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 // Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
 // SPDX-License-Identifier: MIT
  
 #pragma once
  
 #include "ck_tile/core.hpp"
 #include "ck_tile/ops/common.hpp"
 #include "ck_tile/ops/fmha/block/block_masking.hpp"
  
 #include <type_traits>
 #include <utility>
  
 namespace ck_tile {
  
 template <typename FmhaPipeline_, typename EpiloguePipeline_>
 struct FmhaFwdV3Kernel
 {
     using FmhaPipeline                            = ck_tile::remove_cvref_t<FmhaPipeline_>;
     using EpiloguePipeline                        = ck_tile::remove_cvref_t<EpiloguePipeline_>;
     static constexpr ck_tile::index_t kBlockSize  = FmhaPipeline::kBlockSize;
     static constexpr ck_tile::index_t kBlockPerCu = FmhaPipeline::kBlockPerCu;
     static_assert(kBlockPerCu > 0);
  
     using QDataType    = ck_tile::remove_cvref_t<typename FmhaPipeline::QDataType>;
     using KDataType    = ck_tile::remove_cvref_t<typename FmhaPipeline::KDataType>;
     using VDataType    = ck_tile::remove_cvref_t<typename FmhaPipeline::VDataType>;
     using LSEDataType  = ck_tile::remove_cvref_t<typename FmhaPipeline::LSEDataType>;
     using ODataType    = ck_tile::remove_cvref_t<typename FmhaPipeline::ODataType>;
     using SaccDataType = ck_tile::remove_cvref_t<typename FmhaPipeline::SaccDataType>;
  
     static constexpr bool kIsGroupMode = FmhaPipeline::kIsGroupMode;
     static constexpr bool kPadSeqLenQ  = FmhaPipeline::kPadSeqLenQ;
     static constexpr bool kPadSeqLenK  = FmhaPipeline::kPadSeqLenK;
     static constexpr bool kPadHeadDimQ = FmhaPipeline::kPadHeadDimQ;
     static constexpr bool kPadHeadDimV = FmhaPipeline::kPadHeadDimV;
     static constexpr bool kStoreLSE    = FmhaPipeline::kStoreLSE;
  
     using FmhaMask                 = ck_tile::remove_cvref_t<typename FmhaPipeline::FmhaMask>;
     static constexpr bool kHasMask = FmhaMask::IsMasking;
  
     template <ck_tile::index_t I> // to avoid duplicated base class prblem, introduce an template
                                   // arg
     struct FmhaFwdEmptyKargs
     {
     };
  
     // kargs use aggregate initializer, so no constructor will provided
     // use inheritance to minimize karg size
     // user need to use MakeKargs() function to create kargs.
     struct FmhaFwdCommonKargs
     {
         const void* q_ptr;
         const void* k_ptr;
         const void* v_ptr;
         void* o_ptr;
  
         ck_tile::index_t seqlen_q;
         ck_tile::index_t seqlen_k;
         ck_tile::index_t hdim_q;
         ck_tile::index_t hdim_v;
  
         ck_tile::index_t num_head_q;
         // for MQA/GQA, nhead could be different. This parameter is nhead_q / nhead_k
         // if this param is larger than 1, indicate MQA/GQA case
         ck_tile::index_t nhead_ratio_qk;
         float scale_s;
  
         ck_tile::index_t stride_q;
         ck_tile::index_t stride_k;
         ck_tile::index_t stride_v;
         ck_tile::index_t stride_o;
  
         ck_tile::index_t nhead_stride_q;
         ck_tile::index_t nhead_stride_k;
         ck_tile::index_t nhead_stride_v;
         ck_tile::index_t nhead_stride_o;
     };
  
     struct FmhaFwdMaskKargs
     {
         // ck_tile::index_t window_size_left, window_size_right;
         ck_tile::index_t window_size_left, window_size_right;
         ck_tile::GenericAttentionMaskEnum mask_type;
         ck_tile::index_t remap_opt;
     };
  
     struct FmhaFwdCommonLSEKargs
     {
         void* lse_ptr                     = nullptr;
         ck_tile::index_t nhead_stride_lse = 0;
         ck_tile::index_t batch_stride_lse = 0;
     };
  
     struct FmhaFwdBatchModeKargs
         : FmhaFwdCommonKargs,
           std::conditional_t<kHasMask, FmhaFwdMaskKargs, FmhaFwdEmptyKargs<0>>,
           std::conditional_t<kStoreLSE, FmhaFwdCommonLSEKargs, FmhaFwdEmptyKargs<1>>
     {
         ck_tile::index_t batch_stride_q;
         ck_tile::index_t batch_stride_k;
         ck_tile::index_t batch_stride_v;
         ck_tile::index_t batch_stride_o;
  
