// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT

#pragma once

#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/block/block_gemm_asmem_breg_creg_v1_default_policy.hpp"

namespace ck_tile {

// A is block window on shared memory
// B is block distributed tensor
// C is block distributed tensor
template <typename Problem_, typename Policy_ = BlockGemmASmemBRegCRegV1DefaultPolicy>
struct BlockGemmASmemBRegCRegV1
{
    using Problem        = remove_cvref_t<Problem_>;
    using Policy         = remove_cvref_t<Policy_>;
    using ADataType      = remove_cvref_t<typename Problem::ADataType>;
    using BDataType      = remove_cvref_t<typename Problem::BDataType>;
    using CDataType      = remove_cvref_t<typename Problem::CDataType>;
    using BlockGemmShape = remove_cvref_t<typename Problem::BlockGemmShape>;

    static constexpr index_t kBlockSize = Problem::kBlockSize;

    // C += A * B
    template <typename CBlockTensor, typename ABlockWindowTmp, typename BBlockTensorTmp>
    CK_TILE_DEVICE void operator()(CBlockTensor& c_block_tensor,
                                   const ABlockWindowTmp& a_block_window_tmp,
                                   const BBlockTensorTmp& b_block_tensor_tmp) const
    {
        static_assert(
            std::is_same_v<ADataType, remove_cv_t<typename ABlockWindowTmp::DataType>> &&
                std::is_same_v<BDataType, remove_cv_t<typename BBlockTensorTmp::DataType>> &&
                std::is_same_v<CDataType, remove_cv_t<typename CBlockTensor::DataType>>,
            "wrong!");

        constexpr index_t MPerBlock = ABlockWindowTmp{}.get_window_lengths()[number<0>{}];
        constexpr index_t NPerBlock = BBlockTensorTmp{}.get_lengths()[number<0>{}];
        constexpr index_t KPerBlock = ABlockWindowTmp{}.get_window_lengths()[number<1>{}];

        static_assert(MPerBlock == BlockGemmShape::kM && NPerBlock == BlockGemmShape::kN &&
                          KPerBlock == BlockGemmShape::kK,
                      "wrong!");

        constexpr auto config = Policy::template GetWarpGemmMWarpNWarp<Problem>();

        using WG = remove_cvref_t<decltype(config.template at<0>())>;

        constexpr index_t MWarp = config.template at<1>();
        constexpr index_t NWarp = config.template at<2>();

        constexpr index_t MIterPerWarp = MPerBlock / (MWarp * WG::kM);
        constexpr index_t NIterPerWarp = NPerBlock / (NWarp * WG::kN);
        constexpr index_t KIterPerWarp = KPerBlock / WG::kK;

        constexpr index_t MPerBlockPerIter = MPerBlock / MIterPerWarp;
        constexpr index_t KPerBlockPerIter = KPerBlock / KIterPerWarp;

        const index_t iMWarp = get_warp_id() / NWarp;

        constexpr auto b_block_outer_dstr_encoding =
            tile_distribution_encoding<sequence<MWarp>,
                                       tuple<sequence<NIterPerWarp, NWarp>, sequence<KIterPerWarp>>,
                                       tuple<sequence<0, 1>>,
                                       tuple<sequence<0, 1>>,
                                       sequence<1, 2>,
                                       sequence<0, 0>>{};

        constexpr auto c_block_outer_dstr_encoding = tile_distribution_encoding<
            sequence<>,
            tuple<sequence<MIterPerWarp, MWarp>, sequence<NIterPerWarp, NWarp>>,
            tuple<sequence<1, 2>>,
            tuple<sequence<1, 1>>,
            sequence<1, 2>,
            sequence<0, 0>>{};

        constexpr auto b_block_dstr_encode = detail::make_embed_tile_distribution_encoding(
            b_block_outer_dstr_encoding, typename WG::BWarpDstrEncoding{});

        constexpr auto c_block_dstr_encode = detail::make_embed_tile_distribution_encoding(
            c_block_outer_dstr_encoding, typename WG::CWarpDstrEncoding{});

        constexpr auto b_block_dstr = make_static_tile_distribution(b_block_dstr_encode);

        // constrcut from B-block-tensor from B-Block-tensor-tmp
        // FIXME: need method to check b_block_tensor and b_block_tensor_tmp have equivalent
        // distribution
        auto b_block_tensor =
            make_static_distributed_tensor<typename BBlockTensorTmp::DataType>(b_block_dstr);

        b_block_tensor.get_thread_buffer() = b_block_tensor_tmp.get_thread_buffer();

        // construct A-warp-window
        auto a_warp_window_tmp = make_tile_window(
            a_block_window_tmp.get_bottom_tensor_view(),
            make_tuple(number<WG::kM>{}, number<WG::kK>{}),
            a_block_window_tmp.get_window_origin() + multi_index<2>{iMWarp * WG::kM, 0},
            make_static_tile_distribution(typename WG::AWarpDstrEncoding{}));

