add conv1d/3d bwd weight instances (#318)

* add conv1d/3d bwd weight instances

* add profiler code

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

@@ -996,8 +996,30 @@ struct DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_
                     0,
                     arg.c_grid_desc_mblock_mperblock_nblock_nperblock_.GetElementSpaceSize() *
                         sizeof(CDataType)));
+                float elapsed_time =
+                    launch_and_time_kernel(stream_config,
+                                           kernel,
+                                           dim3(grid_size),
+                                           dim3(BlockSize),
+                                           0,
+                                           arg.p_a_grid_,
+                                           arg.p_b_grid_,
+                                           arg.p_c_grid_,
+                                           arg.a_grid_desc_kbatch_k0_m_k1_,
+                                           arg.b_grid_desc_kbatch_k0_n_k1_,
+                                           arg.c_grid_desc_mblock_mperblock_nblock_nperblock_,
+                                           arg.a_element_op_,
+                                           arg.b_element_op_,
+                                           arg.c_element_op_,
+                                           arg.block_2_ctile_map_);
 
-                return launch_and_time_kernel(stream_config,
+                hipGetErrorString(hipMemset(
+                    arg.p_c_grid_,
+                    0,
+                    arg.c_grid_desc_mblock_mperblock_nblock_nperblock_.GetElementSpaceSize() *
+                        sizeof(CDataType)));
+
+                launch_and_time_kernel(StreamConfig{nullptr, false},
                                        kernel,
                                        dim3(grid_size),
                                        dim3(BlockSize),
@@ -1012,6 +1034,8 @@ struct DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_
                                        arg.b_element_op_,
                                        arg.c_element_op_,
                                        arg.block_2_ctile_map_);
+
+                return elapsed_time;
             };
 
             // run kernel for bf16 with splitk
@@ -1022,7 +1046,8 @@ struct DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_
                     arg.c_grid_desc_mblock_mperblock_nblock_nperblock_.GetElementSpaceSize() *
                         sizeof(AccDataType)));
 
-                return launch_and_time_kernel(stream_config,
+                float elapsed_time =
+                    launch_and_time_kernel(stream_config,
                                            kernel,
                                            dim3(grid_size),
                                            dim3(BlockSize),
@@ -1037,6 +1062,30 @@ struct DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_
                                            arg.b_element_op_,
                                            arg.c_element_op_,
                                            arg.block_2_ctile_map_);
+
+                hipGetErrorString(hipMemset(
+                    arg.p_workspace_,
+                    0,
+                    arg.c_grid_desc_mblock_mperblock_nblock_nperblock_.GetElementSpaceSize() *
+                        sizeof(AccDataType)));
+
+                launch_and_time_kernel(StreamConfig{nullptr, false},
+                                       kernel,
+                                       dim3(grid_size),
+                                       dim3(BlockSize),
+                                       0,
+                                       arg.p_a_grid_,
+                                       arg.p_b_grid_,
+                                       static_cast<AccDataType*>(arg.p_workspace_),
+                                       arg.a_grid_desc_kbatch_k0_m_k1_,
+                                       arg.b_grid_desc_kbatch_k0_n_k1_,
+                                       arg.c_grid_desc_mblock_mperblock_nblock_nperblock_,
+                                       arg.a_element_op_,
+                                       arg.b_element_op_,
+                                       arg.c_element_op_,
+                                       arg.block_2_ctile_map_);
+
+                return elapsed_time;
             };
 
             // kernel for type conversion
@@ -1210,6 +1259,20 @@ struct DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_
 
     static bool IsSupportedArgument(const Argument& arg)
     {
+        if constexpr(ConvBackwardWeightSpecialization ==
+                     ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0)
+        {
+            // check if it's 1x1, stride=1 pad = 0 conv
+            for(int i = 0; i < NumDimSpatial; i++)
+            {
+                if(!(arg.filter_spatial_lengths_[i] == 1 && arg.conv_filter_strides_[i] == 1 &&
+                     arg.input_left_pads_[i] == 0 && arg.input_right_pads_[i] == 0))
+                {
+                    return false;
+                }
+            }
+        }
+
         // vector load A/B matrix from global memory
         if(!(ABlockTransferSrcVectorDim == 2 && BBlockTransferSrcVectorDim == 2 &&
              arg.Conv_K_ % ABlockTransferSrcScalarPerVector == 0 &&
@@ -1334,6 +1397,12 @@ struct DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_
             << NPerBlock << ", "
             << K0PerBlock
             << ">";
+        if constexpr(ConvBackwardWeightSpecialization ==
+                     ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0){
+
+            str << " Filter1x1Stride1Pad0";
+        }
+
         // clang-format on
 
         return str.str();

library/src/tensor_operation_instance/gpu/CMakeLists.txt

@@ -24,6 +24,7 @@ add_subdirectory(conv2d_fwd_bias_relu_add)
 add_subdirectory(conv2d_bwd_data)
 add_subdirectory(convnd_bwd_data)
 add_subdirectory(conv2d_bwd_weight)
+add_subdirectory(convnd_bwd_weight)
 add_subdirectory(reduce)
 add_subdirectory(normalization)
 add_subdirectory(elementwise)
@@ -47,6 +48,7 @@ add_library(device_operations STATIC
     $<TARGET_OBJECTS:device_conv2d_bwd_data_instance>
     $<TARGET_OBJECTS:device_convnd_bwd_data_instance>
     $<TARGET_OBJECTS:device_conv2d_bwd_weight_instance>
+    $<TARGET_OBJECTS:device_convnd_bwd_weight_instance>
     $<TARGET_OBJECTS:device_reduce_instance>
     $<TARGET_OBJECTS:device_normalization_instance>
     $<TARGET_OBJECTS:device_elementwise_instance>