         // Optional cumulative sequence length pointers for batch mode
         // If provided, they override seqlen_q / seqlen_k per-batch to skip tail padding.
         const ck_tile::index_t* cu_seqlen_q_ptr = nullptr; // [batch+1]
         const ck_tile::index_t* cu_seqlen_k_ptr = nullptr; // [batch+1]
     };
  
     struct FmhaFwdGroupModeKargs
         : FmhaFwdCommonKargs,
           std::conditional_t<kHasMask, FmhaFwdMaskKargs, FmhaFwdEmptyKargs<0>>,
           std::conditional_t<kStoreLSE, FmhaFwdCommonLSEKargs, FmhaFwdEmptyKargs<1>>
     {
         const int32_t* seqstart_q_ptr;
         const int32_t* seqstart_k_ptr;
         const int32_t* seqlen_q_ptr;
         const int32_t* seqlen_k_ptr;
  
         // Optional cumulative padded sequence starts (including PAD tokens)
         // Used solely to compute memory offsets when sequences are physically padded.
         const int32_t* cu_seqlen_q_ptr = nullptr; // [batch+1]
         const int32_t* cu_seqlen_k_ptr = nullptr; // [batch+1]
     };
  
     using Kargs = std::conditional_t<kIsGroupMode, FmhaFwdGroupModeKargs, FmhaFwdBatchModeKargs>;
  
     template <bool Cond = !kIsGroupMode>
     CK_TILE_HOST static constexpr std::enable_if_t<Cond, Kargs>
     MakeKargs(const void* q_ptr,
               const void* k_ptr,
               const void* v_ptr,
               void* lse_ptr,
               void* o_ptr,
               ck_tile::index_t seqlen_q,
               ck_tile::index_t seqlen_k,
               ck_tile::index_t hdim_q,
               ck_tile::index_t hdim_v,
               ck_tile::index_t num_head_q,
               ck_tile::index_t nhead_ratio_qk,
               float scale_s,
               ck_tile::index_t stride_q,
               ck_tile::index_t stride_k,
               ck_tile::index_t stride_v,
               ck_tile::index_t stride_o,
               ck_tile::index_t nhead_stride_q,
               ck_tile::index_t nhead_stride_k,
               ck_tile::index_t nhead_stride_v,
               ck_tile::index_t nhead_stride_lse,
               ck_tile::index_t nhead_stride_o,
               ck_tile::index_t batch_stride_q,
               ck_tile::index_t batch_stride_k,
               ck_tile::index_t batch_stride_v,
               ck_tile::index_t batch_stride_lse,
               ck_tile::index_t batch_stride_o,
               ck_tile::index_t window_size_left,
               ck_tile::index_t window_size_right,
               ck_tile::index_t mask_type,
               ck_tile::index_t remap_opt,
               const void* cu_seqlen_q_ptr = nullptr,
               const void* cu_seqlen_k_ptr = nullptr)
     {
         Kargs kargs{{q_ptr,
                      k_ptr,
                      v_ptr,
                      o_ptr,
                      seqlen_q,
                      seqlen_k,
                      hdim_q,
                      hdim_v,
                      num_head_q,
                      nhead_ratio_qk,
                      static_cast<float>(scale_s * ck_tile::log2e_v<>),
                      stride_q,
                      stride_k,
                      stride_v,
                      stride_o,
                      nhead_stride_q,
                      nhead_stride_k,
                      nhead_stride_v,
                      nhead_stride_o}, // args for common karg
                     {},               // placeholder for mask
                     {},               // placeholder for lse
                     batch_stride_q,
                     batch_stride_k,
                     batch_stride_v,
                     batch_stride_o};
  
         if constexpr(kHasMask)
         {
             kargs.window_size_left  = window_size_left;
             kargs.window_size_right = window_size_right;
             kargs.mask_type         = static_cast<ck_tile::GenericAttentionMaskEnum>(mask_type);
             kargs.remap_opt         = remap_opt;
         }
         if constexpr(kStoreLSE)
         {
             kargs.lse_ptr          = lse_ptr;
             kargs.nhead_stride_lse = nhead_stride_lse;
             kargs.batch_stride_lse = batch_stride_lse;
         }
  
