Formatting

src/targets/gpu/compile_hip_code_object.cpp

@@ -167,7 +167,7 @@ operation compile_hip_code_object(const std::string& content, hip_compile_option
                        auto path   = fs::path{"migraphx"} / "kernels" / name;
                        return src_file{path, c};
                    });
-    if (not options.embedded_headers.empty())
+    if(not options.embedded_headers.empty())
     {
         std::transform(options.embedded_headers.begin(),
                        options.embedded_headers.end(),

src/targets/gpu/include/migraphx/gpu/compile_hip_code_object.hpp

@@ -42,8 +42,7 @@ struct hip_compile_options
     std::string kernel_name           = "kernel";
     std::string params                = "";
     std::vector<shape> virtual_inputs = {};
-    std::unordered_map<std::string, std::pair<const char*,const char*>> embedded_headers;
-
+    std::unordered_map<std::string, std::pair<const char*, const char*>> embedded_headers;
 
     /**
      * @brief Set the launch parameters but allow v to override the values

src/targets/gpu/jit/ck_gemm.cpp

@@ -40,7 +40,6 @@
 
 #include "ck/include/device_gemm_multiple_d.hpp"
 
-
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 
@@ -79,8 +78,6 @@ __global__ void ${kernel}(${params})
 
 )__migraphx__";
 
-
-
 static bool transposed_matrix(const shape& s) { return s.strides().back() != 1; }
 
 template <class F, class Action>
@@ -244,9 +241,15 @@ struct ck_gemm_compiler : compiler<ck_gemm_compiler>
         const auto b_type = get_type(b_shape);
         const auto e_type = get_type(c_shape);
         std::vector<bool> ds_layout;
-        std::transform(inputs.begin() + 2, inputs.end() - 1, std::back_inserter(ds_layout), [](const auto& i){ return transposed_matrix(i); });
+        std::transform(inputs.begin() + 2,
+                       inputs.end() - 1,
+                       std::back_inserter(ds_layout),
+                       [](const auto& i) { return transposed_matrix(i); });
         std::vector<std::string> ds_type;
-        std::transform(inputs.begin() + 2, inputs.end() - 1, std::back_inserter(ds_type), [](const auto& i){ return get_type(i); });
+        std::transform(inputs.begin() + 2,
+                       inputs.end() - 1,
+                       std::back_inserter(ds_type),
+                       [](const auto& i) { return get_type(i); });
 
         std::string ck_passthrough = "ck_passthrough";
         std::string cde_op         = ck_passthrough;
@@ -256,9 +259,8 @@ struct ck_gemm_compiler : compiler<ck_gemm_compiler>
             cde_op = v.at("post").to<std::string>();
         }
 
-        auto problem =
-            ck::tensor_operation::device::device_gemm_multiple_d::
-                                                    Problem{static_cast<ck::index_t>(m),
+        auto problem = ck::tensor_operation::device::device_gemm_multiple_d::Problem{
+            static_cast<ck::index_t>(m),
             static_cast<ck::index_t>(n),
             static_cast<ck::index_t>(k),
             transA,
@@ -281,7 +283,6 @@ struct ck_gemm_compiler : compiler<ck_gemm_compiler>
         const auto blocks_per_batch = solution.grid_size;
         const auto block_size       = solution.block_size;
 
-
         hip_compile_options options;
         options.embedded_headers = ck_headers;
         auto grid_size = can_fold_batch ? blocks_per_batch : batch_count * blocks_per_batch;