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 // Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
 // SPDX-License-Identifier: MIT
  
 #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_xdlops_v2r3.hpp"
 #include "ck/host_utility/device_prop.hpp"
 #include "ck/host_utility/kernel_launch.hpp"
  
 namespace ck {
 namespace tensor_operation {
 namespace device {
  
 template <typename ADataType,
           typename BDataType,
           typename CDataType,
           typename AccDataType,
           typename ALayout,
           typename BLayout,
           typename CLayout,
           typename AElementwiseOperation,
           typename BElementwiseOperation,
           typename CElementwiseOperation,
           GemmSpecialization GemmSpec,
           ck::index_t BlockSize,
           ck::index_t MPerBlock,
           ck::index_t NPerBlock,
           ck::index_t K0PerBlock,
           ck::index_t K1,
           ck::index_t MPerXDL,
           ck::index_t NPerXDL,
           ck::index_t MXdlPerWave,
           ck::index_t NXdlPerWave,
           typename ABlockTransferThreadClusterLengths_K0_M_K1,
           typename ABlockTransferThreadClusterArrangeOrder,
           typename ABlockTransferSrcAccessOrder,
           ck::index_t ABlockTransferSrcVectorDim,
           ck::index_t ABlockTransferSrcScalarPerVector,
           ck::index_t ABlockTransferDstScalarPerVector_K1,
           bool ABlockLdsAddExtraM,
           typename BBlockTransferThreadClusterLengths_K0_N_K1,
           typename BBlockTransferThreadClusterArrangeOrder,
           typename BBlockTransferSrcAccessOrder,
           ck::index_t BBlockTransferSrcVectorDim,
           ck::index_t BBlockTransferSrcScalarPerVector,
           ck::index_t BBlockTransferDstScalarPerVector_K1,
           bool BBlockLdsAddExtraN,
           ck::index_t CThreadTransferSrcDstVectorDim,
           ck::index_t CThreadTransferDstScalarPerVector,
           ck::index_t NumPrefetch         = 1,
           ck::LoopScheduler LoopSched     = make_default_loop_scheduler(),
           ck::PipelineVersion PipelineVer = ck::PipelineVersion::v1>
 struct DeviceGemmXdl : public DeviceGemm<ALayout,
                                          BLayout,
                                          CLayout,
                                          ADataType,
                                          BDataType,
                                          CDataType,
                                          AElementwiseOperation,
                                          BElementwiseOperation,
                                          CElementwiseOperation>
 {
     GET_NXDL_PER_WAVE_IMPL
     static constexpr auto NXdlPerWave64 = GetNXdlPerWave<true>();
     static constexpr auto NXdlPerWave32 = GetNXdlPerWave<false>();
  
     static constexpr auto I0 = Number<0>{};
     static constexpr auto I1 = Number<1>{};
     static constexpr auto I2 = Number<2>{};
  
     static constexpr auto K1Number = Number<K1>{};
  
     // GridwiseGemm
     template <index_t NXdlPerWave_>
     using GridwiseGemmBase = GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3_ext<
         BlockSize,
         ADataType, // TODO: distinguish A/B datatype
         AccDataType,
         CDataType,
         InMemoryDataOperationEnum::Set,
         ALayout,
         BLayout,
         CLayout,
         AElementwiseOperation,
         BElementwiseOperation,
         CElementwiseOperation,
         GemmSpec,
         MPerBlock,
         NPerBlock,
         K0PerBlock,
         MPerXDL,
         NPerXDL,
         K1,
         MXdlPerWave,
         NXdlPerWave_,
         ABlockTransferThreadClusterLengths_K0_M_K1,
         ABlockTransferThreadClusterArrangeOrder,
         ABlockTransferSrcAccessOrder,
         ABlockTransferSrcVectorDim,
         ABlockTransferSrcScalarPerVector,
         ABlockTransferDstScalarPerVector_K1,
         false, // AThreadTransferSrcResetCoordinateAfterRun,
         ABlockLdsAddExtraM,
         BBlockTransferThreadClusterLengths_K0_N_K1,
         BBlockTransferThreadClusterArrangeOrder,
         BBlockTransferSrcAccessOrder,
         BBlockTransferSrcVectorDim,
         BBlockTransferSrcScalarPerVector,
         BBlockTransferDstScalarPerVector_K1,
         false, // BThreadTransferSrcResetCoordinateAfterRun,
         BBlockLdsAddExtraN,
         Sequence<0, 2, 4, 5, 6, 1, 3, 7>, // CThreadTransferSrcDstAccessOrder,
         CThreadTransferSrcDstVectorDim,
         CThreadTransferDstScalarPerVector,
         NumPrefetch,
         LoopSched,
         PipelineVer>;
     using GridwiseGemm64 = GridwiseGemmBase<math::max(NXdlPerWave64, 1)>;
     using GridwiseGemm32 = GridwiseGemmBase<NXdlPerWave32>;
  
