clean (#143)

include/ck/tensor_operation/gpu/device/device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk.hpp

@@ -468,7 +468,7 @@ struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
                     {
                         continue;
                     }
-                    
+
                     const auto descs = DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(
                         N,
                         K,

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_i8_i32_i8.hpp

@@ -19,7 +19,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int32_t, int8_t, 0, 0, 0, 2, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int32_t, int8_t, 5, 0, 0, 4, 3); // for AVG
 ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int32_t, int8_t, 5, 0, 0, 4, 4);       
 ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int32_t, int8_t, 5, 0, 0, 4, 1);       
-ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int32_t, int8_t, 5, 0, 0, 2, 1);       
+ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int32_t, int8_t, 5, 0, 0, 2, 1);
 // clang-format on
 
 } // namespace device_reduce_instance

library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instance.cpp

@@ -10,7 +10,7 @@ namespace device {
 namespace device_gemm_instance {
 
 using BF16 = ck::bhalf_t;
-using F32 = float;
+using F32  = float;
 
 using Row = ck::tensor_layout::gemm::RowMajor;
 using Col = ck::tensor_layout::gemm::ColumnMajor;
@@ -21,8 +21,9 @@ using S = ck::Sequence<Is...>;
 using PassThrough = ck::tensor_operation::element_wise::PassThrough;
 
 // Compilation parameters for a[k, m] * b[k, n] = c[m, n]
-using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instances = std::tuple<
-    // clang-format off
+using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instances =
+    std::tuple<
+        // clang-format off
         //#####################| AData|  BData|  CData| AccData|  CShuffle| ALayout| BLayout| CLayout|           A|           B|           C| Block|  MPer|  NPer|  KPer| AK1| BK1| MPer| NPer| MXdl| NXdl|  ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds|  BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds|    CShuffle|    CShuffle|     CBlockTransferClusterLengths|  CBlockTransfer|
         //#####################|  Type|   Type|   Type|    Type|  DataType|        |        |        | Elementwise| Elementwise| Elementwise|  Size| Block| Block| Block|    |    |  XDL|  XDL|  Per|  Per|   ThreadCluster|  ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|   ThreadCluster|  ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
         //#####################|      |       |       |        |          |        |        |        |   Operation|   Operation|   Operation|      |      |      |      |    |    |     |     | Wave| Wave| Lengths_K0_M_K1|   ArrangeOrder|               |               |      PerVector|   PerVector_K1|          | Lengths_K0_N_K1|   ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl|   _NWaveNPerXdl|
@@ -43,8 +44,8 @@ using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instances = std::tuple<
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Col,      Row,    Row, PassThrough, PassThrough, PassThrough,   256,   128,    64,    32,   8,   8,   32,   32,    2,    1,     S<4, 64, 1>,     S<0, 2, 1>,     S<0, 2, 1>,              1,              2,              8,      true,     S<4, 64, 1>,     S<0, 2, 1>,     S<0, 2, 1>,             1,              1,              8,      true,           1,           1,             S<1, 1, 16, 1, 1, 4>,               8>,
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Col,      Row,    Row, PassThrough, PassThrough, PassThrough,   256,    64,   128,    32,   2,   2,   32,   32,    1,    2,     S<16,16, 1>,     S<0, 2, 1>,     S<0, 2, 1>,              1,              4,              2,     false,     S<8, 32, 1>,     S<0, 2, 1>,     S<0, 2, 1>,             1,              4,              2,     false,           1,           1,             S<1, 1, 32, 1, 1, 8>,               8>,
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Col,      Row,    Row, PassThrough, PassThrough, PassThrough,   256,    64,   128,    32,   8,   8,   32,   32,    1,    2,     S<4, 64, 1>,     S<0, 2, 1>,     S<0, 2, 1>,              1,              1,              8,      true,     S<4, 64, 1>,     S<0, 2, 1>,     S<0, 2, 1>,             1,              2,              8,      true,           1,           1,             S<1, 1, 32, 1, 1, 8>,               8>
-    // clang-format on
-    >;
+        // clang-format on
+        >;
 
 void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instances(
     std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)

library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instance.cpp

@@ -10,7 +10,7 @@ namespace device {
 namespace device_gemm_instance {
 
 using BF16 = ck::bhalf_t;
-using F32 = float;
+using F32  = float;
 
 using Row = ck::tensor_layout::gemm::RowMajor;
 using Col = ck::tensor_layout::gemm::ColumnMajor;
@@ -21,8 +21,9 @@ using S = ck::Sequence<Is...>;
 using PassThrough = ck::tensor_operation::element_wise::PassThrough;
 
