// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, 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.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v1.hpp"
#include "ck/host_utility/device_prop.hpp"
#include "ck/host_utility/kernel_launch.hpp"

namespace ck {
namespace tensor_operation {
namespace device {

// Note: inter-wave loop scheduler is rolled out to c-shuffle version first. Becuase non c-shuffle
// version currently has compiler issues with register spill which further causes validation
// failures.
template <typename ALayout,
          typename BLayout,
          typename CLayout,
          typename ADataType,
          typename BDataType,
          typename CDataType,
          typename GemmAccDataType,
          typename CShuffleDataType,
          typename AElementwiseOperation,
          typename BElementwiseOperation,
          typename CElementwiseOperation,
          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 CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
          index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
          LoopScheduler LoopSched     = make_default_loop_scheduler(),
          PipelineVersion PipelineVer = PipelineVersion::v1>
struct DeviceGemm_Xdl_CShuffle : public DeviceGemm<ALayout,
                                                   BLayout,
                                                   CLayout,
                                                   ADataType,
                                                   BDataType,
                                                   CDataType,
                                                   AElementwiseOperation,
                                                   BElementwiseOperation,
                                                   CElementwiseOperation>
{
    using DeviceOp = DeviceGemm_Xdl_CShuffle;

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

    static auto MakeAGridDescriptor_AK0_M_AK1(
        index_t M, index_t MPad, index_t K, index_t KPad, index_t StrideA, index_t AK0)
    {
        const auto a_grid_desc_mraw_kraw = [&]() {
            if constexpr(is_same_v<tensor_layout::gemm::RowMajor, ALayout>)
            {
                return make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(StrideA, I1));
            }
            else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, ALayout>)
            {
                return make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(I1, StrideA));
            }
        }();

        if constexpr(GemmSpec == GemmSpecialization::MKPadding ||
                     GemmSpec == GemmSpecialization::MNKPadding)
        {
            // pad both M and K
            const auto a_grid_desc_m_k =
                transform_tensor_descriptor(a_grid_desc_mraw_kraw,
                                            make_tuple(make_right_pad_transform(M, MPad - M),
                                                       make_right_pad_transform(K, KPad - K)),
                                            make_tuple(Sequence<0>{}, Sequence<1>{}),
                                            make_tuple(Sequence<0>{}, Sequence<1>{}));

            const auto a_grid_desc_ak0_m_ak1 =
                transform_tensor_descriptor(a_grid_desc_m_k,
                                            make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
                                                       make_pass_through_transform(MPad)),
                                            make_tuple(Sequence<1>{}, Sequence<0>{}),
                                            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));

            return a_grid_desc_ak0_m_ak1;
        }
        else if constexpr(GemmSpec == GemmSpecialization::MPadding ||
                          GemmSpec == GemmSpecialization::MNPadding)
        {
            // pad M, but not K
            const auto a_grid_desc_ak0_m_ak1 =
                transform_tensor_descriptor(a_grid_desc_mraw_kraw,
                                            make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
                                                       make_right_pad_transform(M, MPad - M)),
                                            make_tuple(Sequence<1>{}, Sequence<0>{}),
                                            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));

            return a_grid_desc_ak0_m_ak1;
        }
        else if constexpr(GemmSpec == GemmSpecialization::KPadding ||
                          GemmSpec == GemmSpecialization::NKPadding)
        {
            // pad K, but not M
            const auto a_grid_desc_m_k = transform_tensor_descriptor(
                a_grid_desc_mraw_kraw,
                make_tuple(make_pass_through_transform(M), make_right_pad_transform(K, KPad - K)),
                make_tuple(Sequence<0>{}, Sequence<1>{}),
                make_tuple(Sequence<0>{}, Sequence<1>{}));

            const auto a_grid_desc_ak0_m_ak1 =
                transform_tensor_descriptor(a_grid_desc_m_k,
                                            make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
                                                       make_pass_through_transform(M)),
                                            make_tuple(Sequence<1>{}, Sequence<0>{}),
                                            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));

