// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.

#pragma once

#include <iostream>
#include <sstream>

#include "ck/utility/common_header.hpp"
#include "ck/tensor_description/tensor_descriptor.hpp"
#include "ck/tensor_description/tensor_descriptor_helper.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_gemm_multiple_d_multiple_r.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/matrix_padder.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_d_multiple_r_xdl_cshuffle.hpp"
#include "ck/host_utility/device_prop.hpp"
#include "ck/host_utility/kernel_launch.hpp"

namespace ck {

template <typename GridwiseGemm,
          typename FloatAB,
          typename FloatDsPointer,
          typename FloatE,
          typename FloatRsPointer,
          typename AElementwiseOperation,
          typename BElementwiseOperation,
          typename CDEElementwiseOperation,
          typename QsElementwiseOperation,
          typename RsElementwiseOperation,
          typename AGridDesc_AK0_M_AK1,
          typename BGridDesc_BK0_N_BK1,
          typename DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
          typename EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
          typename RsGridDescriptor_MBlock_MPerBlock,
          typename Block2ETileMap,
          bool HasMainKBlockLoop>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
    __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
#endif
        kernel_gemm_multiple_d_multiple_r_xdl_cshuffle(
            const FloatAB* __restrict__ p_a_grid,
            const FloatAB* __restrict__ p_b_grid,
            FloatDsPointer p_ds_grid,
            FloatE* __restrict__ p_e_grid,
            FloatRsPointer p_rs_grid,
            const AElementwiseOperation a_element_op,
            const BElementwiseOperation b_element_op,
            const CDEElementwiseOperation cde_element_op,
            const QsElementwiseOperation qs_element_op,
            const RsElementwiseOperation rs_element_op,
            const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
            const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
            const DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
                ds_grid_desc_mblock_mperblock_nblock_nperblock,
            const EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
                e_grid_desc_mblock_mperblock_nblock_nperblock,
            const RsGridDescriptor_MBlock_MPerBlock rs_grid_desc_mblock_mperblock,
            const Block2ETileMap block_2_etile_map)
{
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
    defined(__gfx940__) || defined(__gfx941__) || defined(__gfx942__))
    __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];

    GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid,
                                                  p_b_grid,
                                                  p_ds_grid,
                                                  p_e_grid,
                                                  p_rs_grid,
                                                  p_shared,
                                                  a_element_op,
                                                  b_element_op,
                                                  cde_element_op,
                                                  qs_element_op,
                                                  rs_element_op,
                                                  a_grid_desc_ak0_m_ak1,
                                                  b_grid_desc_bk0_n_bk1,
                                                  ds_grid_desc_mblock_mperblock_nblock_nperblock,
                                                  e_grid_desc_mblock_mperblock_nblock_nperblock,
                                                  rs_grid_desc_mblock_mperblock,
                                                  block_2_etile_map);
#else
    ignore = p_a_grid;
    ignore = p_b_grid;
    ignore = p_ds_grid;
    ignore = p_e_grid;
    ignore = p_rs_grid;
    ignore = a_element_op;
    ignore = b_element_op;
    ignore = cde_element_op;
    ignore = qs_element_op;
    ignore = rs_element_op;
    ignore = a_grid_desc_ak0_m_ak1;
    ignore = b_grid_desc_bk0_n_bk1;
    ignore = ds_grid_desc_mblock_mperblock_nblock_nperblock;
    ignore = e_grid_desc_mblock_mperblock_nblock_nperblock;
    ignore = rs_grid_desc_mblock_mperblock;
    ignore = block_2_etile_map;
#endif
}

