clang format

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

@@ -14,17 +14,19 @@ inline namespace MIGRAPHX_INLINE_NS {
 namespace gpu {
 namespace device {
 
-template<class T>
-struct val_index {
+template <class T>
+struct val_index
+{
     T val;
     int64_t index;
 
-//  MIGRAPHX_DEVICE_CONSTEXPR val_index(T v, int64_t idx) : val(v), index(idx) { }
+    //  MIGRAPHX_DEVICE_CONSTEXPR val_index(T v, int64_t idx) : val(v), index(idx) { }
 };
 
-template<class T>
-struct argmax_op {
-    MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const 
+template <class T>
+struct argmax_op
+{
+    MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
     {
         if(x.val > y.val)
             return x;
@@ -36,14 +38,13 @@ struct argmax_op {
         }
     }
 
-    MIGRAPHX_DEVICE_CONSTEXPR T init() const {
-        return lowest();
-    }
+    MIGRAPHX_DEVICE_CONSTEXPR T init() const { return lowest(); }
 };
 
-template<class T>
-struct argmin_op {
-    MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const 
+template <class T>
+struct argmin_op
+{
+    MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
     {
         if(x.val < y.val)
             return x;
@@ -55,9 +56,7 @@ struct argmin_op {
         }
     }
 
-    MIGRAPHX_DEVICE_CONSTEXPR T init() const {
-        return highest();
-    }
+    MIGRAPHX_DEVICE_CONSTEXPR T init() const { return highest(); }
 };
 
 template <class T, class Op>
@@ -73,28 +72,27 @@ void arg_op(Op op, hipStream_t stream, const argument& result, const argument& a
     hip_visit_all(arg, arg_shape, batch_shape)([&](auto input, auto arg_s, auto batch_s) {
         auto output = device_cast(result.get<int64_t>().data());
         // use one block for items in one batch.
-        const size_t max_block_size = 256;
-        const std::size_t block_size     = compute_block_size(batch_item_num, max_block_size);
-        gs_launch(stream,
-                  batch_shape.elements() * block_size,
-                  block_size)([=](auto i, auto idx) __device__ {
-            auto batch_idx = batch_s.multi(i / block_size);
-            auto data_idx = batch_idx;
-            T init_val = op.init();
-            val_index<T> init = {init_val, -1};
+        const size_t max_block_size  = 256;
+        const std::size_t block_size = compute_block_size(batch_item_num, max_block_size);
+        gs_launch(stream, batch_shape.elements() * block_size, block_size)(
+            [=](auto i, auto idx) __device__ {
+                auto batch_idx    = batch_s.multi(i / block_size);
+                auto data_idx     = batch_idx;
+                T init_val        = op.init();
+                val_index<T> init = {init_val, -1};
 
-            auto op_output = block_reduce<max_block_size, Op, val_index<T>>(
-                idx, op, init, batch_item_num, [&](auto j) __device__ {
-                    data_idx[axis] = j;
-                    T val = input[arg_s.index(data_idx)];
-                    return val_index<T>{val, static_cast<int64_t>(j)};
-            });
+                auto op_output = block_reduce<max_block_size, Op, val_index<T>>(
+                    idx, op, init, batch_item_num, [&](auto j) __device__ {
+                        data_idx[axis] = j;
+                        T val          = input[arg_s.index(data_idx)];
+                        return val_index<T>{val, static_cast<int64_t>(j)};
+                    });
 
-            if(idx.local == 0)
-            {
-                output[batch_s.index(batch_idx)] = op_output.index;
-            }
-        });
+                if(idx.local == 0)
+                {
+                    output[batch_s.index(batch_idx)] = op_output.index;
+                }
+            });
     });
 }