            return a_grid_desc_ak0_m_ak1;
        }
        else
        {
            // not pad M or K
            const auto a_grid_desc_ak0_m_ak1 =
                transform_tensor_descriptor(a_grid_desc_mraw_kraw,
                                            make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
                                                       make_pass_through_transform(M)),
                                            make_tuple(Sequence<1>{}, Sequence<0>{}),
                                            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));

            return a_grid_desc_ak0_m_ak1;
        }
    }

    static auto MakeBGridDescriptor_BK0_N_BK1(
        index_t K, index_t KPad, index_t N, index_t NPad, index_t StrideB, index_t BK0)
    {
        const auto b_grid_desc_nraw_kraw = [&]() {
            if constexpr(is_same<tensor_layout::gemm::RowMajor, BLayout>::value)
            {
                return make_naive_tensor_descriptor(make_tuple(N, K), make_tuple(I1, StrideB));
            }
            else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, BLayout>::value)
            {
                return make_naive_tensor_descriptor(make_tuple(N, K), make_tuple(StrideB, I1));
            }
        }();

        if constexpr(GemmSpec == GemmSpecialization::NKPadding ||
                     GemmSpec == GemmSpecialization::MNKPadding)
        {
            // pad both N and K
            const auto b_grid_desc_n_k =
                transform_tensor_descriptor(b_grid_desc_nraw_kraw,
                                            make_tuple(make_right_pad_transform(N, NPad - N),
                                                       make_right_pad_transform(K, KPad - K)),
                                            make_tuple(Sequence<0>{}, Sequence<1>{}),
                                            make_tuple(Sequence<0>{}, Sequence<1>{}));

            const auto b_grid_desc_bk0_n_bk1 =
                transform_tensor_descriptor(b_grid_desc_n_k,
                                            make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
                                                       make_pass_through_transform(NPad)),
                                            make_tuple(Sequence<1>{}, Sequence<0>{}),
                                            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));

            return b_grid_desc_bk0_n_bk1;
        }
        else if constexpr(GemmSpec == GemmSpecialization::NPadding ||
                          GemmSpec == GemmSpecialization::MNPadding)
        {
            // pad N, but not K
            const auto b_grid_desc_bk0_n_bk1 =
                transform_tensor_descriptor(b_grid_desc_nraw_kraw,
                                            make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
                                                       make_right_pad_transform(N, NPad - N)),
                                            make_tuple(Sequence<1>{}, Sequence<0>{}),
                                            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));

            return b_grid_desc_bk0_n_bk1;
        }
        else if constexpr(GemmSpec == GemmSpecialization::KPadding ||
                          GemmSpec == GemmSpecialization::MKPadding)
        {
            // pad K, but not N
            const auto b_grid_desc_n_k = transform_tensor_descriptor(
                b_grid_desc_nraw_kraw,
                make_tuple(make_pass_through_transform(N), make_right_pad_transform(K, KPad - K)),
                make_tuple(Sequence<0>{}, Sequence<1>{}),
                make_tuple(Sequence<0>{}, Sequence<1>{}));

            const auto b_grid_desc_bk0_n_bk1 =
                transform_tensor_descriptor(b_grid_desc_n_k,
                                            make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
                                                       make_pass_through_transform(N)),
                                            make_tuple(Sequence<1>{}, Sequence<0>{}),
                                            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));

            return b_grid_desc_bk0_n_bk1;
        }
        else
        {
            // not pad N or K
            const auto b_grid_desc_bk0_n_bk1 =
                transform_tensor_descriptor(b_grid_desc_nraw_kraw,
                                            make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
                                                       make_pass_through_transform(N)),
                                            make_tuple(Sequence<1>{}, Sequence<0>{}),
                                            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));

