+                    buffer[i] = binput1.data()[i];
+                }
+                for(size_t i = idx.local; i < bdim_len; i += nlocal)
+                {
+                    buffer[i + bdim_len] = binput2.data()[i + bdim_len];
+                }
+                __syncthreads();
+                // Process the data
+                for(size_t i = idx.global; i < nelements; i += nglobal)
+                {
+                    auto bidx        = (i % bdim_next_stride) / bdim_stride;
+                    auto b1          = buffer[bidx];
+                    auto b2          = buffer[bidx + bdim_len];
+                    output.data()[i] = f(inputs.data()[i]..., b1, b2);
+                }
+            });
         });
-    });
 }
 
 template <class F, class... Arguments>
@@ -219,15 +221,15 @@ auto nary_standard(hipStream_t stream, argument result, Arguments... args)
     return [=](auto f) { nary_standard_impl(stream, f, result, args...); };
 }
 
-template<class... Arguments>
-bool broadcastable(bool &divisible_by_4, argument result, argument barg, Arguments... args)
+template <class... Arguments>
+bool broadcastable(bool& divisible_by_4, argument result, argument barg, Arguments... args)
 {
     divisible_by_4 = false;
-    auto bshape = barg.get_shape();
+    auto bshape    = barg.get_shape();
     const bool standard =
         all_of({args.get_shape()...}, [](const shape& s) { return s.standard(); });
-    const bool same_shapes = all_of(
-        {args.get_shape()...}, [&](const shape& s) { return s == result.get_shape(); });
+    const bool same_shapes =
+        all_of({args.get_shape()...}, [&](const shape& s) { return s == result.get_shape(); });
     // TODO: Check result and args shape is the same
     if(standard and same_shapes and bshape.broadcasted() and not bshape.scalar())
     {
@@ -241,16 +243,15 @@ bool broadcastable(bool &divisible_by_4, argument result, argument barg, Argumen
         if(b_len <= 2048 and std::none_of(std::next(b_it), strides.end(), not_zero))
         {
 
-            divisible_by_4 =
-                (b_len % 4 == 0) and (b_stride % 4 == 0) and
-                (front_args(args...).get_shape().elements() % 4 == 0);
+            divisible_by_4 = (b_len % 4 == 0) and (b_stride % 4 == 0) and
+                             (front_args(args...).get_shape().elements() % 4 == 0);
             return true;
         }
     }
     return false;
 }
 
-inline bool broadcastable(bool &divisible_by_4, argument, argument)
+inline bool broadcastable(bool& divisible_by_4, argument, argument)
 {
     divisible_by_4 = false;
     return false;
@@ -265,9 +266,7 @@ inline auto nary(hipStream_t stream, argument result)
 // Unary
 inline auto nary(hipStream_t stream, argument result, argument arg)
 {
-    return [=](auto f) {
-        nary_impl(stream, f, result, arg);
-    };
+    return [=](auto f) { nary_impl(stream, f, result, arg); };
 }
 
 // Binary
@@ -275,7 +274,7 @@ inline auto nary(hipStream_t stream, argument result, argument arg, argument bar
 {
     return [=](auto f) {
         bool divisible_by_4 = false;
-        if (broadcastable(divisible_by_4, result, barg, arg))
+        if(broadcastable(divisible_by_4, result, barg, arg))
         {
             if(divisible_by_4)
                 nary_broadcast_vec_impl(stream, f, result, barg, arg);
@@ -293,10 +292,10 @@ template <class... Arguments>
 auto nary(hipStream_t stream, argument result, Arguments... args)
 {
     return [=](auto f) {
-        auto barg1     = back_args(args...);
+        auto barg1    = back_args(args...);
         bool fallback = pop_back_args(args...)([&](auto&&... args2) {
             bool divisible_by_4 = false;
-            if (broadcastable(divisible_by_4, result, barg1, args2...))
+            if(broadcastable(divisible_by_4, result, barg1, args2...))
             {
                 if(divisible_by_4)
                     nary_broadcast_vec_impl(stream, f, result, barg1, args2...);