         kargs.cu_seqlen_q_ptr = reinterpret_cast<const int32_t*>(cu_seqlen_q_ptr);
         kargs.cu_seqlen_k_ptr = reinterpret_cast<const int32_t*>(cu_seqlen_k_ptr);
         return kargs;
     }
  
     template <bool Cond = kIsGroupMode>
     CK_TILE_HOST static constexpr std::enable_if_t<Cond, Kargs>
     MakeKargs(const void* q_ptr,
               const void* k_ptr,
               const void* v_ptr,
               void* lse_ptr,
               void* o_ptr,
               const void* seqstart_q_ptr,
               const void* seqstart_k_ptr,
               const void* seqlen_q_ptr,
               const void* seqlen_k_ptr,
               ck_tile::index_t hdim_q,
               ck_tile::index_t hdim_v,
               ck_tile::index_t num_head_q,
               ck_tile::index_t nhead_ratio_qk,
               float scale_s,
               ck_tile::index_t stride_q,
               ck_tile::index_t stride_k,
               ck_tile::index_t stride_v,
               ck_tile::index_t stride_o,
               ck_tile::index_t nhead_stride_q,
               ck_tile::index_t nhead_stride_k,
               ck_tile::index_t nhead_stride_v,
               ck_tile::index_t nhead_stride_lse,
               ck_tile::index_t nhead_stride_o,
               ck_tile::index_t window_size_left,
               ck_tile::index_t window_size_right,
               ck_tile::index_t mask_type,
               ck_tile::index_t remap_opt,
               const void* cu_seqlen_q_ptr = nullptr,
               const void* cu_seqlen_k_ptr = nullptr)
     {
         Kargs kargs{{q_ptr,
                      k_ptr,
                      v_ptr,
                      o_ptr,
                      -1, // seqlen will be updated by another pointer
                      -1, //
                      hdim_q,
                      hdim_v,
                      num_head_q,
                      nhead_ratio_qk,
                      static_cast<float>(scale_s * ck_tile::log2e_v<>),
                      stride_q,
                      stride_k,
                      stride_v,
                      stride_o,
                      nhead_stride_q,
                      nhead_stride_k,
                      nhead_stride_v,
                      nhead_stride_o}, // args for common karg
                     {},               // placeholder for mask
                     {},               // placeholder for lse
                     reinterpret_cast<const int32_t*>(seqstart_q_ptr),
                     reinterpret_cast<const int32_t*>(seqstart_k_ptr),
                     reinterpret_cast<const int32_t*>(seqlen_q_ptr),
                     reinterpret_cast<const int32_t*>(seqlen_k_ptr)};
  
         if constexpr(kHasMask)
         {
             kargs.window_size_left  = window_size_left;
             kargs.window_size_right = window_size_right;
             kargs.mask_type         = static_cast<ck_tile::GenericAttentionMaskEnum>(mask_type);
             kargs.remap_opt         = remap_opt;
         }
         if constexpr(kStoreLSE)
         {
             kargs.lse_ptr          = lse_ptr;
             kargs.nhead_stride_lse = nhead_stride_lse;
         }
  
         kargs.cu_seqlen_q_ptr = reinterpret_cast<const int32_t*>(cu_seqlen_q_ptr);
         kargs.cu_seqlen_k_ptr = reinterpret_cast<const int32_t*>(cu_seqlen_k_ptr);
         return kargs;
     }
  
     CK_TILE_HOST static constexpr auto GridSize(ck_tile::index_t batch_size,
                                                 ck_tile::index_t nhead,
                                                 ck_tile::index_t max_seqlen_q,
                                                 ck_tile::index_t hdim_v)
     {
         if constexpr(kIsGroupMode)
         {
             return dim3(nhead,
                         batch_size,
                         ck_tile::integer_divide_ceil(max_seqlen_q, FmhaPipeline::kM0) *
                             ck_tile::integer_divide_ceil(hdim_v, FmhaPipeline::kN1));
         }
         else
         {
             return dim3(nhead,
                         ck_tile::integer_divide_ceil(max_seqlen_q, FmhaPipeline::kM0) *
                             ck_tile::integer_divide_ceil(hdim_v, FmhaPipeline::kN1),
                         batch_size);
         }
     }
  
