Format

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

@@ -7,51 +7,51 @@
 
 namespace migraphx {
 
-template<class Tensor>
+template <class Tensor>
 constexpr auto gemm_get_batches()
 {
-    constexpr auto lens = get_shape_c<Tensor>{}.lens;
-    constexpr auto strides = get_shape_c<Tensor>{}.strides;
-    constexpr auto new_lens = sequence(lens.size() - _c<2>, [&](auto... is) {
-        return make_const_array(_c<lens[is]>...);
-    });
-    constexpr auto new_strides = sequence(strides.size() - _c<2>, [&](auto... is) {
-        return make_const_array(_c<strides[is]>...);
-    });
+    constexpr auto lens     = get_shape_c<Tensor>{}.lens;
+    constexpr auto strides  = get_shape_c<Tensor>{}.strides;
+    constexpr auto new_lens = sequence(
+        lens.size() - _c<2>, [&](auto... is) { return make_const_array(_c<lens[is]>...); });
+    constexpr auto new_strides = sequence(
+        strides.size() - _c<2>, [&](auto... is) { return make_const_array(_c<strides[is]>...); });
     return make_shape(new_lens, new_strides);
 }
 
-template<class Tensor>
+template <class Tensor>
 constexpr auto gemm_get_matrix()
 {
-    constexpr auto lens = get_shape_c<Tensor>{}.lens;
-    constexpr auto strides = get_shape_c<Tensor>{}.strides;
-    constexpr auto m = lens.size() - _c<2>;
-    constexpr auto n = lens.size() - _c<1>;
-    constexpr auto new_lens = make_const_array(_c<lens[m]>, _c<lens[n]>);
+    constexpr auto lens        = get_shape_c<Tensor>{}.lens;
+    constexpr auto strides     = get_shape_c<Tensor>{}.strides;
+    constexpr auto m           = lens.size() - _c<2>;
+    constexpr auto n           = lens.size() - _c<1>;
+    constexpr auto new_lens    = make_const_array(_c<lens[m]>, _c<lens[n]>);
     constexpr auto new_strides = make_const_array(_c<strides[m]>, _c<strides[n]>);
     return make_shape(new_lens, new_strides);
 }
 
-template<class Tensor, class T>
+template <class Tensor, class T>
 constexpr auto gemm_batch_slice(Tensor t, T i)
 {
-    constexpr auto batch = gemm_get_batches<Tensor>();
+    constexpr auto batch  = gemm_get_batches<Tensor>();
     constexpr auto matrix = gemm_get_matrix<Tensor>();
     return make_tensor_view(t.data() + batch.index(i), matrix);
 }
 
-template<class BlocksPerBatch, class T, class... Ts>
+template <class BlocksPerBatch, class T, class... Ts>
 constexpr auto gemm_batch_args(index idx, BlocksPerBatch bpb, T x, Ts... xs)
 {
     return [=](auto f) {
         // All tensors should have the same rank
-        static_assert((true and ... and (get_shape_c<T>{}.lens.size() == get_shape_c<Ts>{}.lens.size())));
+        static_assert(
+            (true and ... and (get_shape_c<T>{}.lens.size() == get_shape_c<Ts>{}.lens.size())));
         if constexpr(get_shape_c<T>{}.lens.size() > 2)
         {
             // Get the first batch since all batches should have the same number of elements
             constexpr auto batch = gemm_get_batches<T>();
-            static_assert((true and ... and (batch.elements() == gemm_get_batches<Ts>().elements())));
+            static_assert(
+                (true and ... and (batch.elements() == gemm_get_batches<Ts>().elements())));
             idx.group_stride(bpb * batch.elements(), [&](auto gidx) {
                 const auto batch_idx = gidx / bpb;
                 f(gemm_batch_slice(x, batch_idx), gemm_batch_slice(xs, batch_idx)...);
@@ -59,7 +59,7 @@ constexpr auto gemm_batch_args(index idx, BlocksPerBatch bpb, T x, Ts... xs)
         }
         else
         {
-            f(x, xs...);    
+            f(x, xs...);
         }
     };
 }