} // namespace ck

namespace ck {
namespace tensor_operation {
namespace device {

// GEMM:
//   input : A[AK0, M, AK1]
//   input : B[AK0, N, AK1]
//   input : D0[M, N], D1[M, N], ...
//   output : E[M, N]
//   output : R0[M], R1[M], ...
//   C = a_op(A) * b_op(B)
//   E = cde_op(C, D0, D1, ...)
//   Q0 = reduce0(q_op0(E)), Q1 = reduce1(q_op0(E)), ...
//   R0 = r_op0(Q0), R1 = r_op1(Q1), ...
// Assume:
//   D0, D1, ... and E have the same layout
template <typename ALayout,
          typename BLayout,
          typename DELayout,
          typename ADataType,
          typename BDataType,
          typename GemmAccDataType,
          typename CShuffleDataType,
          typename DsDataType,
          typename EDataType,
          typename ReduceAccDataType,
          typename RsDataType,
          typename AElementwiseOperation,
          typename BElementwiseOperation,
          typename CDEElementwiseOperation,
          typename QsElementwiseOperation,
          typename RsElementwiseOperation,
          typename ThreadReduceOperations,
          typename RsGlobalMemoryDataOperation,
          GemmSpecialization GemmSpec,
          index_t NumGemmKPrefetchStage,
          index_t BlockSize,
          index_t MPerBlock,
          index_t NPerBlock,
          index_t KPerBlock,
          index_t AK1,
          index_t BK1,
          index_t MPerXDL,
          index_t NPerXDL,
          index_t MXdlPerWave,
          index_t NXdlPerWave,
          typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
          typename ABlockTransferThreadClusterArrangeOrder,
          typename ABlockTransferSrcAccessOrder,
          index_t ABlockTransferSrcVectorDim,
          index_t ABlockTransferSrcScalarPerVector,
          index_t ABlockTransferDstScalarPerVector_AK1,
          bool ABlockLdsExtraM,
          typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
          typename BBlockTransferThreadClusterArrangeOrder,
          typename BBlockTransferSrcAccessOrder,
          index_t BBlockTransferSrcVectorDim,
          index_t BBlockTransferSrcScalarPerVector,
          index_t BBlockTransferDstScalarPerVector_BK1,
          bool BBlockLdsExtraN,
          index_t CShuffleMXdlPerWavePerShuffle,
          index_t CShuffleNXdlPerWavePerShuffle,
          typename CDRThreadTransferClusterLengths_MPerBlock_NPerBlock,
          index_t CDEReduceThreadTransferScalarPerVector_NPerBlock,
          index_t RThreadTransferDstScalarPerVector_MPerBlock,
          LoopScheduler LoopSched = make_default_loop_scheduler()>
struct DeviceGemmMultipleDMultipleR_Xdl_CShuffle
    : public DeviceGemmMultipleDMultipleR<ALayout,
                                          BLayout,
                                          DELayout,
                                          ADataType,
                                          BDataType,
                                          DsDataType,
                                          EDataType,
                                          RsDataType,
                                          AElementwiseOperation,
                                          BElementwiseOperation,
                                          CDEElementwiseOperation,
                                          QsElementwiseOperation,
                                          RsElementwiseOperation>
{
    using DeviceOp = DeviceGemmMultipleDMultipleR_Xdl_CShuffle;

    static constexpr index_t NumDTensor = DsDataType::Size();
    static constexpr index_t NumRTensor = RsDataType::Size();

    static constexpr auto I0 = Number<0>{};
    static constexpr auto I1 = Number<1>{};
    static constexpr auto I2 = Number<2>{};
    static constexpr auto I3 = Number<3>{};

    static constexpr auto matrix_padder =
        MatrixPadder<GemmSpec, index_t, index_t, index_t>{MPerBlock, NPerBlock, KPerBlock};

    static auto MakeAGridDescriptor_M_K(index_t MRaw, index_t KRaw, index_t StrideA)
    {
        const auto a_grid_desc_mraw_kraw = [&]() {
            if constexpr(is_same_v<tensor_layout::gemm::RowMajor, ALayout>)
            {
                return make_naive_tensor_descriptor(make_tuple(MRaw, KRaw),
                                                    make_tuple(StrideA, I1));
            }
            else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, ALayout>)
            {
                return make_naive_tensor_descriptor(make_tuple(MRaw, KRaw),
                                                    make_tuple(I1, StrideA));
            }
        }();

        return matrix_padder.PadADescriptor_M_K(a_grid_desc_mraw_kraw);
    }

    static auto MakeBGridDescriptor_N_K(index_t KRaw, index_t NRaw, index_t StrideB)
    {
        const auto b_grid_desc_nraw_kraw = [&]() {
            if constexpr(is_same<tensor_layout::gemm::RowMajor, BLayout>::value)
            {
                return make_naive_tensor_descriptor(make_tuple(NRaw, KRaw),
                                                    make_tuple(I1, StrideB));
            }
            else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, BLayout>::value)
            {
                return make_naive_tensor_descriptor(make_tuple(NRaw, KRaw),
                                                    make_tuple(StrideB, I1));
            }
        }();