            return b_grid_desc_bk0_n_bk1;
        }
    }

    static auto
    MakeCGridDescriptor_M_N(index_t M, index_t MPad, index_t N, index_t NPad, index_t StrideC)
    {
        const auto c_grid_desc_mraw_nraw = [&]() {
            if constexpr(is_same<tensor_layout::gemm::RowMajor, CLayout>::value)
            {
                return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(StrideC, I1));
            }
            else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, CLayout>::value)
            {
                return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(I1, StrideC));
            }
        }();

        if constexpr(GemmSpec == GemmSpecialization::MNPadding ||
                     GemmSpec == GemmSpecialization::MNKPadding)
        {
            // pad M and N
            return transform_tensor_descriptor(c_grid_desc_mraw_nraw,
                                               make_tuple(make_right_pad_transform(M, MPad - M),
                                                          make_right_pad_transform(N, NPad - N)),
                                               make_tuple(Sequence<0>{}, Sequence<1>{}),
                                               make_tuple(Sequence<0>{}, Sequence<1>{}));
        }
        else if constexpr(GemmSpec == GemmSpecialization::MPadding ||
                          GemmSpec == GemmSpecialization::MKPadding)
        {
            // pad M, but not N
            return transform_tensor_descriptor(
                c_grid_desc_mraw_nraw,
                make_tuple(make_right_pad_transform(M, MPad - M), make_pass_through_transform(N)),
                make_tuple(Sequence<0>{}, Sequence<1>{}),
                make_tuple(Sequence<0>{}, Sequence<1>{}));
        }
        else if constexpr(GemmSpec == GemmSpecialization::NPadding ||
                          GemmSpec == GemmSpecialization::NKPadding)
        {
            // pad N, but not M
            return transform_tensor_descriptor(
                c_grid_desc_mraw_nraw,
                make_tuple(make_pass_through_transform(M), make_right_pad_transform(N, NPad - N)),
                make_tuple(Sequence<0>{}, Sequence<1>{}),
                make_tuple(Sequence<0>{}, Sequence<1>{}));
        }
        else
        {
            // not pad M or N
            return c_grid_desc_mraw_nraw;
        }
    }

    using AGridDesc_AK0_M_AK1 = decltype(MakeAGridDescriptor_AK0_M_AK1(1, 1, 1, 1, 1, 1));
    using BGridDesc_BK0_N_BK1 = decltype(MakeBGridDescriptor_BK0_N_BK1(1, 1, 1, 1, 1, 1));
    using CGridDesc_M_N       = decltype(MakeCGridDescriptor_M_N(1, 1, 1, 1, 1));

    // GridwiseGemm
    using GridwiseGemm = GridwiseGemm_k0mk1_k0nk1_mn_xdl_cshuffle_v1<
        ADataType, // TODO: distinguish A/B datatype
        GemmAccDataType,
        CShuffleDataType,
        CDataType,
        AElementwiseOperation,
        BElementwiseOperation,
        CElementwiseOperation,
        GemmSpec,
        InMemoryDataOperationEnum::Set,
        AGridDesc_AK0_M_AK1,
        BGridDesc_BK0_N_BK1,
        CGridDesc_M_N,
        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,
        CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
        CShuffleBlockTransferScalarPerVector_NPerBlock,
        LoopSched,
        PipelineVer>;