 // Compilation parameters for a[k, m] * b[n, k] = c[m, n]
-using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instances = std::tuple<
-    // clang-format off
+using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instances =
+    std::tuple<
+        // clang-format off
         //#####################| AData|  BData|  CData| AccData|  CShuffle| ALayout| BLayout| CLayout|           A|           B|           C| Block|  MPer|  NPer|  KPer| AK1| BK1| MPer| NPer| MXdl| NXdl|  ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds|  BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds|    CShuffle|    CShuffle|     CBlockTransferClusterLengths|  CBlockTransfer|
         //#####################|  Type|   Type|   Type|    Type|  DataType|        |        |        | Elementwise| Elementwise| Elementwise|  Size| Block| Block| Block|    |    |  XDL|  XDL|  Per|  Per|   ThreadCluster|  ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|   ThreadCluster|  ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
         //#####################|      |       |       |        |          |        |        |        |   Operation|   Operation|   Operation|      |      |      |      |    |    |     |     | Wave| Wave| Lengths_K0_M_K1|   ArrangeOrder|               |               |      PerVector|   PerVector_K1|          | Lengths_K0_N_K1|   ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl|   _NWaveNPerXdl|
@@ -43,8 +44,8 @@ using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instances = std::tuple<
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Col,      Col,    Row, PassThrough, PassThrough, PassThrough,   256,   128,    64,    32,   8,   8,   32,   32,    2,    1,     S<4, 64, 1>,     S<0, 2, 1>,     S<0, 2, 1>,              1,              2,              8,      true,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,      true,           1,           1,             S<1, 1, 16, 1, 1, 4>,               8>,
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Col,      Col,    Row, PassThrough, PassThrough, PassThrough,   256,    64,   128,    32,   2,   8,   32,   32,    1,    2,     S<16,16, 1>,     S<0, 2, 1>,     S<0, 2, 1>,              1,              4,              2,     false,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,      true,           1,           1,             S<1, 1, 32, 1, 1, 8>,               8>,
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Col,      Col,    Row, PassThrough, PassThrough, PassThrough,   256,    64,   128,    32,   8,   8,   32,   32,    1,    2,     S<4, 64, 1>,     S<0, 2, 1>,     S<0, 2, 1>,              1,              1,              8,      true,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,      true,           1,           1,             S<1, 1, 32, 1, 1, 8>,               8>
-    // clang-format on
-    >;
+        // clang-format on
+        >;
 
 void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instances(
     std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)

library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instance.cpp

@@ -10,7 +10,7 @@ namespace device {
 namespace device_gemm_instance {
 
 using BF16 = ck::bhalf_t;
-using F32 = float;
+using F32  = float;
 
 using Row = ck::tensor_layout::gemm::RowMajor;
 using Col = ck::tensor_layout::gemm::ColumnMajor;
@@ -21,8 +21,9 @@ using S = ck::Sequence<Is...>;
 using PassThrough = ck::tensor_operation::element_wise::PassThrough;
 