     CK_TILE_DEVICE static constexpr auto
     RemapTileIndices(int32_t tg_idx, int32_t tg_idy, int32_t remap_option)
     {
         if(remap_option < 1)
         {
             return make_tuple(static_cast<int32_t>(gridDim.x - tg_idx - 1), tg_idy);
         }
  
         int32_t remapped_tg_idx = tg_idx;
         int32_t remapped_tg_idy = tg_idy;
  
         if(remap_option == 2)
         { // special remapping
             int32_t tmp0 = (remapped_tg_idy & 0x7) * gridDim.x + remapped_tg_idx;
             int32_t tmp1 = tmp0 & 0x7;
  
             remapped_tg_idx = tmp0 >> 3;
             remapped_tg_idy = (remapped_tg_idy & 0xfffffff8) + tmp1;
         }
         else
         { // normal remapping
             int32_t cus_per_xdim_per_xcc = gridDim.x >> 3;
             int32_t tgs_cu_id            = remapped_tg_idx >> 3;
  
             if(tgs_cu_id < cus_per_xdim_per_xcc)
             {
                 int32_t tgs_xcc_id = remapped_tg_idx & 0x7;
                 int32_t new_tg_idx = tgs_xcc_id * cus_per_xdim_per_xcc + tgs_cu_id;
  
                 remapped_tg_idx = new_tg_idx;
             }
         }
  
         return make_tuple(remapped_tg_idx, remapped_tg_idy);
     }
  
     CK_TILE_DEVICE static constexpr auto GetTileIndex(const Kargs&)
     {
         using namespace ck_tile;
  
         // const index_t num_tile_n1 = ck_tile::integer_divide_ceil(kargs.hdim_v,
         // FmhaPipeline::kN1);
  
         // assume that num_tile_n1 is always 1
         if constexpr(kIsGroupMode)
         {
             const index_t i_nhead = blockIdx.x;
             const index_t i_batch = blockIdx.y;
             const index_t i_block = blockIdx.z;
  
             if constexpr(kHasMask)
             {
                 return ck_tile::make_tuple(gridDim.z - 1 - i_block, 0, i_nhead, i_batch);
             }
             else
             {
                 return ck_tile::make_tuple(i_block, 0, i_nhead, i_batch);
             }
         }
         else
         {
             const index_t i_nhead = blockIdx.x;
             const index_t i_block = blockIdx.y;
             const index_t i_batch = blockIdx.z;
  
             if constexpr(kHasMask)
             {
                 return ck_tile::make_tuple(gridDim.y - 1 - i_block, 0, i_nhead, i_batch);
             }
             else
             {
                 return ck_tile::make_tuple(i_block, 0, i_nhead, i_batch);
             }
         }
     }
  
     CK_TILE_HOST static constexpr auto BlockSize() { return dim3(kBlockSize); }
  
     CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetSmemSize()
     {
         return ck_tile::max(FmhaPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
     }
  
     CK_TILE_DEVICE void operator()(Kargs kargs) const
     {
         using namespace ck_tile;
  
         // allocate LDS
         __shared__ char smem_ptr[GetSmemSize()];
  
         // divide problem
         const auto [i_tile_m, i_tile_n, i_nhead, i_batch] = GetTileIndex(kargs);
  
         const index_t i_m0 = amd_wave_read_first_lane(i_tile_m * FmhaPipeline::kM0);
         const index_t i_n1 = amd_wave_read_first_lane(i_tile_n * FmhaPipeline::kN1);
  
         long_index_t batch_offset_q   = 0;
         long_index_t batch_offset_k   = 0;
         long_index_t batch_offset_v   = 0;
         long_index_t batch_offset_lse = 0;
         long_index_t batch_offset_o   = 0;
  
         if constexpr(kIsGroupMode)
         {
             // Use seqstart_q_ptr and seqstart_k_ptr for physical starts
             const long_index_t query_start = kargs.seqstart_q_ptr[i_batch];
             const long_index_t key_start   = kargs.seqstart_k_ptr[i_batch];
  
             batch_offset_q = query_start * kargs.stride_q;
             batch_offset_k = key_start * kargs.stride_k;
             batch_offset_v = key_start * kargs.stride_v;
  
             if constexpr(kStoreLSE)
             {
                 // LSE layout is [nhead, total_seqlen], index by unpadded start
                 batch_offset_lse = query_start;
             }
             batch_offset_o = query_start * kargs.stride_o;
  