    // Argument
    struct Argument : public BaseArgument
    {
        Argument(const ADataType* p_a_grid,
                 const BDataType* p_b_grid,
                 CDataType* p_c_grid,
                 index_t M,
                 index_t N,
                 index_t K,
                 index_t StrideA,
                 index_t StrideB,
                 index_t StrideC)
            : p_a_grid_{p_a_grid},
              p_b_grid_{p_b_grid},
              p_c_grid_{p_c_grid},
              M_{M},
              N_{N},
              K_{K},
              a_grid_desc_ak0_m_ak1_{
                  DeviceOp::MakeAGridDescriptor_AK0_M_AK1(M,
                                                          GridwiseGemm::CalculateMPadded(M),
                                                          K,
                                                          GridwiseGemm::CalculateKPadded(K),
                                                          StrideA,
                                                          GridwiseGemm::CalculateAK0(K))},
              b_grid_desc_bk0_n_bk1_{
                  DeviceOp::MakeBGridDescriptor_BK0_N_BK1(K,
                                                          GridwiseGemm::CalculateKPadded(K),
                                                          N,
                                                          GridwiseGemm::CalculateNPadded(N),
                                                          StrideB,
                                                          GridwiseGemm::CalculateBK0(K))},
              c_grid_desc_m_n_{DeviceOp::MakeCGridDescriptor_M_N(M,
                                                                 GridwiseGemm::CalculateMPadded(M),
                                                                 N,
                                                                 GridwiseGemm::CalculateNPadded(N),
                                                                 StrideC)},
              kraw_{K}
        {
        }

        //  private:
        const ADataType* p_a_grid_;
        const BDataType* p_b_grid_;
        CDataType* p_c_grid_;
        index_t M_;
        index_t N_;
        index_t K_;
        AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1_;
        BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1_;
        CGridDesc_M_N c_grid_desc_m_n_;
        index_t kraw_;
    };

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

        float Run(const Argument& karg, const StreamConfig& stream_config = StreamConfig{})
        {
#if DEBUG_LOG
            {
                std::cout << "arg.a_grid_desc_ak0_m_ak1_{"
                          << karg.a_grid_desc_ak0_m_ak1_.GetLength(I0) << ", "
                          << karg.a_grid_desc_ak0_m_ak1_.GetLength(I1) << ", "
                          << karg.a_grid_desc_ak0_m_ak1_.GetLength(I2) << "}" << std::endl;

                std::cout << "arg.b_grid_desc_bk0_n_bk1_{"
                          << karg.b_grid_desc_bk0_n_bk1_.GetLength(I0) << ", "
                          << karg.b_grid_desc_bk0_n_bk1_.GetLength(I1) << ", "
                          << karg.b_grid_desc_bk0_n_bk1_.GetLength(I2) << "}" << std::endl;

                std::cout << "arg.c_grid_desc_m_n_{ " << arg.c_grid_desc_m_n_.GetLength(I0) << ", "
                          << karg.c_grid_desc_m_n_.GetLength(I1) << "}" << std::endl;
            }
#endif

            if(!GridwiseGemm::CheckValidity(
                   karg.a_grid_desc_ak0_m_ak1_, karg.b_grid_desc_bk0_n_bk1_, karg.c_grid_desc_m_n_))
            {
                throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
            }

            index_t gdx, gdy, gdz;
            std::tie(gdx, gdy, gdz) = GridwiseGemm::CalculateGridSize(karg.M_, karg.N_);

            const auto K = GridwiseGemm::CalculateAK0(karg.K_) * AK1;

            float ave_time = 0;

            if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
            {
                const auto kernel =
                    kernel_gemm_xdl_cshuffle_v1<GridwiseGemm,
                                                ADataType, // TODO: distiguish A/B datatype
                                                CDataType,
                                                DeviceOp::AGridDesc_AK0_M_AK1,
                                                DeviceOp::BGridDesc_BK0_N_BK1,
                                                DeviceOp::CGridDesc_M_N,
                                                true>;