 // Compilation parameters for a[m, k] * b[k, n] = c[m, n]
-using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instances = std::tuple<
-    // clang-format off
+using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instances =
+    std::tuple<
+        // clang-format off
         //#####################| AData|  BData|  CData| AccData|  CShuffle| ALayout| BLayout| CLayout|           A|           B|           C| Block|  MPer|  NPer|  KPer| AK1| BK1| MPer| NPer| MXdl| NXdl|  ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds|  BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds|    CShuffle|    CShuffle|     CBlockTransferClusterLengths|  CBlockTransfer|
         //#####################|  Type|   Type|   Type|    Type|  DataType|        |        |        | Elementwise| Elementwise| Elementwise|  Size| Block| Block| Block|    |    |  XDL|  XDL|  Per|  Per|   ThreadCluster|  ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|   ThreadCluster|  ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
         //#####################|      |       |       |        |          |        |        |        |   Operation|   Operation|   Operation|      |      |      |      |    |    |     |     | Wave| Wave| Lengths_K0_M_K1|   ArrangeOrder|               |               |      PerVector|   PerVector_K1|          | Lengths_K0_N_K1|   ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl|   _NWaveNPerXdl|
@@ -43,8 +44,8 @@ using device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instances = std::tuple<
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Row,      Row,    Row, PassThrough, PassThrough, PassThrough,   256,   128,    64,    32,   8,   8,   32,   32,    2,    1,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      true,     S<4, 64, 1>,     S<0, 2, 1>,     S<0, 2, 1>,             1,              1,              8,      true,           1,           1,             S<1, 1, 16, 1, 1, 4>,               8>,
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Row,      Row,    Row, PassThrough, PassThrough, PassThrough,   256,    64,   128,    32,   8,   2,   32,   32,    1,    2,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      true,     S<8, 32, 1>,     S<0, 2, 1>,     S<0, 2, 1>,             1,              4,              2,     false,           1,           1,             S<1, 1, 32, 1, 1, 8>,               8>,
         DeviceGemmXdl_C_Shuffle<  BF16,   BF16,   BF16,     F32,      BF16,     Row,      Row,    Row, PassThrough, PassThrough, PassThrough,   256,    64,   128,    32,   8,   8,   32,   32,    1,    2,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      true,     S<4, 64, 1>,     S<0, 2, 1>,     S<0, 2, 1>,             1,              2,              8,      true,           1,           1,             S<1, 1, 32, 1, 1, 8>,               8>
-    // clang-format on
-    >;
+        // clang-format on
+        >;
 
 void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instances(
     std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)

library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instance.cpp

@@ -47,11 +47,33 @@ using device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances = std::tuple<
 
 // using device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_irregular_tile_instances = std::tuple<
 //     // clang-format off
-//         //#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout|           A|           B|           C|          GEMM| Block|  MPer|  NPer| K0Per| K1| MPer| NPer| MXdl| NXdl|  ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds|  BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds|    CShuffle|    CShuffle|     CBlockTransferClusterLengths|  CBlockTransfer|
-//         //#########################| Type|  Type|  Type|    Type|        |        |        | Elementwise| Elementwise| Elementwise|Spacialization|  Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|  ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|   ThreadCluster|  ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
-//         //#########################|     |      |      |        |        |        |        |   Operation|   Operation|   Operation|              |      |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|   ArrangeOrder|               |               |      PerVector|   PerVector_K1|          | Lengths_K0_N_K1|   ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl|   _NWaveNPerXdl|
-//         //#########################|     |      |      |        |        |        |        |            |            |            |              |      |      |      |      |   |     |     |     |     |                |               |               |               |               |               |          |                |               |               |              |               |               |          |            |            |                                 |                |
-//         DeviceGemmXdlSplitKCShuffle<   F16,   F16,   F16,     F32,     Row,     Col,     Row, PassThrough, PassThrough, PassThrough,   GemmDefault,   256,   128,   144,     4,  8,   16,   16,    2,    9,  S<1, 4, 64, 1>,  S<0, 2, 1, 3>,  S<0, 2, 1, 3>,              3,              8,              8,      true,  S<1, 4, 16, 4>,  S<0, 2, 1, 3>,  S<0, 2, 1, 3>,             3,              2,              2,      true,           1,           9,                   S<1, 2, 1, 72>,               2>
+//         //#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A|
+//         B|           C|          GEMM| Block|  MPer|  NPer| K0Per| K1| MPer| NPer| MXdl| NXdl|
+//         ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer|
+//         ABlockTransfer| ABlockLds|  BBlockTransfer| BBlockTransfer| BBlockTransfer|
+//         BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds|    CShuffle|    CShuffle|
+//         CBlockTransferClusterLengths|  CBlockTransfer|
+//         //#########################| Type|  Type|  Type|    Type|        |        |        |
+//         Elementwise| Elementwise| Elementwise|Spacialization|  Size| Block| Block| Block|   |
+//         XDL|  XDL|  Per|  Per|   ThreadCluster|  ThreadCluster| SrcAccessOrder|   SrcVectorDim|
+//         SrcScalar|      DstScalar| AddExtraM|   ThreadCluster|  ThreadCluster| SrcAccessOrder|
+//         SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|
+//         _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
+//         //#########################|     |      |      |        |        |        |        |
+//         Operation|   Operation|   Operation|              |      |      |      |      |   |     |
+//         | Wave| Wave| Lengths_K0_M_K1|   ArrangeOrder|               |               | PerVector|
+//         PerVector_K1|          | Lengths_K0_N_K1|   ArrangeOrder|               |              |
+//         PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|
+//         _NBlock_NXdlPerWave_NWaveNPerXdl|   _NWaveNPerXdl|
+//         //#########################|     |      |      |        |        |        |        | | |
+//         |              |      |      |      |      |   |     |     |     |     |                |
+//         |               |               |               |               |          | | | | | | |
+//         |            |            |                                 |                |
+//         DeviceGemmXdlSplitKCShuffle<   F16,   F16,   F16,     F32,     Row,     Col,     Row,
+//         PassThrough, PassThrough, PassThrough,   GemmDefault,   256,   128,   144,     4,  8, 16,
+//         16,    2,    9,  S<1, 4, 64, 1>,  S<0, 2, 1, 3>,  S<0, 2, 1, 3>,              3, 8, 8,
+//         true,  S<1, 4, 16, 4>,  S<0, 2, 1, 3>,  S<0, 2, 1, 3>,             3,              2, 2,
+//         true,           1,           9,                   S<1, 2, 1, 72>,               2>
 //     // clang-format on
 //     >;
 