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/CMakeLists.txt

+#device_convnd_bwd_weight_instance
+set(DEVICE_CONVND_BWD_WEIGHT_INSTANCE_SOURCE 
+    device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f16_instance.cpp;
+    device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f32_instance.cpp;
+    device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_bf16_instance.cpp;
+    device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_f16_instance.cpp;
+    device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_f32_instance.cpp;
+    device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_bf16_instance.cpp;
+    device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f16_instance.cpp;
+    device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f32_instance.cpp;
+    device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_bf16_instance.cpp;
+)
+
+add_library(device_convnd_bwd_weight_instance OBJECT ${DEVICE_CONVND_BWD_WEIGHT_INSTANCE_SOURCE})
+target_compile_features(device_convnd_bwd_weight_instance PUBLIC) 
+set_target_properties(device_convnd_bwd_weight_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
+rocm_install(TARGETS device_convnd_bwd_weight_instance)
+
+clang_tidy_check(device_convnd_bwd_weight_instance)

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_bf16_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using BF16 = bhalf_t;
+using F32  = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv1d_bwd_weight_xdl_c_shuffle_nwc_kxc_nwk_bf16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+using device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_1x1_s1_p0_bf16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+void add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_bf16_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances, device_conv1d_bwd_weight_xdl_c_shuffle_nwc_kxc_nwk_bf16_instances{});
+    add_device_operation_instances(
+        instances, device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_1x1_s1_p0_bf16_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f16_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F16 = ck::half_t;
+using F32 = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv1d_bwd_weight_xdl_c_shuffle_nwc_kxc_nwk_f16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        8>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>
+    // clang-format on
+    >;
+
+using device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_1x1_s1_p0_f16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        8>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>
+    // clang-format on
+    >;
+
+void add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f16_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances, device_conv1d_bwd_weight_xdl_c_shuffle_nwc_kxc_nwk_f16_instances{});
+    add_device_operation_instances(
+        instances, device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_1x1_s1_p0_f16_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f32_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F32 = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv1d_bwd_weight_xdl_c_shuffle_nwc_kxc_nwk_f32_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   256,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,   256,    4,  4,   32,   32,    2,    4,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,    64,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    64,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,   128,    64,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      256,    64,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,   128,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,      128,    32,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    64,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     1,       64,    32,    64,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+using device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_1x1_s1_p0_f32_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   256,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,   256,    4,  4,   32,   32,    2,    4,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,    64,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    64,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,   128,    64,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      256,    64,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,   128,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,      128,    32,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    64,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     1,       64,    32,    64,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+void add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f32_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances, device_conv1d_bwd_weight_xdl_c_shuffle_nwc_kxc_nwk_f32_instances{});
+    add_device_operation_instances(
+        instances, device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_1x1_s1_p0_f32_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_bf16_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using BF16 = bhalf_t;
+using F32  = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv2d_bwd_weight_xdl_c_shuffle_nhwc_kyxc_nhwk_bf16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+using device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_bf16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+void add_device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_bf16_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances, device_conv2d_bwd_weight_xdl_c_shuffle_nhwc_kyxc_nhwk_bf16_instances{});
+    add_device_operation_instances(
+        instances, device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_bf16_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_f16_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F16 = ck::half_t;
+using F32 = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv2d_bwd_weight_xdl_c_shuffle_nhwc_kyxc_nhwk_f16_default_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        8>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>
+    // clang-format on
+    >;
+
+using device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        8>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>
+    // clang-format on
+    >;
+
+void add_device_convnd_bwd_weight_xdl_nhwc_kyxc_nhwk_f16_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances, device_conv2d_bwd_weight_xdl_c_shuffle_nhwc_kyxc_nhwk_f16_default_instances{});
+    add_device_operation_instances(
+        instances, device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f16_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_f32_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F32 = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv2d_bwd_weight_xdl_c_shuffle_nhwc_kyxc_nhwk_f32_default_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   256,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,   256,    4,  4,   32,   32,    2,    4,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,    64,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    64,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,   128,    64,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      256,    64,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,   128,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,      128,    32,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    64,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     2,       64,    32,    64,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+using device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f32_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   256,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,   256,    4,  4,   32,   32,    2,    4,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,    64,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    64,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,   128,    64,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      256,    64,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,   128,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,      128,    32,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    64,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     2,       64,    32,    64,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+void add_device_convnd_bwd_weight_xdl_nhwc_kyxc_nhwk_f32_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances, device_conv2d_bwd_weight_xdl_c_shuffle_nhwc_kyxc_nhwk_f32_default_instances{});
+    add_device_operation_instances(
+        instances, device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f32_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_bf16_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using BF16 = bhalf_t;
