Formatting

src/targets/gpu/jit/ck_gemm.cpp

@@ -38,7 +38,6 @@
 #include <migraphx/env.hpp>
 #include <migraphx/file_buffer.hpp>
 
-
 #include "ck/ck.hpp"
 #include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
 #include "ck/tensor_operation/gpu/device/device_gemm_multiple_d.hpp"
@@ -64,7 +63,6 @@ MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_CK_TUNING);
 MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_CK_TUNING_VALUE);
 MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_CK_DEBUG);
 
-
 // NOLINTNEXTLINE
 static const char* const ck_gemm_kernel = R"__migraphx__(
 #include <args.hpp>
@@ -312,10 +310,12 @@ struct ck_gemm_compiler : compiler<ck_gemm_compiler>
         const bool transCDE    = transposed_matrix(c_shape);
         const auto a_type      = get_type(a_shape);
         const auto b_type      = get_type(b_shape);
-        const auto cde_type = ck_tuple(inputs.begin() + 2, inputs.end() - 1, &get_type);//get_type(c_shape);
+        const auto cde_type =
+            ck_tuple(inputs.begin() + 2, inputs.end() - 1, &get_type); // get_type(c_shape);
         const auto cde_layout = ck_tuple(inputs.begin() + 2, inputs.end() - 1, &get_layout);
 
-        std::string ck_passthrough = "ck_passthrough";//"ck::tensor_operation::element_wise::PassThrough";
+        std::string ck_passthrough =
+            "ck_passthrough"; //"ck::tensor_operation::element_wise::PassThrough";
         std::string cde_op = ck_passthrough;
         assert(inputs.size() < 4 or v.contains("post"));
         if(v.contains("post"))
@@ -323,10 +323,22 @@ struct ck_gemm_compiler : compiler<ck_gemm_compiler>
             cde_op = v.at("post").to<std::string>();
         }
 
-        auto problem = ck::tensor_operation::device::instance::Problem{static_cast<ck::index_t>(m), static_cast<ck::index_t>(n), static_cast<ck::index_t>(k), static_cast<ck::index_t>(numDTensors), static_cast<ck::index_t>(tuning_value),  
-                                transA, transB, transCDE,
-                                a_type, b_type, cde_type,
-                                ck_passthrough, ck_passthrough, cde_op, cde_layout};
+        auto problem =
+            ck::tensor_operation::device::instance::Problem{static_cast<ck::index_t>(m),
+                                                            static_cast<ck::index_t>(n),
+                                                            static_cast<ck::index_t>(k),
+                                                            static_cast<ck::index_t>(numDTensors),
+                                                            static_cast<ck::index_t>(tuning_value),
+                                                            transA,
+                                                            transB,
+                                                            transCDE,
+                                                            a_type,
+                                                            b_type,
+                                                            cde_type,
+                                                            ck_passthrough,
+                                                            ck_passthrough,
+                                                            cde_op,
+                                                            cde_layout};
         const auto solution   = problem.GetSolution();
         auto blocks_per_batch = problem.GetGridSize();
         auto block_size       = problem.GetBlockSize();