     using Argument = typename GridwiseGemm64::Argument;
  
     // Invoker
     struct Invoker : public BaseInvoker
     {
         template <typename GridwiseGemm>
         float RunImp(const typename GridwiseGemm::Argument& karg,
                      const StreamConfig& stream_config = StreamConfig{})
         {
             if(stream_config.log_level_ > 0)
             {
                 karg.Print();
             }
  
             if(!GridwiseGemm::CheckValidity(karg))
             {
                 throw std::runtime_error(
                     "wrong! GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3_ext has invalid setting");
             }
  
             const auto [gdx, gdy, gdz] = GridwiseGemm::CalculateGridSize(karg.M, karg.N);
  
             float ave_time = 0;
  
             if(GridwiseGemm::CalculateHasMainKBlockLoop(karg.K))
             {
                 const auto kernel = kernel_gemm_xdlops_v2r3<GridwiseGemm, true>;
  
                 ave_time = launch_and_time_kernel(
                     stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, karg);
             }
             else
             {
                 const auto kernel = kernel_gemm_xdlops_v2r3<GridwiseGemm, false>;
  
                 ave_time = launch_and_time_kernel(
                     stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, karg);
             }
  
             return ave_time;
         }
  
         INVOKER_RUN3_IMPL
  
         // 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& karg)
     {
         if(ck::get_device_name() == "gfx908")
         {
             if constexpr(!(is_same_v<AccDataType, float> || is_same_v<AccDataType, float> ||
                            is_same_v<AccDataType, int32_t>))
             {
                 return false;
             }
         }
         else if(ck::is_lds_direct_load_supported())
         {
             if constexpr(!(is_same_v<AccDataType, float> || is_same_v<AccDataType, float> ||
                            is_same_v<AccDataType, int32_t> || is_same_v<AccDataType, double>))
             {
                 return false;
             }
         }
         else
         {
             return false;
         }
  
         if(karg.K % K1 != 0)
         {
             return false;
         }
         if(get_warp_size() == 64)
         {
             if constexpr(NXdlPerWave64 > 0)
             {
                 return GridwiseGemm64::CheckValidity(karg);
             }
         }
         else
         {
             if constexpr(NXdlPerWave32 > 0)
             {
                 return GridwiseGemm32::CheckValidity(
                     reinterpret_cast<const typename GridwiseGemm32::Argument&>(karg));
             }
         }
         return false;
     }
  
     // 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,
                              AElementwiseOperation,
                              BElementwiseOperation,
                              CElementwiseOperation)
     {
         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 << "DeviceGemmXdl"
             << "<"
             << BlockSize << ", "
             << MPerBlock << ", "
             << NPerBlock << ", "
             << K0PerBlock << ", "
             << K1 << ", "
             << MPerXDL << ", "
             << NPerXDL << ", "
             << MXdlPerWave << ", "
             << NXdlPerWave << ", "
             << ABlockTransferSrcScalarPerVector << ", "
             << ABlockTransferDstScalarPerVector_K1 << ", "
             << BBlockTransferSrcScalarPerVector << ", "
             << BBlockTransferDstScalarPerVector_K1
             << ">"
             << " NumPrefetch: "
             << NumPrefetch << ", "
             << "LoopScheduler: "
             << LoopSchedToString[LoopSched] << ", "
             << "PipelineVersion: "
             << PipelineVersionToString[PipelineVer];
         // clang-format on
  
         return str.str();
     }
 };
  
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck