// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.

#pragma once

#include <iostream>
#include <sstream>

#include "ck/utility/reduction_operator.hpp"
#include "ck/tensor_operation/gpu/device/device_normalization.hpp"
#include "ck/tensor_operation/gpu/device/device_reduce.hpp"
#include "ck/tensor_operation/gpu/device/device_reduce_multiblock.hpp"
#include "ck/tensor_operation/gpu/device/device_reduce_common.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_layernorm.hpp"
#include "ck/tensor_operation/gpu/grid/gridwise_set_buffer_value.hpp"
#include "ck/host_utility/device_prop.hpp"
#include "ck/host_utility/kernel_launch.hpp"

namespace ck {
namespace tensor_operation {
namespace device {

// Y = LayerNorm(X, Beta, Gamma)
template <typename XDataType,
          typename GammaDataType,
          typename BetaDataType,
          typename AccDataType,
          typename YDataType,
          typename AccElementwiseOperation,
          index_t Rank,
          index_t NumReduceDim,
          index_t BlockSize,
          index_t MThreadClusterSize,
          index_t KThreadClusterSize,
          index_t MThreadSliceSize,
          index_t KThreadSliceSize,
          index_t XYSrcVectorDim,
          index_t XSrcVectorSize,
          index_t GammaSrcVectorSize,
          index_t BetaSrcVectorSize,
          index_t YDstVectorSize>
struct DeviceLayernorm : public DeviceNormalization2<XDataType,
                                                     GammaDataType,
                                                     BetaDataType,
                                                     AccDataType,
                                                     YDataType,
                                                     AccElementwiseOperation,
                                                     Rank,
                                                     NumReduceDim>
{
    static_assert(
        (KThreadSliceSize % GammaSrcVectorSize == 0),
        "Invalid thread slice sizes and/or gamma vector sizes configuration, please check!");

    static_assert(
        (KThreadSliceSize % BetaSrcVectorSize == 0),
        "Invalid thread slice sizes and/or beta vector sizes configuration, please check!");

    using PassThrough = tensor_operation::element_wise::PassThrough;

    // Used for freeloading of some handy functions from DeviceReduceMultiBlock
    using Reduction = DeviceReduceMultiBlock<XDataType,
                                             AccDataType,
                                             YDataType,
                                             Rank,
                                             NumReduceDim,
                                             reduce::Add,
                                             PassThrough,             // InElementwiseOperation
                                             AccElementwiseOperation, // AccElementwiseOperation
                                             InMemoryDataOperationEnum::Set,
                                             false, // PropagateNan
                                             false, // OutputIndex
                                             false, // HaveIndexInputIfOutputIndex
                                             BlockSize,
                                             MThreadClusterSize,
                                             KThreadClusterSize,
                                             MThreadSliceSize,
                                             KThreadSliceSize,
                                             XYSrcVectorDim,
                                             XSrcVectorSize,
                                             1>; // YDstVectorSize

    static auto MakeAffine1dDescriptor(const std::vector<index_t>& Lengths,
                                       const std::vector<index_t>& Strides,
                                       int blkGroupSize,
                                       int numBlockTileIteration)
    {
        const auto tupleLengths = make_tuple_from_array(Lengths, Number<NumReduceDim>{});
        const auto tupleStrides = make_tuple_from_array(Strides, Number<NumReduceDim>{});

        auto desc = make_naive_tensor_descriptor(tupleLengths, tupleStrides);

        auto grid_desc_k = transform_tensor_descriptor(
            desc,
            make_tuple(make_merge_transform(tupleLengths)),
            make_tuple(typename arithmetic_sequence_gen<0, NumReduceDim, 1>::type{}),
            make_tuple(Sequence<0>{}));

        const auto reduceTotalLength = grid_desc_k.GetLength(Number<0>{});
        const int reduceSizePerBlock = Reduction::K_BlockTileSize * numBlockTileIteration;

        const auto Pad_K = reduceSizePerBlock * blkGroupSize - reduceTotalLength;

        auto grid_desc_k_padded = transform_tensor_descriptor(
            grid_desc_k,
            make_tuple(make_right_pad_transform(reduceTotalLength, Pad_K)),
            make_tuple(Sequence<0>{}),
            make_tuple(Sequence<0>{}));

        return (grid_desc_k_padded);
    };