        return matrix_padder.PadBDescriptor_N_K(b_grid_desc_nraw_kraw);
    }

    static auto MakeEGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t StrideE)
    {
        const auto e_grid_desc_mraw_nraw = [&]() {
            if constexpr(is_same<tensor_layout::gemm::RowMajor, DELayout>::value)
            {
                return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
                                                    make_tuple(StrideE, I1));
            }
            else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, DELayout>::value)
            {
                return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
                                                    make_tuple(I1, StrideE));
            }
        }();

        return matrix_padder.PadCDescriptor_M_N(e_grid_desc_mraw_nraw);
    }

    // assume D is packed tensor
    static auto MakeRGridDescriptor_M(index_t MRaw)
    {
        const auto r_grid_desc_mraw = make_naive_tensor_descriptor_packed(make_tuple(MRaw));

        const auto M    = math::integer_divide_ceil(MRaw, MPerBlock) * MPerBlock;
        const auto MPad = M - MRaw;

        if constexpr(GemmSpec == GemmSpecialization::MPadding ||
                     GemmSpec == GemmSpecialization::MNPadding ||
                     GemmSpec == GemmSpecialization::MKPadding ||
                     GemmSpec == GemmSpecialization::MNKPadding)
        {
            // pad M
            return transform_tensor_descriptor(r_grid_desc_mraw,
                                               make_tuple(make_right_pad_transform(MRaw, MPad)),
                                               make_tuple(Sequence<0>{}),
                                               make_tuple(Sequence<0>{}));
        }
        else
        {
            // not pad M
            return r_grid_desc_mraw;
        }
    }

    using AGridDesc_M_K = decltype(MakeAGridDescriptor_M_K(1, 1, 1));
    using BGridDesc_N_K = decltype(MakeBGridDescriptor_N_K(1, 1, 1));
    using EGridDesc_M_N = decltype(MakeEGridDescriptor_M_N(1, 1, 1));
    using RGridDesc_M   = decltype(MakeRGridDescriptor_M(1));

    // GridwiseGemm
    using GridwiseGemm = GridwiseGemmMultipleDMultipleR_k0mk1_k0nk1_mn_xdl_cshuffle_v1<
        ADataType, // TODO: distinguish A/B datatype
        GemmAccDataType,
        CShuffleDataType,
        DsDataType,
        EDataType,
        ReduceAccDataType,
        RsDataType,
        AElementwiseOperation,
        BElementwiseOperation,
        CDEElementwiseOperation,
        QsElementwiseOperation,
        RsElementwiseOperation,
        ThreadReduceOperations,
        InMemoryDataOperationEnum::Set,
        RsGlobalMemoryDataOperation,
        AGridDesc_M_K,
        BGridDesc_N_K,
        EGridDesc_M_N,
        RGridDesc_M,
        NumGemmKPrefetchStage,
        BlockSize,
        MPerBlock,
        NPerBlock,
        KPerBlock,
        AK1,
        BK1,
        MPerXDL,
        NPerXDL,
        MXdlPerWave,
        NXdlPerWave,
        ABlockTransferThreadClusterLengths_AK0_M_AK1,
        ABlockTransferThreadClusterArrangeOrder,
        ABlockTransferSrcAccessOrder,
        ABlockTransferSrcVectorDim,
        ABlockTransferSrcScalarPerVector,
        ABlockTransferDstScalarPerVector_AK1,
        false,
        ABlockLdsExtraM,
        BBlockTransferThreadClusterLengths_BK0_N_BK1,
        BBlockTransferThreadClusterArrangeOrder,
        BBlockTransferSrcAccessOrder,
        BBlockTransferSrcVectorDim,
        BBlockTransferSrcScalarPerVector,
        BBlockTransferDstScalarPerVector_BK1,
        false,
        BBlockLdsExtraN,
        CShuffleMXdlPerWavePerShuffle,
        CShuffleNXdlPerWavePerShuffle,
        CDRThreadTransferClusterLengths_MPerBlock_NPerBlock,
        CDEReduceThreadTransferScalarPerVector_NPerBlock,
        RThreadTransferDstScalarPerVector_MPerBlock,
        LoopSched>;

    using AGridDesc_AK0_M_AK1 =
        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultAGridDescriptor_AK0_M_AK1(
            AGridDesc_M_K{}))>;
    using BGridDesc_BK0_N_BK1 =
        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultBGridDescriptor_BK0_N_BK1(
            BGridDesc_N_K{}))>;

    using Block2ETileMap = typename GridwiseGemm::DefaultBlock2ETileMap;