+using F32  = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv3d_bwd_weight_xdl_c_shuffle_ndhwc_kzyxc_ndhwk_bf16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+using device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_1x1_s1_p0_bf16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<   BF16,    BF16,    BF16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+void add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_bf16_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances, device_conv3d_bwd_weight_xdl_c_shuffle_ndhwc_kzyxc_ndhwk_bf16_instances{});
+    add_device_operation_instances(
+        instances, device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_1x1_s1_p0_bf16_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f16_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F16 = ck::half_t;
+using F32 = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv3d_bwd_weight_xdl_c_shuffle_ndhwc_kzyxc_ndhwk_f16_default_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        8>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>
+    // clang-format on
+    >;
+
+using device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_1x1_s1_p0_f16_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   256,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 8>,        8>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,   256,    4,  8,   32,   32,    2,    4,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 8>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,   128,    4,  8,   32,   32,    4,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,    64,   128,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    64,    64,    4,  8,   32,   32,    2,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,    64,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,    64,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 8,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,    32,   128,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  8>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              1,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 32, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    64,    32,    4,  8,   32,   32,    2,    1,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,    true,     S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,      true,        1,            1,     S<1, 16, 1, 4>,        8>,   
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    32,    64,    4,  8,   32,   32,    1,    2,  S<1, 4, 4,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              2,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              8,              4,      true,        1,            1,     S<1, 16, 1, 4>,        8>
+    // clang-format on
+    >;
+
+void add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f16_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_conv3d_bwd_weight_xdl_c_shuffle_ndhwc_kzyxc_ndhwk_f16_default_instances{});
+    add_device_operation_instances(
+        instances, device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_1x1_s1_p0_f16_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/convnd_bwd_weight/device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f32_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <numeric>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_backward_weight_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F32 = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+static constexpr auto ConvBwdWeightDefault =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
+
+static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
+    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
+
+// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
+using device_conv3d_bwd_weight_xdl_c_shuffle_ndhwc_kzyxc_ndhwk_f32_default_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|          ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|        Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                      |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   256,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,   256,    4,  4,   32,   32,    2,    4,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,    64,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    64,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,   128,    64,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      256,    64,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,   128,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,      128,    32,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    64,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightDefault,     3,       64,    32,    64,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+using device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_1x1_s1_p0_f32_instances = std::tuple<
+    // clang-format off
+        //#################################################################################| InData| WeiData| OutData| AccData|          In|         Wei|         Out|                       ConvBackward|    Num|  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|    CBlockTransfer| CBlockTransfer|
+        //#################################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|                             Weight|    Dim|   Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|   ThreadCluster|    ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar| AddExtraM|    ThreadCluster|   ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave|    ClusterLengths|ScalarPerVector|
+        //#################################################################################|       |        |        |        |   Operation|   Operation|   Operation|                     Specialization|Spatial|       |      |      |      |   |     |     | Wave| Wave| Lengths_K0_M_K1|     ArrangeOrder|               |               |      PerVector|   PerVector_K1|          |  Lengths_K0_N_K1|    ArrangeOrder|               |              |      PerVector|   PerVector_K1|          |  PerShuffle|  PerShuffle|  MBlock_MPerBlock|   NWaveNPerXdl|
+        //#################################################################################|       |        |        |        |            |            |            |                                   |       |       |      |      |      |   |     |     |     |     |                |                 |               |               |               |               |          |                 |                |               |              |               |               |          |            |            |  NBlock_NPerBlock|               |
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   256,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,   256,    4,  4,   32,   32,    2,    4,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 64, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 8>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,   128,    4,  4,   32,   32,    4,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,    64,   128,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    64,    64,    4,  4,   32,   32,    2,    2,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,   128,    64,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      256,    64,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 16, 4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,   128,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,      128,    32,   128,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  4>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              1,    true,     S<1, 4, 32, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 32, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    64,    32,    4,  4,   32,   32,    2,    1,  S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,    true,     S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,      true,        1,            1,     S<1, 16, 1, 4>,        4>,
+        DeviceConvndBwdWeightXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<    F32,     F32,     F32,     F32, PassThrough, PassThrough, PassThrough,  ConvBwdWeightFilter1x1Stride1Pad0,     3,       64,    32,    64,    4,  4,   32,   32,    1,    2,  S<1, 4, 8,  2>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              2,    true,     S<1, 4, 16, 1>,   S<0, 3, 1, 2>,   S<0, 2, 1, 3>,             2,              4,              4,      true,        1,            1,     S<1, 16, 1, 4>,        4>
+    // clang-format on
+    >;
+
+void add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f32_instances(
+    std::vector<DeviceConvBwdWeightPtr<PassThrough, PassThrough, PassThrough>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_conv3d_bwd_weight_xdl_c_shuffle_ndhwc_kzyxc_ndhwk_f32_default_instances{});
+    add_device_operation_instances(
+        instances, device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_1x1_s1_p0_f32_instances{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