             // real logical lengths (exclude PAD)
             // Priority: seqlen_q_ptr > cu_seqlen_q_ptr > calculated from seqstart_q_ptr
             if(kargs.seqlen_q_ptr != nullptr)
             {
                 kargs.seqlen_q = kargs.seqlen_q_ptr[i_batch];
             }
             else if(kargs.cu_seqlen_q_ptr != nullptr)
             {
                 kargs.seqlen_q =
                     kargs.cu_seqlen_q_ptr[i_batch + 1] - kargs.cu_seqlen_q_ptr[i_batch];
             }
             else
             {
                 kargs.seqlen_q = kargs.seqstart_q_ptr[i_batch + 1] - kargs.seqstart_q_ptr[i_batch];
             }
             // # of required blocks is different in each groups, terminate unnecessary blocks
             // earlier
             if(kargs.seqlen_q <= i_m0)
             {
                 return;
             }
  
             if(kargs.seqlen_k_ptr != nullptr)
             {
                 kargs.seqlen_k = kargs.seqlen_k_ptr[i_batch];
             }
             else if(kargs.cu_seqlen_k_ptr != nullptr)
             {
                 kargs.seqlen_k =
                     kargs.cu_seqlen_k_ptr[i_batch + 1] - kargs.cu_seqlen_k_ptr[i_batch];
             }
             else
             {
                 kargs.seqlen_k = kargs.seqstart_k_ptr[i_batch + 1] - kargs.seqstart_k_ptr[i_batch];
             }
         }
         else
         {
             batch_offset_q = static_cast<long_index_t>(i_batch) * kargs.batch_stride_q;
             batch_offset_k = static_cast<long_index_t>(i_batch) * kargs.batch_stride_k;
             batch_offset_v = static_cast<long_index_t>(i_batch) * kargs.batch_stride_v;
             if constexpr(kStoreLSE)
             {
                 batch_offset_lse = static_cast<long_index_t>(i_batch) * kargs.batch_stride_lse;
             }
             batch_offset_o = static_cast<long_index_t>(i_batch) * kargs.batch_stride_o;
  
             // If cumulative seqlen pointers are provided, override per-batch effective lengths
             if(kargs.cu_seqlen_q_ptr != nullptr)
             {
                 kargs.seqlen_q =
                     kargs.cu_seqlen_q_ptr[i_batch + 1] - kargs.cu_seqlen_q_ptr[i_batch];
             }
             if(kargs.cu_seqlen_k_ptr != nullptr)
             {
                 kargs.seqlen_k =
                     kargs.cu_seqlen_k_ptr[i_batch + 1] - kargs.cu_seqlen_k_ptr[i_batch];
             }
         }
  
         // for simplicity, batch stride we just modify the pointer
         const QDataType* q_ptr = reinterpret_cast<const QDataType*>(kargs.q_ptr) +
                                  static_cast<long_index_t>(i_nhead) * kargs.nhead_stride_q +
                                  batch_offset_q;
         const KDataType* k_ptr =
             reinterpret_cast<const KDataType*>(kargs.k_ptr) +
             static_cast<long_index_t>(i_nhead / kargs.nhead_ratio_qk) * kargs.nhead_stride_k +
             batch_offset_k;
         const VDataType* v_ptr =
             reinterpret_cast<const VDataType*>(kargs.v_ptr) +
             static_cast<long_index_t>(i_nhead / kargs.nhead_ratio_qk) * kargs.nhead_stride_v +
             batch_offset_v;
         ODataType* o_ptr = reinterpret_cast<ODataType*>(kargs.o_ptr) +
                            static_cast<long_index_t>(i_nhead) * kargs.nhead_stride_o +
                            batch_offset_o;
  
         // Q/K/V DRAM and DRAM window
         const auto q_dram = [&]() {
             const auto q_dram_naive = make_naive_tensor_view<address_space_enum::global>(
                 q_ptr,
                 make_tuple(kargs.seqlen_q, kargs.hdim_q),
                 make_tuple(kargs.stride_q, 1),
                 number<FmhaPipeline::kAlignmentQ>{},
                 number<1>{});
  
             return pad_tensor_view(
                 q_dram_naive,
                 make_tuple(number<FmhaPipeline::kM0>{}, number<FmhaPipeline::kSubQKHeaddim>{}),
                 sequence<kPadSeqLenQ, kPadHeadDimQ>{});
         }();
         const auto k_dram = [&]() {
             const auto k_dram_naive = make_naive_tensor_view<address_space_enum::global>(
                 k_ptr,
                 make_tuple(kargs.seqlen_k, kargs.hdim_q),
                 make_tuple(kargs.stride_k, 1),
                 number<FmhaPipeline::kAlignmentK>{},
                 number<1>{});
  