    // Argument
    struct Argument : public BaseArgument
    {
        Argument(const void* p_a_grid,
                 const void* p_b_grid,
                 std::array<const void*, NumDTensor> p_ds_grid,
                 void* p_e_grid,
                 std::array<void*, NumRTensor> p_rs_grid,
                 index_t MRaw,
                 index_t NRaw,
                 index_t KRaw,
                 index_t StrideA,
                 index_t StrideB,
                 std::array<index_t, NumDTensor> StrideDs,
                 index_t StrideE,
                 AElementwiseOperation a_element_op,
                 BElementwiseOperation b_element_op,
                 CDEElementwiseOperation cde_element_op,
                 QsElementwiseOperation qs_element_op,
                 RsElementwiseOperation rs_element_op)
            : p_a_grid_{static_cast<const ADataType*>(p_a_grid)},
              p_b_grid_{static_cast<const BDataType*>(p_b_grid)},
              p_ds_grid_{}, // FIXME
              p_e_grid_{static_cast<EDataType*>(p_e_grid)},
              p_rs_grid_{}, // FIXME
              a_grid_desc_m_k_{DeviceOp::MakeAGridDescriptor_M_K(MRaw, KRaw, StrideA)},
              b_grid_desc_n_k_{DeviceOp::MakeBGridDescriptor_N_K(KRaw, NRaw, StrideB)},
              e_grid_desc_m_n_{DeviceOp::MakeEGridDescriptor_M_N(MRaw, NRaw, StrideE)},
              r_grid_desc_m_{DeviceOp::MakeRGridDescriptor_M(MRaw)},
              a_grid_desc_ak0_m_ak1_{
                  GridwiseGemm::MakeDefaultAGridDescriptor_AK0_M_AK1(a_grid_desc_m_k_)},
              b_grid_desc_bk0_n_bk1_{
                  GridwiseGemm::MakeDefaultBGridDescriptor_BK0_N_BK1(b_grid_desc_n_k_)},
              ds_grid_desc_mblock_mperblock_nblock_nperblock_{},
              e_grid_desc_mblock_mperblock_nblock_nperblock_{},
              rs_grid_desc_mblock_mperblock_{},
              block_2_etile_map_{GridwiseGemm::MakeDefaultBlock2ETileMap(e_grid_desc_m_n_)},
              a_element_op_{a_element_op},
              b_element_op_{b_element_op},
              cde_element_op_{cde_element_op},
              qs_element_op_{qs_element_op},
              rs_element_op_{rs_element_op}
        {
            if(GridwiseGemm::CheckValidity(a_grid_desc_m_k_,
                                           b_grid_desc_n_k_,
                                           e_grid_desc_m_n_,
                                           r_grid_desc_m_,
                                           block_2_etile_map_))
            {
                e_grid_desc_mblock_mperblock_nblock_nperblock_ =
                    GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
                        e_grid_desc_m_n_);

                static_for<0, NumDTensor, 1>{}([&](auto i) {
                    using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;

                    p_ds_grid_(i) = static_cast<const DDataType*>(p_ds_grid[i]);

                    const auto d_grid_desc_m_n =
                        DeviceOp::MakeEGridDescriptor_M_N(MRaw, NRaw, StrideDs[i]);

                    ds_grid_desc_mblock_mperblock_nblock_nperblock_(i) =
                        GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
                            d_grid_desc_m_n);
                });

                static_for<0, NumRTensor, 1>{}([&](auto i) {
                    using RDataType = remove_cvref_t<tuple_element_t<i.value, RsDataType>>;

                    p_rs_grid_(i) = static_cast<RDataType*>(p_rs_grid[i]);

                    rs_grid_desc_mblock_mperblock_(i) =
                        GridwiseGemm::MakeRGridDescriptor_MBlock_MPerBlock(r_grid_desc_m_);
                });
            }
        }

        //  private:
        // pointers
        const ADataType* p_a_grid_;
        const BDataType* p_b_grid_;
        typename GridwiseGemm::DsGridPointer p_ds_grid_;
        EDataType* p_e_grid_;
        typename GridwiseGemm::RsGridPointer p_rs_grid_;

        // tensor descriptors
        AGridDesc_M_K a_grid_desc_m_k_;
        BGridDesc_N_K b_grid_desc_n_k_;
        EGridDesc_M_N e_grid_desc_m_n_;
        RGridDesc_M r_grid_desc_m_;

        // tensor descriptors for block/thread-wise copy
        AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1_;
        BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1_;
        StaticallyIndexedArray<
            typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
            NumDTensor>
            ds_grid_desc_mblock_mperblock_nblock_nperblock_; // FIXME: Ds desc may be of different
                                                             // type from E
        typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
            e_grid_desc_mblock_mperblock_nblock_nperblock_;

        StaticallyIndexedArray<typename GridwiseGemm::RGridDescriptor_MBlock_MPerBlock, NumRTensor>
            rs_grid_desc_mblock_mperblock_;

        // block-to-e-tile map
        Block2ETileMap block_2_etile_map_;

        // element-wise op
        AElementwiseOperation a_element_op_;
        BElementwiseOperation b_element_op_;
        CDEElementwiseOperation cde_element_op_;
        QsElementwiseOperation qs_element_op_;
        RsElementwiseOperation rs_element_op_;
    };

    // Invoker
    struct Invoker : public BaseInvoker
    {
        using Argument = DeviceOp::Argument;

        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
        {
            if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_m_k_,
                                            arg.b_grid_desc_n_k_,
                                            arg.e_grid_desc_m_n_,
                                            arg.r_grid_desc_m_,
                                            arg.block_2_etile_map_))
            {
                throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
            }

            const index_t grid_size =
                arg.block_2_etile_map_.CalculateGridSize(arg.e_grid_desc_m_n_);

            const auto K =
                arg.a_grid_desc_ak0_m_ak1_.GetLength(I0) * arg.a_grid_desc_ak0_m_ak1_.GetLength(I2);

            auto launch_kernel = [&](auto has_main_k_block_loop) {
                constexpr bool has_main_loop = has_main_k_block_loop.value;

                const auto kernel = kernel_gemm_multiple_d_multiple_r_xdl_cshuffle<
                    GridwiseGemm,
                    ADataType, // TODO: distiguish A/B datatype
                    typename GridwiseGemm::DsGridPointer,
                    EDataType,
                    typename GridwiseGemm::RsGridPointer,
                    AElementwiseOperation,
                    BElementwiseOperation,
                    CDEElementwiseOperation,
                    QsElementwiseOperation,
                    RsElementwiseOperation,
                    DeviceOp::AGridDesc_AK0_M_AK1,
                    DeviceOp::BGridDesc_BK0_N_BK1,
                    ck::StaticallyIndexedArray<
                        typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
                        NumDTensor>,
                    typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
                    ck::StaticallyIndexedArray<
                        typename GridwiseGemm::RGridDescriptor_MBlock_MPerBlock,
                        NumRTensor>,
                    typename GridwiseGemm::DefaultBlock2ETileMap,
                    has_main_loop>;

                return launch_and_time_kernel(stream_config,
                                              kernel,
                                              dim3(grid_size),
                                              dim3(BlockSize),
                                              0,
                                              arg.p_a_grid_,
                                              arg.p_b_grid_,
                                              arg.p_ds_grid_,
                                              arg.p_e_grid_,
                                              arg.p_rs_grid_,
                                              arg.a_element_op_,
                                              arg.b_element_op_,
                                              arg.cde_element_op_,
                                              arg.qs_element_op_,
                                              arg.rs_element_op_,
                                              arg.a_grid_desc_ak0_m_ak1_,
                                              arg.b_grid_desc_bk0_n_bk1_,
                                              arg.ds_grid_desc_mblock_mperblock_nblock_nperblock_,
                                              arg.e_grid_desc_mblock_mperblock_nblock_nperblock_,
                                              arg.rs_grid_desc_mblock_mperblock_,
                                              arg.block_2_etile_map_);
            };

            float ave_time = 0;