    using GridDesc_M_K = decltype(Reduction::MakeSrc2dDescriptor({1}, {1}, 1, 1));
    using GridDesc_K   = decltype(MakeAffine1dDescriptor({1}, {1}, 1, 1));

    using GridwiseReduceLayernormGeneric = GridwiseLayernorm_mk_to_mk<XDataType,
                                                                      GammaDataType,
                                                                      BetaDataType,
                                                                      YDataType,
                                                                      AccDataType,
                                                                      AccElementwiseOperation,
                                                                      GridDesc_M_K,
                                                                      GridDesc_K,
                                                                      BlockSize,
                                                                      MThreadClusterSize,
                                                                      KThreadClusterSize,
                                                                      MThreadSliceSize,
                                                                      KThreadSliceSize,
                                                                      XYSrcVectorDim,
                                                                      XSrcVectorSize,
                                                                      GammaSrcVectorSize,
                                                                      BetaSrcVectorSize,
                                                                      XYSrcVectorDim,
                                                                      YDstVectorSize,
                                                                      false>;

    using GridwiseReduceLayernormSweepOnce = GridwiseLayernorm_mk_to_mk<XDataType,
                                                                        GammaDataType,
                                                                        BetaDataType,
                                                                        YDataType,
                                                                        AccDataType,
                                                                        AccElementwiseOperation,
                                                                        GridDesc_M_K,
                                                                        GridDesc_K,
                                                                        BlockSize,
                                                                        MThreadClusterSize,
                                                                        KThreadClusterSize,
                                                                        MThreadSliceSize,
                                                                        KThreadSliceSize,
                                                                        XYSrcVectorDim,
                                                                        XSrcVectorSize,
                                                                        GammaSrcVectorSize,
                                                                        BetaSrcVectorSize,
                                                                        XYSrcVectorDim,
                                                                        YDstVectorSize,
                                                                        true>;

    struct Argument : public Reduction::Argument
    {
        Argument(const std::vector<index_t> lengths,
                 const std::vector<index_t> xStrides,
                 const std::vector<index_t> gammaStrides,
                 const std::vector<index_t> betaStrides,
                 const std::vector<index_t> reduceDims,
                 AccElementwiseOperation acc_elementwise_op,
                 AccDataType epsilon,
                 const XDataType* p_x,
                 const GammaDataType* p_gamma,
                 const BetaDataType* p_beta,
                 YDataType* p_y)
            : Reduction::Argument(lengths,
                                  xStrides,
                                  {},
                                  {},
                                  reduceDims,
                                  0.0f, // alpha
                                  0.0f, // beta
                                  p_x,
                                  nullptr,
                                  p_y,
                                  nullptr,
                                  acc_elementwise_op,
                                  PassThrough{}),
              epsilon_(epsilon),
              p_gamma_(p_gamma),
              p_beta_(p_beta),
              gammaStrides_(gammaStrides),
              betaStrides_(betaStrides)
        {
            reduceLength_.resize(NumReduceDim);

            for(int i = 0; i < NumReduceDim; ++i)
            {
                reduceLength_[i] = lengths[reduceDims[i]];
            }
        }

        AccDataType epsilon_;
        const GammaDataType* p_gamma_;
        const BetaDataType* p_beta_;
        std::vector<index_t> reduceLength_;
        std::vector<index_t> gammaStrides_;
        std::vector<index_t> betaStrides_;
    };

    struct Invoker : public BaseInvoker
    {
        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
        {
            const auto x_grid_desc_m_k = Reduction::MakeSrc2dDescriptor(
                arg.inLengths_, arg.inStrides_, arg.blkGroupSize, arg.numBlockTileIteration);
            const auto gamma_grid_desc_k = MakeAffine1dDescriptor(
                arg.reduceLength_, arg.gammaStrides_, arg.blkGroupSize, arg.numBlockTileIteration);
            const auto beta_grid_desc_k = MakeAffine1dDescriptor(
                arg.reduceLength_, arg.betaStrides_, arg.blkGroupSize, arg.numBlockTileIteration);
            const auto y_grid_desc_m_k = Reduction::MakeSrc2dDescriptor(
                arg.inLengths_, arg.inStrides_, arg.blkGroupSize, arg.numBlockTileIteration);

            bool sweep_once =
                x_grid_desc_m_k.GetLength(Number<1>{}) <= KThreadClusterSize * KThreadSliceSize;