#if 0 // FIXME: using array will cause register spill
        array<array<decltype(b_warp_window_tmp), KIterPerWarp>, NIterPerWarp> b_warp_windows{
            {b_warp_window_tmp}};

        for(index_t nIter = 0; nIter < NIterPerWarp; nIter++)
        {
            for(index_t kIter = 0; kIter < KIterPerWarp; kIter++)
            {
                move_tile_window(b_warp_windows(nIter)(kIter),
                                 {nIter * NPerBlockPerIter, kIter * KPerBlockPerIter});
            }
        }
#else
        statically_indexed_array<
            statically_indexed_array<decltype(a_warp_window_tmp), KIterPerWarp>,
            MIterPerWarp>
            a_warp_windows;

        static_ford<sequence<MIterPerWarp, KIterPerWarp>>{}([&](auto mk) {
            constexpr auto mIter         = number<mk[number<0>{}]>{};
            constexpr auto kIter         = number<mk[number<1>{}]>{};
            a_warp_windows(mIter)(kIter) = a_warp_window_tmp;

            move_tile_window(a_warp_windows(mIter)(kIter),
                             {mIter * MPerBlockPerIter, kIter * KPerBlockPerIter});
        });
#endif

        // check C-block-distribution
        static_assert(
            std::is_same_v<remove_cvref_t<decltype(c_block_dstr_encode)>,
                           remove_cvref_t<decltype(CBlockTensor::get_tile_distribution()
                                                       .get_static_tile_distribution_encoding())>>,
            "wrong!");

        using BWarpDstr = typename WG::BWarpDstr;
        using CWarpDstr = typename WG::CWarpDstr;

        using BWarpTensor = typename WG::BWarpTensor;
        using CWarpTensor = typename WG::CWarpTensor;

        constexpr auto b_warp_y_lengths =
            to_sequence(BWarpDstr{}.get_ys_to_d_descriptor().get_lengths());
        constexpr auto c_warp_y_lengths =
            to_sequence(CWarpDstr{}.get_ys_to_d_descriptor().get_lengths());

        constexpr auto b_warp_y_index_zeros = uniform_sequence_gen_t<BWarpDstr::NDimY, 0>{};
        constexpr auto c_warp_y_index_zeros = uniform_sequence_gen_t<CWarpDstr::NDimY, 0>{};

        // hot loop:
        static_ford<sequence<KIterPerWarp, MIterPerWarp>>{}([&](auto km) {
            constexpr auto kIter = number<km[number<0>{}]>{};
            constexpr auto mIter = number<km[number<1>{}]>{};
            // read A warp tensor from A Block window
            const auto a_warp_tensor = load_tile(a_warp_windows(mIter)(kIter));
            static_for<0, NIterPerWarp, 1>{}([&](auto nIter) {
                // read B warp tensor from B block tensor
                BWarpTensor b_warp_tensor;

                b_warp_tensor.get_thread_buffer() = b_block_tensor.get_y_sliced_thread_data(
                    merge_sequences(sequence<nIter, kIter>{}, b_warp_y_index_zeros),
                    merge_sequences(sequence<1, 1>{}, b_warp_y_lengths));

                // read C warp tensor from C block tensor
                CWarpTensor c_warp_tensor;

                c_warp_tensor.get_thread_buffer() = c_block_tensor.get_y_sliced_thread_data(
                    merge_sequences(sequence<mIter, nIter>{}, c_warp_y_index_zeros),
                    merge_sequences(sequence<1, 1>{}, c_warp_y_lengths));

                // warp GEMM
                WG{}(c_warp_tensor, a_warp_tensor, b_warp_tensor);

                // write C warp tensor into C block tensor
                c_block_tensor.set_y_sliced_thread_data(
                    merge_sequences(sequence<mIter, nIter>{}, c_warp_y_index_zeros),
                    merge_sequences(sequence<1, 1>{}, c_warp_y_lengths),
                    c_warp_tensor.get_thread_buffer());
            });
        });
    }

    CK_TILE_DEVICE static constexpr auto MakeCBlockTile()
    {
        constexpr index_t MPerBlock = BlockGemmShape::kM;
        constexpr index_t NPerBlock = BlockGemmShape::kN;

        constexpr auto config = Policy::template GetWarpGemmMWarpNWarp<Problem>();

        using WG = remove_cvref_t<decltype(config.template at<0>())>;

        constexpr index_t MWarp = config.template at<1>();
        constexpr index_t NWarp = config.template at<2>();

        constexpr index_t MIterPerWarp = MPerBlock / (MWarp * WG::kM);
        constexpr index_t NIterPerWarp = NPerBlock / (NWarp * WG::kN);
        // constexpr index_t KIterPerWarp = KPerBlock / WG::kK;

        constexpr auto c_block_outer_dstr_encoding = tile_distribution_encoding<
            sequence<>,
            tuple<sequence<MIterPerWarp, MWarp>, sequence<NIterPerWarp, NWarp>>,
            tuple<sequence<1, 2>>,
            tuple<sequence<1, 1>>,
            sequence<1, 2>,
            sequence<0, 0>>{};

        constexpr auto c_block_dstr_encode = detail::make_embed_tile_distribution_encoding(
            c_block_outer_dstr_encoding, typename WG::CWarpDstrEncoding{});
        constexpr auto c_block_dstr = make_static_tile_distribution(c_block_dstr_encode);
        auto c_block_tensor         = make_static_distributed_tensor<CDataType>(c_block_dstr);
        return c_block_tensor;
    }

    // C = A * B
    template <typename ABlockWindowTmp, typename BBlockTensorTmp>
    CK_TILE_DEVICE auto operator()(const ABlockWindowTmp& a_block_window_tmp,
                                   const BBlockTensorTmp& b_block_tensor_tmp) const
    {
        auto c_block_tensor = MakeCBlockTile();
        operator()(c_block_tensor, a_block_window_tmp, b_block_tensor_tmp);
        return c_block_tensor;
    }
};

} // namespace ck_tile
