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 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
  
 #pragma once
  
 #include "ck_tile/core.hpp"
 #include "ck_tile/ops/gemm/warp/warp_gemm_dispatcher.hpp"
 #include "ck_tile/ops/common/tensor_layout.hpp"
  
 namespace ck_tile {
  
 // this epilogue just store out a M*N matrix, row major
  
 template <typename AccDataType_,
           typename ODataType_,
           bool kPadM_,
           bool kPadN_,
           bool UseRawStore_                      = true,
           memory_operation_enum MemoryOperation_ = memory_operation_enum::set>
 struct Default2DEpilogueProblem
 {
     using AccDataType                                      = remove_cvref_t<AccDataType_>;
     using ODataType                                        = remove_cvref_t<ODataType_>;
     static constexpr bool kPadM                            = kPadM_;
     static constexpr bool kPadN                            = kPadN_;
     static constexpr bool UseRawStore                      = UseRawStore_;
     static constexpr memory_operation_enum MemoryOperation = MemoryOperation_;
     static constexpr index_t NumDTensor                    = 0;
 };
  
 template <typename ADataType_,
           typename BDataType_,
           typename DsDataType_,
           typename AccDataType_,
           typename ODataType_,
           typename DsLayout_,
           typename CLayout_,
           typename CDElementwise_,
           index_t kM_,
           index_t kN_,
           bool kPadM_,
           bool kPadN_,
           index_t kMPerXdl_,
           index_t kNPerXdl_,
           index_t kKPerXdl_,
           bool isCTransposed_,
           bool UseRawStore_                      = true,
           memory_operation_enum MemoryOperation_ = memory_operation_enum::set>
 struct DefaultGemm2DEpilogueProblem : public Default2DEpilogueProblem<AccDataType_,
                                                                       ODataType_,
                                                                       kPadM_,
                                                                       kPadN_,
                                                                       UseRawStore_,
                                                                       MemoryOperation_>
 {
     using ADataType                        = remove_cvref_t<ADataType_>;
     using BDataType                        = remove_cvref_t<BDataType_>;
     using CLayout                          = remove_cvref_t<CLayout_>;
     using DsDataType                       = remove_cvref_t<DsDataType_>;
     using CDElementwise                    = remove_cvref_t<CDElementwise_>;
     using DsLayout                         = remove_cvref_t<DsLayout_>;
     static constexpr index_t kMPerBlock    = kM_;
     static constexpr index_t kNPerBlock    = kN_;
     static constexpr index_t kMPerXdl      = kMPerXdl_;
     static constexpr index_t kNPerXdl      = kNPerXdl_;
     static constexpr index_t kKPerXdl      = kKPerXdl_;
     static constexpr index_t isCTransposed = isCTransposed_;
  
     static constexpr index_t NumDTensor = DsDataType::size();
  
     static_assert(NumDTensor == DsLayout::size(),
                   "The size of DsDataType and DsLayout should be the same");
 };
  
 template <typename Problem_, typename Policy_ = void>
 struct Default2DEpilogue
 {
     using Problem                     = remove_cvref_t<Problem_>;
     using AccDataType                 = remove_cvref_t<typename Problem::AccDataType>;
     using ODataType                   = remove_cvref_t<typename Problem::ODataType>;
     static constexpr bool kPadM       = Problem::kPadM;
     static constexpr bool kPadN       = Problem::kPadN;
     static constexpr bool UseRawStore = Problem::UseRawStore;
     static constexpr memory_operation_enum MemoryOperation = Problem::MemoryOperation;
  
     CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize() { return 0; }
  
     // TODO: this function assume store out vector size is the same as OAccTile last dimension size
     //       how do we fix this ?
     template <typename ODramWindowTmp, typename OAccTile, typename DsDramWindows>
     CK_TILE_DEVICE auto operator()(ODramWindowTmp& o_dram_window_tmp,
                                    const OAccTile& o_acc_tile,
                                    const DsDramWindows& ds_dram_windows,
                                    void* = nullptr)
     {
         const auto storeOrUpdateTile = [&](const auto& o_tile) {
             // TODO: this is ugly
             if constexpr(UseRawStore && (kPadM || kPadN))
             {
                 if constexpr(MemoryOperation == memory_operation_enum::set)
                 {
                     store_tile_raw(o_dram_window_tmp, cast_tile<ODataType>(o_tile));
                 }
                 else
                 {
                     update_tile_raw(o_dram_window_tmp, cast_tile<ODataType>(o_tile));
                 }
                 buffer_store_fence();
             }
             else
             {
                 if constexpr(MemoryOperation == memory_operation_enum::set)
                 {
                     store_tile(o_dram_window_tmp, cast_tile<ODataType>(o_tile));
                 }
                 else
                 {
                     update_tile(o_dram_window_tmp, cast_tile<ODataType>(o_tile));
                 }
             }
         };
  
