// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.

#pragma once

#include <iostream>

#include "ck/ck.hpp"
#include "ck/utility/reduction_enums.hpp"
#include "ck/utility/reduction_functions_accumulate.hpp"
#include "ck/tensor_operation/gpu/device/reduction_operator_mapping.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_pool2d_fwd_nhwc_nhwc.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_index_pool_bwd_impl.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"

#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/device_memory.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/host_tensor_generator.hpp"
#include "ck/library/utility/literals.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_pool_fwd.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_maxpool_bwd.hpp"

template <typename InDataType,
          typename OutDataType,
          typename IndexDataType,
          typename ComputeDataType,
          typename DInDataType,
          typename DOutDataType,
          typename InLayout,
          typename OutLayout,
          bool PropagateNan>
bool maxpool_bwd_test(bool do_verification,
                      bool time_kernel,
                      ck::index_t N,
                      ck::index_t C,
                      ck::index_t Y,
                      ck::index_t X,
                      ck::index_t Hi,
                      ck::index_t Wi,
                      ck::index_t window_stride_h,
                      ck::index_t window_stride_w,
                      ck::index_t in_left_pad_h,
                      ck::index_t in_left_pad_w,
                      ck::index_t in_right_pad_h,
                      ck::index_t in_right_pad_w)
{
    using PassThrough = ck::tensor_operation::element_wise::PassThrough;

    using DevicePoolFwdInstance =
        ck::tensor_operation::device::DevicePool2dFwd_Input_N_Hi_Wi_C_Output_N_Ho_Wo_C<
            InDataType,      // InDataType
            OutDataType,     // OutDataType
            IndexDataType,   // IndexDataType
            ComputeDataType, // ComputeDataType
            ck::ReduceTensorOp::MAX,
            true, // OutputIndex
            64,   // BlockSize
            64,   // ReduceMThreadClusterSize
            1,    // ReduceKThreadClusterSize
            4,    // ReduceMThreadSliceSize
            1,    // ReduceKThreadSliceSize
            1>;   // InSrcOutDstVectorSize

    using DeviceMaxPoolBwdInstance = ck::tensor_operation::device::
        DeviceIndexPoolBwdImpl<DOutDataType, IndexDataType, DInDataType, 4>;

    const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - Y) / window_stride_h + 1;
    const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - X) / window_stride_w + 1;

    const std::vector<ck::index_t> window_spatial_lengths{Y, X};
    const std::vector<ck::index_t> window_strides{window_stride_h, window_stride_w};
    const std::vector<ck::index_t> input_left_pads{in_left_pad_h, in_left_pad_w};
    const std::vector<ck::index_t> input_right_pads{in_right_pad_h, in_right_pad_w};

    // tensor layout
    auto f_host_tensor_descriptor =
        [](std::size_t N_, std::size_t C_, std::size_t H, std::size_t W, auto layout) {
            using namespace ck::literals;

            if constexpr(ck::is_same<decltype(layout), ck::tensor_layout::convolution::NCHW>::value)
            {
                return HostTensorDescriptor({N_, C_, H, W}, {C_ * H * W, H * W, W, 1_uz});
            }
            else if constexpr(ck::is_same<decltype(layout),
                                          ck::tensor_layout::convolution::NHWC>::value)
            {
                return HostTensorDescriptor({N_, C_, H, W}, {C_ * H * W, 1_uz, W * C_, C_});
            }
        };

    // in
    Tensor<InDataType> in_n_c_hi_wi(f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{}));

    // out
    Tensor<OutDataType> out_n_c_ho_wo_host(f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));
    Tensor<OutDataType> out_n_c_ho_wo_device(f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));

    // indices
    Tensor<IndexDataType> indices_n_c_ho_wo_device(
        f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));
    Tensor<IndexDataType> indices_n_c_ho_wo_host(
        f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));

    // dout
    Tensor<DOutDataType> dout_n_c_ho_wo(f_host_tensor_descriptor(N, C, Ho, Wo, OutLayout{}));

    // din
    Tensor<DInDataType> din_n_c_hi_wi_host(f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{}));
    Tensor<DInDataType> din_n_c_hi_wi_device(f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{}));

    std::cout << "in_n_c_hi_wi: " << in_n_c_hi_wi.mDesc << std::endl;
    std::cout << "out_n_c_ho_wo: " << out_n_c_ho_wo_host.mDesc << std::endl;
    std::cout << "indices_n_c_ho_wo: " << indices_n_c_ho_wo_host.mDesc << std::endl;
    std::cout << "dout_n_c_ho_wo: " << dout_n_c_ho_wo.mDesc << std::endl;
    std::cout << "din_n_c_hi_wi: " << din_n_c_hi_wi_host.mDesc << std::endl;

    in_n_c_hi_wi.GenerateTensorValue(GeneratorTensor_3<InDataType>{-1.0, 1.0});
    dout_n_c_ho_wo.GenerateTensorValue(GeneratorTensor_3<DOutDataType>{-1.0, 1.0});