            const auto kernel_main = sweep_once ? kernel_layernorm<GridwiseReduceLayernormSweepOnce,
                                                                   XDataType,
                                                                   GammaDataType,
                                                                   BetaDataType,
                                                                   YDataType,
                                                                   AccDataType,
                                                                   AccElementwiseOperation,
                                                                   GridDesc_M_K,
                                                                   GridDesc_K>
                                                : kernel_layernorm<GridwiseReduceLayernormGeneric,
                                                                   XDataType,
                                                                   GammaDataType,
                                                                   BetaDataType,
                                                                   YDataType,
                                                                   AccDataType,
                                                                   AccElementwiseOperation,
                                                                   GridDesc_M_K,
                                                                   GridDesc_K>;

            float avg_time = 0;
            avg_time += launch_and_time_kernel(stream_config,
                                               kernel_main,
                                               dim3(arg.gridSize),
                                               dim3(BlockSize),
                                               0,
                                               x_grid_desc_m_k,
                                               gamma_grid_desc_k,
                                               beta_grid_desc_k,
                                               y_grid_desc_m_k,
                                               arg.numBlockTileIteration,
                                               arg.epsilon_,
                                               arg.in_dev_,
                                               arg.p_gamma_,
                                               arg.p_beta_,
                                               arg.out_dev_,
                                               arg.acc_elementwise_op_);

            return (avg_time);
        };

        float Run(const BaseArgument* p_arg,
                  const StreamConfig& stream_config = StreamConfig{}) override
        {
            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
        };
    };

    bool IsSupportedArgument(const BaseArgument* p_arg) override
    {
        const Argument* p_arg_ = dynamic_cast<const Argument*>(p_arg);

        if(!Reduction::IsSupportedArgument(p_arg_))
        {
            return false;
        }

        if(p_arg_->inLengths_[Rank - 1] % YDstVectorSize != 0)
        {
            return false;
        }

        if(p_arg_->gammaStrides_.size() != NumReduceDim ||
           p_arg_->betaStrides_.size() != NumReduceDim)
            return false;

        auto IsScalarPerVectorValid = [](bool isLastDimensionCoalesced, int scalarPerVector) {
            bool ret = true;

            if(!isLastDimensionCoalesced)
                ret = scalarPerVector == 1;
            else
                ret = KThreadSliceSize % scalarPerVector == 0;

            return ret;
        };

        if(!IsScalarPerVectorValid(p_arg_->gammaStrides_.back() == 1, GammaSrcVectorSize))
            return false;

        if(!IsScalarPerVectorValid(p_arg_->betaStrides_.back() == 1, BetaSrcVectorSize))
            return false;

        return true;
    };

    std::unique_ptr<BaseArgument>
    MakeArgumentPointer(const std::vector<index_t> lengths,
                        const std::vector<index_t> xStrides,
                        const std::vector<index_t> gammaStrides,
                        const std::vector<index_t> betaStrides,
                        const std::vector<index_t> reduceDims,
                        AccDataType epsilon,
                        const void* p_x,
                        const void* p_gamma,
                        const void* p_beta,
                        void* p_y,
                        AccElementwiseOperation acc_elementwise_op) override
    {
        return std::make_unique<Argument>(lengths,
                                          xStrides,
                                          gammaStrides,
                                          betaStrides,
                                          reduceDims,
                                          acc_elementwise_op,
                                          epsilon,
                                          static_cast<const XDataType*>(p_x),
                                          static_cast<const GammaDataType*>(p_gamma),
                                          static_cast<const BetaDataType*>(p_beta),
                                          static_cast<YDataType*>(p_y));
    };

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

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

        // clang-format off
        str << "DeviceLayernorm<" << BlockSize << ",";
        str << "M_C" << MThreadClusterSize << "_S" << MThreadSliceSize << ",";
        str << "K_C" << KThreadClusterSize << "_S" << KThreadSliceSize << ",";
        str << "XYSrcVectorDim_" << XYSrcVectorDim  << ",";
        str << "VectorSize_X" << XSrcVectorSize << "_Gamma" << GammaSrcVectorSize << "_Beta" << BetaSrcVectorSize << "_Y" << YDstVectorSize << ">";
        // clang-format on

        return str.str();
    }
};

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