         if constexpr(!std::is_same_v<DsDramWindows, std::nullptr_t> && Problem::NumDTensor >= 1)
         {
             using elementwise_result_t = decltype(load_tile(
                 make_tile_window(ds_dram_windows[number<0>{}].get_bottom_tensor_view(),
                                  make_tuple(Problem::kMPerBlock, Problem::kNPerBlock),
                                  ds_dram_windows[number<0>{}].get_window_origin(),
                                  o_acc_tile.get_tile_distribution())));
  
             elementwise_result_t elementwise_result;
  
             const auto d_tensor_tuple = generate_tuple(
                 [&](auto idx) {
                     const auto d_tile_window =
                         make_tile_window(ds_dram_windows[idx], o_acc_tile.get_tile_distribution());
                     return load_tile(d_tile_window);
                 },
                 number<Problem::NumDTensor>{});
  
             const auto c_d_tuple = concat_tuple_of_reference(
                 tie(elementwise_result, o_acc_tile),
                 generate_tie([&](auto idx) -> const auto& { return d_tensor_tuple[idx]; },
                              number<Problem::NumDTensor>{}));
  
             tile_elementwise_inout_unpack(typename Problem::CDElementwise{}, c_d_tuple);
  
             storeOrUpdateTile(elementwise_result);
         }
         else
         {
             storeOrUpdateTile(o_acc_tile);
         }
     }
 };
  
 template <typename Problem_, typename Policy_ = void>
 struct DefaultGemm2DEpilogue : public Default2DEpilogue<Problem_, Policy_>
 {
     using Problem     = remove_cvref_t<Problem_>;
     using ADataType   = remove_cvref_t<typename Problem::ADataType>;
     using BDataType   = remove_cvref_t<typename Problem::BDataType>;
     using AccDataType = remove_cvref_t<typename Problem::AccDataType>;
     using ODataType   = remove_cvref_t<typename Problem::ODataType>;
     // Used for weight-only quantization kernel, B would be dequantized to the same data type as A
     using BTypeToUse =
         std::conditional_t<std::is_same_v<BDataType, pk_int4_t>, ADataType, BDataType>;
     using DsDataType                       = remove_cvref_t<typename Problem::DsDataType>;
     using DsLayout                         = remove_cvref_t<typename Problem::DsLayout>;
     using CDElementwise                    = remove_cvref_t<typename Problem::CDElementwise>;
     using CLayout                          = remove_cvref_t<typename Problem::CLayout>;
     static constexpr index_t kMPerXdl      = Problem::kMPerXdl;
     static constexpr index_t kNPerXdl      = Problem::kNPerXdl;
     static constexpr index_t kKPerXdl      = Problem::kKPerXdl;
     static constexpr index_t isCTransposed = Problem::isCTransposed;
  
     using WG = WarpGemmDispatcher<ADataType,
                                   BTypeToUse,
                                   AccDataType,
                                   kMPerXdl,
                                   kNPerXdl,
                                   kKPerXdl,
                                   isCTransposed>;
  
     using CWarpDstr = typename WG::CWarpDstr;
  
     CK_TILE_HOST_DEVICE static constexpr auto GetVectorSizeC()
     {
         // N is contiguous dimension
         if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
         {
             if constexpr(isCTransposed)
             {
                 // In this case each thread has multiple consecutive elements in
                 // N dimension, however consecutive threads' elements have stride.
                 constexpr index_t NDimY = CWarpDstr::NDimY;
                 constexpr auto c_warp_y_lengths =
                     CWarpDstr{}.get_ys_to_d_descriptor().get_lengths();
                 static_assert(WG::WarpGemmAttribute::Impl::kCM1PerLane ==
                               c_warp_y_lengths.get(number<NDimY - 1>{}));
                 return c_warp_y_lengths.get(number<NDimY - 1>{});
             }
             else
             {
                 // In this case each thread has just a single item in Ndim
                 return (WG::WarpGemmAttribute::Impl::kCNLane *
                         WG::WarpGemmAttribute::Impl::kBNBlock) /
                        WG::kN;
             }
         }
         // M is contiguous dimension
         else if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::ColumnMajor>)
         {
             if constexpr(isCTransposed)
             {
                 // In this case each thread has just a single item in Mdim
                 return (WG::WarpGemmAttribute::Impl::kCNLane *
                         WG::WarpGemmAttribute::Impl::kAMBlock) /
                        WG::kN;
             }
             else
             {
                 // In this case each thread has multiple consecutive elements in
                 // M dimension, however consecutive threads' elements have stride.
                 constexpr index_t NDimY = CWarpDstr::NDimY;
                 constexpr auto c_warp_y_lengths =
                     CWarpDstr{}.get_ys_to_d_descriptor().get_lengths();
                 static_assert(WG::WarpGemmAttribute::Impl::kCM1PerLane ==
                               c_warp_y_lengths.get(number<NDimY - 1>{}));
                 return c_warp_y_lengths.get(number<NDimY - 1>{});
             }
         }
         else
         {
             static_assert(false, "Unsupported CLayout!");
         }
     }
  
     template <index_t I>
     CK_TILE_HOST_DEVICE static constexpr auto GetVectorSizeD([[maybe_unused]] number<I> index)
     {
         return GetVectorSizeC();
     }
 };
  
 } // namespace ck_tile