    DeviceMem in_device_buf(sizeof(InDataType) * in_n_c_hi_wi.mDesc.GetElementSpaceSize());
    DeviceMem out_device_buf(sizeof(OutDataType) *
                             out_n_c_ho_wo_device.mDesc.GetElementSpaceSize());
    DeviceMem indices_device_buf(sizeof(IndexDataType) *
                                 indices_n_c_ho_wo_device.mDesc.GetElementSpaceSize());
    DeviceMem dout_device_buf(sizeof(DOutDataType) * dout_n_c_ho_wo.mDesc.GetElementSpaceSize());
    DeviceMem din_device_buf(sizeof(DInDataType) *
                             din_n_c_hi_wi_device.mDesc.GetElementSpaceSize());

    in_device_buf.ToDevice(in_n_c_hi_wi.mData.data());
    dout_device_buf.ToDevice(dout_n_c_ho_wo.mData.data());
    din_device_buf.SetZero();

    auto pool_fwd              = DevicePoolFwdInstance{};
    auto pool_fwd_invoker_ptr  = pool_fwd.MakeInvokerPointer();
    auto pool_fwd_argument_ptr = pool_fwd.MakeArgumentPointer(
        static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
        static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
        static_cast<IndexDataType*>(indices_device_buf.GetDeviceBuffer()),
        {N, C, Hi, Wi},
        window_spatial_lengths,
        {N, C, Ho, Wo},
        {C * Hi * Wi, 1, Wi * C, C},
        {C * Ho * Wo, 1, Wo * C, C},
        {C * Ho * Wo, 1, Wo * C, C},
        window_strides,
        input_left_pads,
        input_right_pads,
        {2, 3});

    if(!pool_fwd.IsSupportedArgument(pool_fwd_argument_ptr.get()))
    {
        throw std::runtime_error("wrong! pool_fwd with the specified compilation parameters does "
                                 "not support this problem");
    }

    float ave_time_fwd =
        pool_fwd_invoker_ptr->Run(pool_fwd_argument_ptr.get(), StreamConfig{nullptr, time_kernel});

    auto pool_bwd              = DeviceMaxPoolBwdInstance{};
    auto pool_bwd_invoker_ptr  = pool_bwd.MakeInvokerPointer();
    auto pool_bwd_argument_ptr = pool_bwd.MakeArgumentPointer(
        static_cast<DOutDataType*>(dout_device_buf.GetDeviceBuffer()),
        static_cast<IndexDataType*>(indices_device_buf.GetDeviceBuffer()),
        static_cast<DInDataType*>(din_device_buf.GetDeviceBuffer()),
        dout_n_c_ho_wo.mDesc.GetElementSpaceSize(),
        din_n_c_hi_wi_device.mDesc.GetElementSpaceSize(),
        window_spatial_lengths,
        window_strides);

    if(!pool_bwd.IsSupportedArgument(pool_bwd_argument_ptr.get()))
    {
        throw std::runtime_error("wrong! pool_bwd with the specified compilation parameters does "
                                 "not support this problem");
    }

    size_t pool_bwd_workspace_sz = pool_bwd.GetWorkSpaceSize(pool_bwd_argument_ptr.get());
    DeviceMem pool_bwd_workspace_device_buf(pool_bwd_workspace_sz);
    pool_bwd_workspace_device_buf.SetZero();
    pool_bwd.SetWorkSpacePointer(pool_bwd_argument_ptr.get(),
                                 pool_bwd_workspace_device_buf.GetDeviceBuffer());

    float ave_time_bwd =
        pool_bwd_invoker_ptr->Run(pool_bwd_argument_ptr.get(), StreamConfig{nullptr, time_kernel});

    std::cout << "Pool fwd perf: " << ave_time_fwd << " ms" << std::endl;
    std::cout << "Pool bwd perf: " << ave_time_bwd << " ms" << std::endl;

    bool pass = true;

    if(do_verification)
    {
        using ReferencePoolingFwdInstance =
            ck::tensor_operation::host::ReferencePoolingFwd<4,
                                                            2,
                                                            InDataType,
                                                            OutDataType,
                                                            ComputeDataType,
                                                            IndexDataType,
                                                            ck::ReduceTensorOp::MAX,
                                                            PropagateNan,
                                                            true>;

        auto ref_pooling_fwd          = ReferencePoolingFwdInstance{};
        auto ref_pooling_fwd_invoker  = ref_pooling_fwd.MakeInvoker();
        auto ref_pooling_fwd_argument = ref_pooling_fwd.MakeArgument(in_n_c_hi_wi,
                                                                     out_n_c_ho_wo_host,
                                                                     indices_n_c_ho_wo_host,
                                                                     window_spatial_lengths,
                                                                     window_strides,
                                                                     input_left_pads,
                                                                     input_right_pads);
        ref_pooling_fwd_invoker.Run(ref_pooling_fwd_argument);

        using ReferencePoolingBwdInstance = ck::tensor_operation::host::
            ReferenceMaxPoolBwd<DOutDataType, IndexDataType, float, DInDataType, PassThrough>;

        auto ref_pooling_bwd          = ReferencePoolingBwdInstance{};
        auto ref_pooling_bwd_invoker  = ref_pooling_bwd.MakeInvoker();
        auto ref_pooling_bwd_argument = ref_pooling_bwd.MakeArgument(
            dout_n_c_ho_wo, indices_n_c_ho_wo_host, din_n_c_hi_wi_host, PassThrough{});

        ref_pooling_bwd_invoker.Run(ref_pooling_bwd_argument);

        out_device_buf.FromDevice(out_n_c_ho_wo_device.mData.data());
        indices_device_buf.FromDevice(indices_n_c_ho_wo_device.mData.data());
        din_device_buf.FromDevice(din_n_c_hi_wi_device.mData.data());

        pass = pass && ck::utils::check_err(out_n_c_ho_wo_device, out_n_c_ho_wo_host);
        pass = pass && ck::utils::check_err(indices_n_c_ho_wo_device, indices_n_c_ho_wo_host);
        pass = pass && ck::utils::check_err(din_n_c_hi_wi_device, din_n_c_hi_wi_host);
    }

    return (pass);
};