profiler/CMakeLists.txt

@@ -19,6 +19,7 @@ set(PROFILER_SOURCE
     src/profile_convnd_fwd.cpp
     src/profile_convnd_bwd_data.cpp
     src/profile_conv_bwd_weight.cpp
+    src/profile_convnd_bwd_weight.cpp
     src/profile_reduce.cpp
     src/profile_normalization.cpp
 )
@@ -43,5 +44,6 @@ target_link_libraries(ckProfiler PRIVATE device_conv2d_fwd_bias_relu_instance)
 target_link_libraries(ckProfiler PRIVATE device_conv2d_fwd_bias_relu_add_instance)
 target_link_libraries(ckProfiler PRIVATE device_convnd_bwd_data_instance)
 target_link_libraries(ckProfiler PRIVATE device_conv2d_bwd_weight_instance)
+target_link_libraries(ckProfiler PRIVATE device_convnd_bwd_weight_instance)
 target_link_libraries(ckProfiler PRIVATE device_normalization_instance)
 target_link_libraries(ckProfiler PRIVATE device_reduce_instance)

profiler/include/profile_convnd_bwd_weight_impl.hpp

+#pragma once
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_conv_backward_weight.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+
+#include "ck/library/utility/check_err.hpp"
+#include "ck/library/utility/conv_util.hpp"
+#include "ck/library/host_tensor/device_memory.hpp"
+#include "ck/library/host_tensor/host_tensor.hpp"
+#include "ck/library/host_tensor/host_tensor_generator.hpp"
+#include "ck/library/reference_tensor_operation/cpu/reference_conv_backward_weight.hpp"
+
+using F16  = ck::half_t;
+using F32  = float;
+using BF16 = ck::bhalf_t;
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using DeviceConvndBwdWeightNoOpPtr =
+    DeviceConvBwdWeightPtr<ck::tensor_operation::element_wise::PassThrough,
+                           ck::tensor_operation::element_wise::PassThrough,
+                           ck::tensor_operation::element_wise::PassThrough>;
+
+void add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f32_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+void add_device_convnd_bwd_weight_xdl_nhwc_kyxc_nhwk_f32_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+void add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f32_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+
+void add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f16_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+void add_device_convnd_bwd_weight_xdl_nhwc_kyxc_nhwk_f16_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+void add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f16_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+
+void add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_bf16_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+void add_device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_bf16_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+void add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_bf16_instances(
+    std::vector<DeviceConvndBwdWeightNoOpPtr>&);
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck
+
+namespace ck {
+namespace profiler {
+
+using DeviceConvndBwdWeightNoOpPtr =
+    ck::tensor_operation::device::instance::DeviceConvndBwdWeightNoOpPtr;
+
+template <typename InLayout>
+HostTensorDescriptor get_input_host_tensor_descriptor(const std::vector<std::size_t>& dims,
+                                                      int num_dim_spatial = 2)
+{
+    namespace tl = ck::tensor_layout::convolution;
+
+    switch(num_dim_spatial)
+    {
+    case 3: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, InLayout{});
+    }
+    case 2: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, InLayout{});
+    }
+    case 1: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, InLayout{});
+    }
+    default: {
+        throw std::runtime_error("Unsupported number of spatial dimensions provided!");
+    }
+    }
+}
+
+template <typename WeiLayout>
+HostTensorDescriptor get_filters_host_tensor_descriptor(const std::vector<std::size_t>& dims,
+                                                        int num_dim_spatial = 2)
+{
+    namespace tl = ck::tensor_layout::convolution;
+
+    switch(num_dim_spatial)
+    {
+    case 3: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, WeiLayout{});
+    }
+    case 2: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, WeiLayout{});
+    }
+    case 1: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, WeiLayout{});
+    }
+    default: {
+        throw std::runtime_error("Unsupported number of spatial dimensions provided!");
+    }
+    }
+}
+
+template <typename OutLayout>
+HostTensorDescriptor get_output_host_ensor_descriptor(const std::vector<std::size_t>& dims,
+                                                      int num_dim_spatial = 2)
+{
+    namespace tl = ck::tensor_layout::convolution;
+
+    switch(num_dim_spatial)
+    {
+    case 3: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, OutLayout{});
+    }
+    case 2: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, OutLayout{});
+    }
+    case 1: {
+        return ck::utils::conv::get_host_tensor_descriptor(dims, OutLayout{});
+    }
+    default: {
+        throw std::runtime_error("Unsupported number of spatial dimensions provided!");
+    }
+    }
+}
+
+template <typename InDataType, typename WeiDataType, typename OutDataType>
+void get_device_conv_bwd_weight_op_ptr(
+    InDataType, WeiDataType, OutDataType, std::vector<DeviceConvndBwdWeightNoOpPtr>&, int)
+{
+    std::cout << "can not find device conv bwd weight" << std::endl;
+    exit(1);
+}
+
+template <>
+void get_device_conv_bwd_weight_op_ptr(
+    F32, F32, F32, std::vector<DeviceConvndBwdWeightNoOpPtr>& conv_ptrs, int num_dim_spatial)
+{
+    switch(num_dim_spatial)
+    {
+    case 1:
+        ck::tensor_operation::device::instance::
+            add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f32_instances(conv_ptrs);
+        break;
+    case 2:
+        ck::tensor_operation::device::instance::
+            add_device_convnd_bwd_weight_xdl_nhwc_kyxc_nhwk_f32_instances(conv_ptrs);
+        break;
+    case 3:
+        ck::tensor_operation::device::instance::
+            add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f32_instances(conv_ptrs);
+        break;
+    default: break;
+    }
+}
+
+template <>
+void get_device_conv_bwd_weight_op_ptr(
+    F16, F16, F16, std::vector<DeviceConvndBwdWeightNoOpPtr>& conv_ptrs, int num_dim_spatial)
+{
+    switch(num_dim_spatial)
+    {
+    case 1:
+        ck::tensor_operation::device::instance::
+            add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_f16_instances(conv_ptrs);
+        break;
+    case 2:
+        ck::tensor_operation::device::instance::
+            add_device_convnd_bwd_weight_xdl_nhwc_kyxc_nhwk_f16_instances(conv_ptrs);
+        break;
+    case 3:
+        ck::tensor_operation::device::instance::
+            add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_f16_instances(conv_ptrs);
+        break;
+    default: break;
+    }
+}
+
+template <>
+void get_device_conv_bwd_weight_op_ptr(
+    BF16, BF16, BF16, std::vector<DeviceConvndBwdWeightNoOpPtr>& conv_ptrs, int num_dim_spatial)
+{
+    switch(num_dim_spatial)
+    {
+    case 1:
+        ck::tensor_operation::device::instance::
+            add_device_conv1d_bwd_weight_xdl_nwc_kxc_nwk_bf16_instances(conv_ptrs);
+        break;
+    case 2:
+        ck::tensor_operation::device::instance::
+            add_device_conv2d_bwd_weight_xdl_nhwc_kyxc_nhwk_bf16_instances(conv_ptrs);
+        break;
+    case 3:
+        ck::tensor_operation::device::instance::
+            add_device_conv3d_bwd_weight_xdl_ndhwc_kzyxc_ndhwk_bf16_instances(conv_ptrs);
+        break;
+    default: break;
+    }
+}
+
+template <typename DataType>
+void show_data_nhwc_layout(Tensor<DataType>& nhwc)
+{
+    std::cout << "[";
+    for(int n = 0; n < ck::type_convert<int>(nhwc.mDesc.GetLengths()[0]); n++)
+    {
+        std::cout << "[";
+        for(int hi = 0; hi < ck::type_convert<int>(nhwc.mDesc.GetLengths()[2]); hi++)
+        {
+            std::cout << "[";
+            for(int wi = 0; wi < ck::type_convert<int>(nhwc.mDesc.GetLengths()[3]); wi++)
+            {
+                std::cout << "[";
+                for(int c = 0; c < ck::type_convert<int>(nhwc.mDesc.GetLengths()[1]); c++)
+                {
+                    std::cout << static_cast<float>(nhwc(n, c, hi, wi)) << "  ";
+                }
+                std::cout << "]";
+            }
+            std::cout << "]";
+        }
+        std::cout << "]";
+    }
+    std::cout << "]";
+}
+
+template <int NDimSpatial,
+          typename InDataType,
+          typename WeiDataType,
+          typename OutDataType,
+          typename InLayout,
+          typename WeiLayout,
+          typename OutLayout>
+bool profile_convnd_bwd_weight_impl(int do_verification,
+                                    int init_method,
+                                    bool do_log,
+                                    bool time_kernel,
+                                    ck::index_t N,
+                                    ck::index_t K,
+                                    ck::index_t C,
+                                    std::vector<ck::index_t> input_spatial_lengths,
+                                    std::vector<ck::index_t> filter_spatial_lengths,
+                                    std::vector<ck::index_t> output_spatial_lengths,
+                                    std::vector<ck::index_t> conv_filter_strides,
+                                    std::vector<ck::index_t> conv_filter_dilations,
+                                    std::vector<ck::index_t> input_left_pads,
+                                    std::vector<ck::index_t> input_right_pads,
+                                    ck::index_t split_k)
+{
+    using InElementOp  = ck::tensor_operation::element_wise::PassThrough;
+    using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
+    using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
+
+    const auto in_element_op  = InElementOp{};
+    const auto wei_element_op = WeiElementOp{};
+    const auto out_element_op = OutElementOp{};
+
+    std::vector<std::size_t> input_dims{static_cast<std::size_t>(N), static_cast<std::size_t>(C)};
+    input_dims.insert(
+        std::end(input_dims), std::begin(input_spatial_lengths), std::end(input_spatial_lengths));
+
+    std::vector<std::size_t> filter_dims{static_cast<std::size_t>(K), static_cast<std::size_t>(C)};
+    filter_dims.insert(std::end(filter_dims),
+                       std::begin(filter_spatial_lengths),
+                       std::end(filter_spatial_lengths));
+
+    std::vector<std::size_t> output_dims{static_cast<std::size_t>(N), static_cast<std::size_t>(K)};
+    output_dims.insert(std::end(output_dims),
+                       std::begin(output_spatial_lengths),
+                       std::end(output_spatial_lengths));
+
+    Tensor<InDataType> input(get_input_host_tensor_descriptor<InLayout>(input_dims, NDimSpatial));
+    Tensor<WeiDataType> weights_host_result(
+        get_filters_host_tensor_descriptor<WeiLayout>(filter_dims, NDimSpatial));
+    Tensor<WeiDataType> weights_device_result(
+        get_filters_host_tensor_descriptor<WeiLayout>(filter_dims, NDimSpatial));
+    Tensor<OutDataType> output(
+        get_output_host_ensor_descriptor<OutLayout>(output_dims, NDimSpatial));
+
+    std::cout << "input: " << input.mDesc << std::endl;
+    std::cout << "weights: " << weights_host_result.mDesc << std::endl;
+    std::cout << "output: " << output.mDesc << std::endl;
+
+    switch(init_method)
+    {
+    case 0: break;
+    case 1:
+        input.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-2, 2});
+        output.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-2, 2});
+        break;
+    default:
+        input.GenerateTensorValue(GeneratorTensor_1<OutDataType>{1});
+        output.GenerateTensorValue(GeneratorTensor_1<WeiDataType>{1});
+    }
+
+    DeviceMem in_device_buf(sizeof(InDataType) * input.mDesc.GetElementSpace());
+    DeviceMem wei_device_buf(sizeof(WeiDataType) * weights_device_result.mDesc.GetElementSpace());
+    DeviceMem out_device_buf(sizeof(OutDataType) * output.mDesc.GetElementSpace());
+
+    in_device_buf.ToDevice(input.mData.data());
+    out_device_buf.ToDevice(output.mData.data());
+
+    // reset input to zero
+    wei_device_buf.SetZero();
+
+    if(do_verification)
+    {
+        auto RunReference = [&](auto& ref_conv) {
+            auto ref_invoker = ref_conv.MakeInvoker();
+
+            auto ref_argument = ref_conv.MakeArgument(input,
+                                                      weights_host_result,
+                                                      output,
+                                                      conv_filter_strides,
+                                                      conv_filter_dilations,
+                                                      input_left_pads,
+                                                      input_right_pads,
+                                                      InElementOp{},
+                                                      WeiElementOp{},
+                                                      OutElementOp{});
+            ref_invoker.Run(ref_argument);
+        };
+
+        auto ref_conv = ck::tensor_operation::host::ReferenceConvBwdWeight<InDataType,
+                                                                           WeiDataType,
+                                                                           OutDataType,
+                                                                           InElementOp,
+                                                                           WeiElementOp,
+                                                                           OutElementOp,
+                                                                           NDimSpatial>();
+        RunReference(ref_conv);
+    }
+
+    // add device Conv instances
+    std::vector<DeviceConvndBwdWeightNoOpPtr> conv_ptrs;
+    get_device_conv_bwd_weight_op_ptr(
+        InDataType{}, WeiDataType{}, OutDataType{}, conv_ptrs, NDimSpatial);
+
+    if(conv_ptrs.size() <= 0)
+    {
+        throw std::runtime_error("wrong! no device Conv instance found");
+    }
+
+    std::string best_conv_name;
+    float best_ave_time   = 0;
+    float best_tflops     = 0;
+    float best_gb_per_sec = 0;
+
+    // profile device Conv instances
+    bool success = true;
+    for(auto& conv_ptr : conv_ptrs)
+    {
+        // using atomic, so need to reset input, setzero is done in invoker
+        // if(split_k > 1)
+        //{
+        //    wei_device_buf.SetZero();
+        //}
+
+        auto argument_ptr = conv_ptr->MakeArgumentPointer(
+            static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
+            static_cast<WeiDataType*>(wei_device_buf.GetDeviceBuffer()),
+            static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
+            N,
+            K,
+            C,
+            input_spatial_lengths,
+            filter_spatial_lengths,
+            output_spatial_lengths,
+            conv_filter_strides,
+            conv_filter_dilations,
+            input_left_pads,
+            input_right_pads,
+            in_element_op,
+            wei_element_op,
+            out_element_op,
+            split_k);
+
+        if(!conv_ptr->IsSupportedArgument(argument_ptr.get()))
+        {
+            std::cout << "wrong! device_conv with the specified compilation parameters does "
+                         "not support this Conv problem"
+                      << std::endl;
+            continue;
+        }
+
+        auto invoker_ptr      = conv_ptr->MakeInvokerPointer();
+        std::string conv_name = conv_ptr->GetTypeString();
+        float ave_time        = 0;
+
+        if(std::is_same<InDataType, ck::bhalf_t>::value && split_k > 1)
+        {
+            // alloc work space
+            size_t bwd_weight_workspace_size = conv_ptr->GetWorkSpaceSize(argument_ptr.get());
+            if(bwd_weight_workspace_size <= 0)
+            {
+                printf("wrong work space size\n");
+                exit(1);
+            }
+            DeviceMem wei_work_space_device_buf(bwd_weight_workspace_size);
+            wei_work_space_device_buf.SetZero();
+            conv_ptr->SetWorkSpacePointer(argument_ptr.get(),
+                                          wei_work_space_device_buf.GetDeviceBuffer());
+            ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, time_kernel});
+        }
+        else
+        {
+            ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, time_kernel});
+        }
+
+        std::size_t flop =
+            ck::utils::conv::get_flops(N, C, K, filter_spatial_lengths, output_spatial_lengths);
+        std::size_t num_btype = ck::utils::conv::get_btype<InDataType, WeiDataType, OutDataType>(
+            N, C, K, input_spatial_lengths, filter_spatial_lengths, output_spatial_lengths);
+
+        float tflops     = static_cast<float>(flop) / 1.E9 / ave_time;
+        float gb_per_sec = num_btype / 1.E6 / ave_time;
+
+        std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec
+                  << " GB/s" << std::endl;
+
+        if(tflops > best_tflops)
+        {
+            best_conv_name  = conv_name;
+            best_tflops     = tflops;
+            best_ave_time   = ave_time;
+            best_gb_per_sec = gb_per_sec;
+        }
+
+        if(do_verification)
+        {
+            wei_device_buf.FromDevice(weights_device_result.mData.data());
+
+            float max_error = check_error(weights_host_result, weights_device_result);
+
+            if(max_error > 8)
+            {
+                std::cout << "Fail Info: " << conv_ptr->GetTypeString() << std::endl;
+
+                success = false;
+            }
+            else
+            {
+                std::cout << "Pass Info: " << conv_ptr->GetTypeString() << std::endl;
+            }
+
+            check_error(weights_host_result, weights_device_result);
+
+            if(do_log)
+            {
+                std::cout << "in : ";
+                show_data_nhwc_layout(output);
+                std::cout << std::endl;
+
+                std::cout << "wei: ";
+                show_data_nhwc_layout(weights_host_result);
+                std::cout << std::endl;
+
+                std::cout << "out  : ";
+                show_data_nhwc_layout(input);
+                std::cout << std::endl;
+
+                std::cout << "wei_device: ";
+                show_data_nhwc_layout(weights_device_result);
+                std::cout << std::endl;
+            }
+        }
+    }
+
+    std::cout << "Best Perf: " << best_ave_time << " ms, " << best_tflops << " TFlops, "
+              << best_gb_per_sec << " GB/s, " << best_conv_name << std::endl;
+    return success;
+}
+
+} // namespace profiler
+} // namespace ck