            if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
            {
                ave_time = launch_kernel(integral_constant<bool, true>{});
            }
            else
            {
                ave_time = launch_kernel(integral_constant<bool, false>{});
            }

            return ave_time;
        }

        // polymorphic
        float Run(const BaseArgument* p_arg,
                  const StreamConfig& stream_config = StreamConfig{}) override
        {
            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
        }
    };

    static bool IsSupportedArgument(const Argument& arg)
    {
        if(!ck::is_xdl_supported())
        {
            return false;
        }

        return GridwiseGemm::CheckValidity(arg.a_grid_desc_m_k_,
                                           arg.b_grid_desc_n_k_,
                                           arg.e_grid_desc_m_n_,
                                           arg.r_grid_desc_m_,
                                           arg.block_2_etile_map_);
    }

    // polymorphic
    bool IsSupportedArgument(const BaseArgument* p_arg) override
    {
        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
    }

    static auto MakeArgument(const void* p_a,
                             const void* p_b,
                             std::array<const void*, NumDTensor> p_ds,
                             void* p_e,
                             std::array<void*, NumRTensor> p_rs,
                             index_t MRaw,
                             index_t NRaw,
                             index_t KRaw,
                             index_t StrideA,
                             index_t StrideB,
                             std::array<index_t, NumDTensor> StrideDs,
                             index_t StrideE,
                             AElementwiseOperation a_element_op,
                             BElementwiseOperation b_element_op,
                             CDEElementwiseOperation cde_element_op,
                             QsElementwiseOperation qs_element_op,
                             RsElementwiseOperation rs_element_op)
    {
        return Argument{p_a,
                        p_b,
                        p_ds,
                        p_e,
                        p_rs,
                        MRaw,
                        NRaw,
                        KRaw,
                        StrideA,
                        StrideB,
                        StrideDs,
                        StrideE,
                        a_element_op,
                        b_element_op,
                        cde_element_op,
                        qs_element_op,
                        rs_element_op};
    }

    static auto MakeInvoker() { return Invoker{}; }

    // polymorphic
    std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
                                                      const void* p_b,
                                                      std::array<const void*, NumDTensor> p_ds,
                                                      void* p_e,
                                                      std::array<void*, NumRTensor> p_rs,
                                                      index_t MRaw,
                                                      index_t NRaw,
                                                      index_t KRaw,
                                                      index_t StrideA,
                                                      index_t StrideB,
                                                      std::array<index_t, NumDTensor> StrideDs,
                                                      index_t StrideE,
                                                      AElementwiseOperation a_element_op,
                                                      BElementwiseOperation b_element_op,
                                                      CDEElementwiseOperation cde_element_op,
                                                      QsElementwiseOperation qs_element_op,
                                                      RsElementwiseOperation rs_element_op) override
    {
        return std::make_unique<Argument>(p_a,
                                          p_b,
                                          p_ds,
                                          p_e,
                                          p_rs,
                                          MRaw,
                                          NRaw,
                                          KRaw,
                                          StrideA,
                                          StrideB,
                                          StrideDs,
                                          StrideE,
                                          a_element_op,
                                          b_element_op,
                                          cde_element_op,
                                          qs_element_op,
                                          rs_element_op);
    }

    // polymorphic
    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
    {
        return std::make_unique<Invoker>(Invoker{});
    }

    // polymorphic
    std::string GetTypeString() const override
    {
        auto str = std::stringstream();

        // clang-format off
        str << "DeviceGemmMultipleDMultipleR_Xdl_CShuffle"
            << "<"
            << BlockSize << ", "
            << MPerBlock << ", "
            << NPerBlock << ", "
            << KPerBlock << ", "
            << AK1 << ", "
            << BK1 << ", "
            << getGemmSpecializationString(GemmSpec) << ", "
            << MPerXDL << ", "
            << NPerXDL << ", "
            << MXdlPerWave << ", "
            << NXdlPerWave << ", "
            << ABlockTransferSrcScalarPerVector << ", "
            << BBlockTransferSrcScalarPerVector << ", "
            << CShuffleMXdlPerWavePerShuffle << ", "
            << CShuffleNXdlPerWavePerShuffle
            << ">";
        // clang-format on

        return str.str();
    }
};

} // namespace device
} // namespace tensor_operation
} // namespace ck