             return pad_tensor_view(
                 k_dram_naive,
                 make_tuple(number<FmhaPipeline::kN0>{}, number<FmhaPipeline::kK0>{}),
                 sequence<kPadSeqLenK, kPadHeadDimQ>{});
         }();
         const auto v_dram = [&]() {
             const auto v_dram_naive = make_naive_tensor_view<address_space_enum::global>(
                 v_ptr,
                 make_tuple(kargs.seqlen_k, kargs.hdim_v),
                 make_tuple(kargs.stride_v, 1),
                 number<FmhaPipeline::kAlignmentV>{},
                 number<1>{});
  
             return pad_tensor_view(
                 v_dram_naive,
                 make_tuple(number<FmhaPipeline::kK1>{}, number<FmhaPipeline::kN1>{}),
                 sequence<kPadSeqLenK, kPadHeadDimV>{});
         }();
  
         auto q_dram_window = make_tile_window(
             q_dram,
             make_tuple(number<FmhaPipeline::kM0>{}, number<FmhaPipeline::kSubQKHeaddim>{}),
             {i_m0, 0});
  
         auto k_dram_window = make_tile_window(
             k_dram, make_tuple(number<FmhaPipeline::kN0>{}, number<FmhaPipeline::kK0>{}), {0, 0});
  
         auto v_dram_window =
             make_tile_window(v_dram,
                              make_tuple(number<FmhaPipeline::kK1>{}, number<FmhaPipeline::kN1>{}),
                              {0, i_n1});
  
         // lse
         auto lse_dram_window = [&, i_nhead_ = i_nhead]() {
             constexpr auto lse_dram_window_lengths = make_tuple(number<FmhaPipeline::kM0>{});
             if constexpr(kStoreLSE)
             {
                 LSEDataType* lse_ptr =
                     reinterpret_cast<LSEDataType*>(kargs.lse_ptr) +
                     static_cast<long_index_t>(i_nhead_) * kargs.nhead_stride_lse + batch_offset_lse;
  
                 const auto lse_dram = [&]() {
                     const auto lse_dram_naive = make_naive_tensor_view<address_space_enum::global>(
                         lse_ptr,
                         make_tuple(kargs.seqlen_q),
                         make_tuple(1),
                         number<1>{},
                         number<1>{});
  
                     return pad_tensor_view(
                         lse_dram_naive, lse_dram_window_lengths, sequence<kPadSeqLenQ>{});
                 }();
  
                 return make_tile_window(lse_dram, lse_dram_window_lengths, {i_m0});
             }
             else
             {
                 return make_null_tile_window(lse_dram_window_lengths);
             }
         }();
  
         FmhaMask mask = [&]() {
             if constexpr(kHasMask)
                 return ck_tile::make_generic_attention_mask_from_lr_window<FmhaMask>(
                     kargs.window_size_left,
                     kargs.window_size_right,
                     kargs.seqlen_q,
                     kargs.seqlen_k,
                     kargs.mask_type == GenericAttentionMaskEnum::MASK_FROM_TOP_LEFT);
             else
                 return FmhaMask{kargs.seqlen_q, kargs.seqlen_k};
         }();
  
         auto o_acc_tile = [&]() {
             return FmhaPipeline{}(q_dram_window,
                                   k_dram_window,
                                   v_dram_window,
                                   lse_dram_window,
                                   mask,
                                   kargs.scale_s,
                                   smem_ptr);
         }();
  
         // O DRAM and O DRAM window
         auto o_dram = [&]() {
             const auto o_dram_naive = make_naive_tensor_view<address_space_enum::global>(
                 o_ptr,
                 make_tuple(kargs.seqlen_q, kargs.hdim_v),
                 make_tuple(kargs.stride_o, 1),
                 number<FmhaPipeline::kAlignmentO>{},
                 number<1>{});
  
             return pad_tensor_view(
                 o_dram_naive,
                 make_tuple(number<FmhaPipeline::kM0>{}, number<FmhaPipeline::kN1>{}),
                 sequence<kPadSeqLenQ, kPadHeadDimV>{});
         }();
  
         auto o_dram_window =
             make_tile_window(o_dram,
                              make_tuple(number<FmhaPipeline::kM0>{}, number<FmhaPipeline::kN1>{}),
                              {i_m0, i_n1});
  
         EpiloguePipeline{}(o_dram_window, o_acc_tile, nullptr);
     }
 };
 } // namespace ck_tile