profiler/src/profile_convnd_bwd_weight.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <iostream>
+#include <numeric>
+#include <initializer_list>
+#include <cstdlib>
+
+#include "profiler/include/profile_convnd_bwd_weight_impl.hpp"
+
+namespace {
+
+enum struct ConvDataType
+{
+    F32_F32_F32,    // 0
+    F16_F16_F16,    // 1
+    BF16_BF16_BF16, // 2
+};
+
+enum struct ConvInputLayout
+{
+    NCHW, // 0
+    NHWC, // 1
+};
+
+enum struct ConvWeightLayout
+{
+    KCYX, // 0
+    KYXC, // 1
+};
+
+enum struct ConvOutputLayout
+{
+    NKHW, // 0
+    NHWK, // 1
+};
+ck::utils::conv::ConvParams parse_conv_params(int num_dim_spatial, char* argv[], int arg_idx)
+{
+    // (N, K, C) + num_dim_spatial * 6 (filter, input, strides, dilations, pad left, pad right)
+    ck::utils::conv::ConvParams params;
+
+    params.num_dim_spatial_ = num_dim_spatial;
+    params.N_               = std::stoi(argv[arg_idx++]);
+    params.K_               = std::stoi(argv[arg_idx++]);
+    params.C_               = std::stoi(argv[arg_idx++]);
+
+    params.filter_spatial_lengths_.resize(num_dim_spatial);
+    for(int i = 0; i < num_dim_spatial; ++i)
+    {
+        params.filter_spatial_lengths_[i] = std::stoi(argv[arg_idx++]);
+    }
+    params.input_spatial_lengths_.resize(num_dim_spatial);
+    for(int i = 0; i < num_dim_spatial; ++i)
+    {
+        params.input_spatial_lengths_[i] = std::stoi(argv[arg_idx++]);
+    }
+    params.conv_filter_strides_.resize(num_dim_spatial);
+    for(int i = 0; i < num_dim_spatial; ++i)
+    {
+        params.conv_filter_strides_[i] = std::stoi(argv[arg_idx++]);
+    }
+    params.conv_filter_dilations_.resize(num_dim_spatial);
+    for(int i = 0; i < num_dim_spatial; ++i)
+    {
+        params.conv_filter_dilations_[i] = std::stoi(argv[arg_idx++]);
+    }
+    params.input_left_pads_.resize(num_dim_spatial);
+    for(int i = 0; i < num_dim_spatial; ++i)
+    {
+        params.input_left_pads_[i] = std::stoi(argv[arg_idx++]);
+    }
+    params.input_right_pads_.resize(num_dim_spatial);
+    for(int i = 0; i < num_dim_spatial; ++i)
+    {
+        params.input_right_pads_[i] = std::stoi(argv[arg_idx++]);
+    }
+
+    return params;
+}
+
+} // namespace
+
+int profile_convnd_bwd_weight(int argc, char* argv[], int num_dim_spatial)
+{
+    const int preParams = 11;
+    int conv_args       = 3 + num_dim_spatial * 6;
+    int cmdline_nargs   = conv_args + preParams;
+    if(cmdline_nargs != argc)
+    {
+        printf("arg1: tensor operation (convnd[1|2|3]d_bwd_weight: BackwardConvolution)\n");
+        printf("arg2: data type (0: fp32; 1: fp16, 2: bf16)\n");
+        printf("arg3: input tensor layout (0: NCHW; 1: NHWC)\n");
+        printf("arg4: weight tensor layout (0: KCYX; 1: KYXC)\n");
+        printf("arg5: output tensor layout (0: NKHW; 1: NHWK)\n");
+        printf("arg6: verification (0: no; 1: yes)\n");
+        printf("arg7: initialization (0: no init; 1: integer value; 2: decimal value)\n");
+        printf("arg8: print tensor value (0: no; 1: yes)\n");
+        printf("arg9: time kernel (0=n0, 1=yes)\n");
+        printf("arg10: splitk\n");
+        printf("arg11 to 25: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, "
+               "RightPx\n");
+        return 1;
+    }
+
+    const auto data_type       = static_cast<ConvDataType>(std::stoi(argv[2]));
+    const auto in_layout       = static_cast<ConvInputLayout>(std::stoi(argv[3]));
+    const auto wei_layout      = static_cast<ConvWeightLayout>(std::stoi(argv[4]));
+    const auto out_layout      = static_cast<ConvOutputLayout>(std::stoi(argv[5]));
+    const bool do_verification = std::stoi(argv[6]);
+    const int init_method      = std::stoi(argv[7]);
+    const bool do_log          = std::stoi(argv[8]);
+    const bool time_kernel     = std::stoi(argv[9]);
+
+    ck::index_t split_k = std::stoi(argv[10]);
+    split_k             = std::max(1, split_k);
+
+    ck::utils::conv::ConvParams params = parse_conv_params(num_dim_spatial, argv, preParams);
+
+    auto Run = [&](auto input_type, auto wei_type, auto out_type) {
+        using InDataType  = decltype(input_type);
+        using WeiDataType = decltype(wei_type);
+        using OutDataType = decltype(out_type);
+
+        switch(num_dim_spatial)
+        {
+        case 1:
+            ck::profiler::profile_convnd_bwd_weight_impl<1,
+                                                         InDataType,
+                                                         WeiDataType,
+                                                         OutDataType,
+                                                         ck::tensor_layout::convolution::NWC,
+                                                         ck::tensor_layout::convolution::KXC,
+                                                         ck::tensor_layout::convolution::NWK>(
+                do_verification,
+                init_method,
+                do_log,
+                time_kernel,
+                params.N_,
+                params.K_,
+                params.C_,
+                params.input_spatial_lengths_,
+                params.filter_spatial_lengths_,
+                params.GetOutputSpatialLengths(),
+                params.conv_filter_strides_,
+                params.conv_filter_dilations_,
+                params.input_left_pads_,
+                params.input_right_pads_,
+                split_k);
+            break;
+
+        case 2:
+            ck::profiler::profile_convnd_bwd_weight_impl<2,
+                                                         InDataType,
+                                                         WeiDataType,
+                                                         OutDataType,
+                                                         ck::tensor_layout::convolution::NHWC,
+                                                         ck::tensor_layout::convolution::KYXC,
+                                                         ck::tensor_layout::convolution::NHWK>(
+                do_verification,
+                init_method,
+                do_log,
+                time_kernel,
+                params.N_,
+                params.K_,
+                params.C_,
+                params.input_spatial_lengths_,
+                params.filter_spatial_lengths_,
+                params.GetOutputSpatialLengths(),
+                params.conv_filter_strides_,
+                params.conv_filter_dilations_,
+                params.input_left_pads_,
+                params.input_right_pads_,
+                split_k);
+            break;
+
+        case 3:
+            ck::profiler::profile_convnd_bwd_weight_impl<3,
+                                                         InDataType,
+                                                         WeiDataType,
+                                                         OutDataType,
+                                                         ck::tensor_layout::convolution::NDHWC,
+                                                         ck::tensor_layout::convolution::KZYXC,
+                                                         ck::tensor_layout::convolution::NDHWK>(
+                do_verification,
+                init_method,
+                do_log,
+                time_kernel,
+                params.N_,
+                params.K_,
+                params.C_,
+                params.input_spatial_lengths_,
+                params.filter_spatial_lengths_,
+                params.GetOutputSpatialLengths(),
+                params.conv_filter_strides_,
+                params.conv_filter_dilations_,
+                params.input_left_pads_,
+                params.input_right_pads_,
+                split_k);
+            break;
+
+        default: break;
+        }
+    };
+    if(data_type == ConvDataType::F32_F32_F32 && in_layout == ConvInputLayout::NHWC &&
+       wei_layout == ConvWeightLayout::KYXC && out_layout == ConvOutputLayout::NHWK)
+    {
+        Run(float{}, float{}, float{});
+    }
+    else if(data_type == ConvDataType::F16_F16_F16 && in_layout == ConvInputLayout::NHWC &&
+            wei_layout == ConvWeightLayout::KYXC && out_layout == ConvOutputLayout::NHWK)
+    {
+        Run(ck::half_t{}, ck::half_t{}, ck::half_t{});
+    }
+    else if(data_type == ConvDataType::BF16_BF16_BF16 && in_layout == ConvInputLayout::NHWC &&
+            wei_layout == ConvWeightLayout::KYXC && out_layout == ConvOutputLayout::NHWK)
+    {
+        Run(ck::bhalf_t{}, ck::bhalf_t{}, ck::bhalf_t{});
+    }
+    else
+    {
+        std::cout << "wrong! this Conv data_type & layout is not implemented" << std::endl;
+        return 1;
+    }
+
+    return 0;
+}