profiler/src/profiler.cpp

@@ -19,7 +19,6 @@ int profile_grouped_gemm(int, char*[]);
 
 int main(int argc, char* argv[])
 {
-#if 0
     if(strcmp(argv[1], "gemm") == 0)
     {
         return profile_gemm(argc, argv);
@@ -86,7 +85,4 @@ int main(int argc, char* argv[])
 
         return 0;
     }
-#else
-    profile_grouped_gemm(argc, argv);
-#endif
 }

test/gemm/gemm_bf16.cpp

@@ -32,10 +32,14 @@ namespace ck {
 namespace tensor_operation {
 namespace device {
 namespace device_gemm_instance {
-void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
-void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
-void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
-void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
+void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instances(
+    std::vector<DeviceGemmNoOpPtr>&);
+void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instances(
+    std::vector<DeviceGemmNoOpPtr>&);
+void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_nk_mn_instances(
+    std::vector<DeviceGemmNoOpPtr>&);
+void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instances(
+    std::vector<DeviceGemmNoOpPtr>&);
 } // namespace device_gemm_instance
 } // namespace device
 } // namespace tensor_operation

test/gemm/gemm_int8.cpp

@@ -32,11 +32,15 @@ namespace ck {
 namespace tensor_operation {
 namespace device {
 namespace device_gemm_instance {
-void add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
-void add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
-void add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
-void add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
-}
+void add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instances(
+    std::vector<DeviceGemmNoOpPtr>&);
+void add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instances(
+    std::vector<DeviceGemmNoOpPtr>&);
+void add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instances(
+    std::vector<DeviceGemmNoOpPtr>&);
+void add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instances(
+    std::vector<DeviceGemmNoOpPtr>&);
+} // namespace device_gemm_instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

test/include/test_util.hpp

@@ -55,10 +55,10 @@ check_err(const std::vector<T>& out,
 }
 
 bool check_err(const std::vector<_Float16>& out,
-                   const std::vector<_Float16>& ref,
-                   const std::string& msg,
-                   _Float16 rtol = static_cast<_Float16>(1e-3f),
-                   _Float16 atol = static_cast<_Float16>(1e-3f))
+               const std::vector<_Float16>& ref,
+               const std::string& msg,
+               _Float16 rtol = static_cast<_Float16>(1e-3f),
+               _Float16 atol = static_cast<_Float16>(1e-3f))
 {
     if(out.size() != ref.size())
     {
@@ -69,14 +69,14 @@ bool check_err(const std::vector<_Float16>& out,
     }
 
     bool res{true};
-    int err_count = 0;
-    double err         = 0;
-    double max_err     = std::numeric_limits<_Float16>::min();
+    int err_count  = 0;
+    double err     = 0;
+    double max_err = std::numeric_limits<_Float16>::min();
     for(std::size_t i = 0; i < ref.size(); ++i)
     {
         double out_ = double(out[i]);
         double ref_ = double(ref[i]);
-        err = std::abs(out_ - ref_);
+        err         = std::abs(out_ - ref_);
         if(err > atol + rtol * std::abs(ref_) || !std::isfinite(out_) || !std::isfinite(ref_))
         {
             max_err = err > max_err ? err : max_err;