                ave_time = launch_and_time_kernel(stream_config,
                                                  kernel,
                                                  dim3(gdx, gdy, gdz),
                                                  dim3(BlockSize),
                                                  0,
                                                  karg.p_a_grid_,
                                                  karg.p_b_grid_,
                                                  karg.p_c_grid_,
                                                  karg.a_grid_desc_ak0_m_ak1_,
                                                  karg.b_grid_desc_bk0_n_bk1_,
                                                  karg.c_grid_desc_m_n_);
            }
            else
            {
                const auto kernel =
                    kernel_gemm_xdl_cshuffle_v1<GridwiseGemm,
                                                ADataType, // TODO: distiguish A/B datatype
                                                CDataType,
                                                DeviceOp::AGridDesc_AK0_M_AK1,
                                                DeviceOp::BGridDesc_BK0_N_BK1,
                                                DeviceOp::CGridDesc_M_N,
                                                false>;
                ave_time = launch_and_time_kernel(stream_config,
                                                  kernel,
                                                  dim3(gdx, gdy, gdz),
                                                  dim3(BlockSize),
                                                  0,
                                                  karg.p_a_grid_,
                                                  karg.p_b_grid_,
                                                  karg.p_c_grid_,
                                                  karg.a_grid_desc_ak0_m_ak1_,
                                                  karg.b_grid_desc_bk0_n_bk1_,
                                                  karg.c_grid_desc_m_n_);
            }

            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 constexpr bool IsValidCompilationParameter()
    {
        // TODO: properly implement this check
        return true;
    }

    static bool IsSupportedArgument(const Argument& arg)
    {
        if(!(ck::get_device_name() == "gfx908" || ck::get_device_name() == "gfx90a"))
        {
            return false;
        }

        if((arg.kraw_ % AK1 != 0 || arg.kraw_ % BK1 != 0) &&
           !(GemmSpec == GemmSpecialization::MKPadding ||
             GemmSpec == GemmSpecialization::NKPadding ||
             GemmSpec == GemmSpecialization::MNKPadding ||
             GemmSpec == GemmSpecialization::KPadding))
        {
            return false;
        }

        return GridwiseGemm::CheckValidity(
            arg.a_grid_desc_ak0_m_ak1_, arg.b_grid_desc_bk0_n_bk1_, arg.c_grid_desc_m_n_);
    }

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

    static auto MakeArgument(const ADataType* p_a,
                             const BDataType* p_b,
                             CDataType* p_c,
                             index_t M,
                             index_t N,
                             index_t K,
                             index_t StrideA,
                             index_t StrideB,
                             index_t StrideC)
    {
        return Argument{p_a, p_b, p_c, M, N, K, StrideA, StrideB, StrideC};
    }

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

    // polymorphic
    std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
                                                      const void* p_b,
                                                      void* p_c,
                                                      index_t M,
                                                      index_t N,
                                                      index_t K,
                                                      index_t StrideA,
                                                      index_t StrideB,
                                                      index_t StrideC,
                                                      AElementwiseOperation,
                                                      BElementwiseOperation,
                                                      CElementwiseOperation) override
    {
        return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
                                          static_cast<const BDataType*>(p_b),
                                          static_cast<CDataType*>(p_c),
                                          M,
                                          N,
                                          K,
                                          StrideA,
                                          StrideB,
                                          StrideC);
    }

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

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

        std::map<LoopScheduler, std::string> LoopSchedToString{
            {LoopScheduler::Default, "Default"}, {LoopScheduler::Interwave, "Interwave"}};

        std::map<PipelineVersion, std::string> PipelineVersionToString{{PipelineVersion::v1, "v1"},
                                                                       {PipelineVersion::v2, "v2"}};

        // clang-format off
        str << "DeviceGemm_Xdl_CShuffle"
            << "<"
            << BlockSize << ", "
            << MPerBlock << ", "
            << NPerBlock << ", "
            << KPerBlock << ", "
            << AK1 << ", "
            << BK1 << ", "
            << MPerXDL << ", "
            << NPerXDL << ", "
            << MXdlPerWave << ", "
            << NXdlPerWave << ", "
            << ABlockTransferSrcScalarPerVector << ", "
            << BBlockTransferSrcScalarPerVector << ", "
            << CShuffleMXdlPerWavePerShuffle << ", "
            << CShuffleNXdlPerWavePerShuffle
            << ">"
            << " LoopScheduler: "
            << LoopSchedToString[LoopSched] << ", "
            << "PipelineVersion: "
            << PipelineVersionToString[PipelineVer];;
        // clang-format on

        return str.str();
    }
};

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