profiler/src/profiler.cpp

@@ -20,6 +20,7 @@ int profile_convnd_bwd_data(int, char*[], int);
 int profile_conv_bwd_weight(int, char*[]);
 int profile_normalization(int, char*[]);
 int profile_reduce(int, char*[]);
+int profile_convnd_bwd_weight(int, char*[], int);
 
 static void print_helper_message()
 {
@@ -117,6 +118,18 @@ int main(int argc, char* argv[])
     {
         return profile_conv_bwd_weight(argc, argv);
     }
+    else if(strcmp(argv[1], "convnd1d_bwd_weight") == 0)
+    {
+        return profile_convnd_bwd_weight(argc, argv, 1);
+    }
+    else if(strcmp(argv[1], "convnd2d_bwd_weight") == 0)
+    {
+        return profile_convnd_bwd_weight(argc, argv, 2);
+    }
+    else if(strcmp(argv[1], "convnd3d_bwd_weight") == 0)
+    {
+        return profile_convnd_bwd_weight(argc, argv, 3);
+    }
     else if(strcmp(argv[1], "reduce") == 0)
     {
         return profile_reduce(argc, argv);

test/CMakeLists.txt

@@ -44,6 +44,7 @@ add_subdirectory(grouped_gemm)
 add_subdirectory(convnd_fwd)
 add_subdirectory(reduce)
 add_subdirectory(conv2d_bwd_weight)
+add_subdirectory(convnd_bwd_weight)
 add_subdirectory(convnd_bwd_data)
 add_subdirectory(block_to_ctile_map)
 add_subdirectory(softmax)

test/convnd_bwd_weight/CMakeLists.txt

+add_test_executable(test_convnd_bwd_weight convnd_bwd_weight.cpp) 
+target_link_libraries(test_convnd_bwd_weight PRIVATE host_tensor device_convnd_bwd_weight_instance conv_util)

test/convnd_bwd_weight/convnd_bwd_weight.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <iostream>
+#include <numeric>
+#include <initializer_list>
+#include <cstdlib>
+#include <vector>
+
+#include "test/convnd_fwd/conv_util.hpp"
+#include "profiler/include/profile_convnd_bwd_weight_impl.hpp"
+
+int test_self()
+{
+    bool pass = true;
+    std::vector<ck::utils::conv::ConvParams> params;
+
+    params.push_back({1, 128, 256, 256, {1}, {7}, {2}, {1}, {0}, {0}});
+    params.push_back({1, 128, 256, 256, {3}, {14}, {1}, {1}, {1}, {1}});
+    params.push_back({1, 128, 256, 256, {1}, {3}, {1}, {1}, {0}, {0}});
+
+    for(auto& param : params)
+    {
+        // f32
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<1,
+                                                             float,
+                                                             float,
+                                                             float,
+                                                             ck::tensor_layout::convolution::NWC,
+                                                             ck::tensor_layout::convolution::KXC,
+                                                             ck::tensor_layout::convolution::NWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+
+        // fp16
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<1,
+                                                             ck::half_t,
+                                                             ck::half_t,
+                                                             ck::half_t,
+                                                             ck::tensor_layout::convolution::NWC,
+                                                             ck::tensor_layout::convolution::KXC,
+                                                             ck::tensor_layout::convolution::NWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+
+        // bf16
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<1,
+                                                             ck::bhalf_t,
+                                                             ck::bhalf_t,
+                                                             ck::bhalf_t,
+                                                             ck::tensor_layout::convolution::NWC,
+                                                             ck::tensor_layout::convolution::KXC,
+                                                             ck::tensor_layout::convolution::NWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+    }
+
+    // check 2d
+    params.clear();
+    params.push_back({2, 128, 256, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
+    params.push_back({2, 128, 256, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
+    params.push_back({2, 128, 256, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
+
+    for(auto& param : params)
+    {
+        // f32
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<2,
+                                                             float,
+                                                             float,
+                                                             float,
+                                                             ck::tensor_layout::convolution::NHWC,
+                                                             ck::tensor_layout::convolution::KYXC,
+                                                             ck::tensor_layout::convolution::NHWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+
+        // fp16
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<2,
+                                                             ck::half_t,
+                                                             ck::half_t,
+                                                             ck::half_t,
+                                                             ck::tensor_layout::convolution::NHWC,
+                                                             ck::tensor_layout::convolution::KYXC,
+                                                             ck::tensor_layout::convolution::NHWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+
+        // bf16
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<2,
+                                                             ck::bhalf_t,
+                                                             ck::bhalf_t,
+                                                             ck::bhalf_t,
+                                                             ck::tensor_layout::convolution::NHWC,
+                                                             ck::tensor_layout::convolution::KYXC,
+                                                             ck::tensor_layout::convolution::NHWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+    }
+
+    // check 2d
+    params.clear();
+    params.push_back(
+        {3, 128, 256, 256, {1, 1, 1}, {4, 4, 4}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
+    params.push_back(
+        {3, 128, 256, 256, {3, 3, 3}, {4, 4, 8}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
+    params.push_back(
+        {3, 128, 256, 256, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
+
+    for(auto& param : params)
+    {
+        // f32
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<3,
+                                                             float,
+                                                             float,
+                                                             float,
+                                                             ck::tensor_layout::convolution::NDHWC,
+                                                             ck::tensor_layout::convolution::KZYXC,
+                                                             ck::tensor_layout::convolution::NDHWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+
+        // fp16
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<3,
+                                                             ck::half_t,
+                                                             ck::half_t,
+                                                             ck::half_t,
+                                                             ck::tensor_layout::convolution::NDHWC,
+                                                             ck::tensor_layout::convolution::KZYXC,
+                                                             ck::tensor_layout::convolution::NDHWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+
+        // bf16
+        pass &= ck::profiler::profile_convnd_bwd_weight_impl<3,
+                                                             ck::bhalf_t,
+                                                             ck::bhalf_t,
+                                                             ck::bhalf_t,
+                                                             ck::tensor_layout::convolution::NDHWC,
+                                                             ck::tensor_layout::convolution::KZYXC,
+                                                             ck::tensor_layout::convolution::NDHWK>(
+            true,  // do_verification
+            1,     // init_method
+            false, // do_log
+            true,  // time_kernel
+            param.N_,
+            param.K_,
+            param.C_,
+            param.input_spatial_lengths_,
+            param.filter_spatial_lengths_,
+            param.GetOutputSpatialLengths(),
+            param.conv_filter_strides_,
+            param.conv_filter_dilations_,
+            param.input_left_pads_,
+            param.input_right_pads_,
+            2);
+    }
+
+    return pass;
+}
+int main()
+{
+    // int data_type   = 1;
+    // int init_method = 1;
+
+    bool pass = true;
+
+    pass = test_self();
+
+    if(pass)
+    {
+        std::cout << "test conv2d bwd weight : Pass" << std::endl;
+        return 0;
+    }
+    else
+    {
+        std::cout << "test conv2d bwd weight: Fail " << std::endl;
+        return -1;
+    }
+}