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

#include "convnd_bwd_weight_common.hpp"

#include "ck/tensor_operation/gpu/device/impl/device_convnd_bwd_weight_nwc_kxc_nwk_dl.hpp"

using InDataType  = ck::bhalf_t;
using WeiDataType = ck::bhalf_t;
using OutDataType = ck::bhalf_t;
using AccDataType = float;

template <ck::index_t... Is>
using S = ck::Sequence<Is...>;

using InElementOp  = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;

static constexpr auto ConvBwdWeightDefault =
    ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;

template <ck::index_t NDimSpatial>
using DeviceConvndBwdWeightInstance =
    ck::tensor_operation::device::DeviceConvNdBwdWeightNwcKxcNwk_Dl<
        NDimSpatial,    // NDimSpatial
        InDataType,     // InDataType
        WeiDataType,    // WeiDataType
        OutDataType,    // OutDataType
        AccDataType,    // AccDataType
        InElementOp,    // InElementwiseOperation
        WeiElementOp,   // WeiElementwiseOperation
        OutElementOp,   // OutElementwiseOperation
        ConvBwdWeightDefault,   // ConvBackwardWeightSpecialization
        256,    // BlockSize
        128,    // MPerBlock
        128,    // NPerBlock
        16,     // K0PerBlock
        2,      // K1
        4,      // M1PerThread
        4,      // N1PerThread
        1,      // KPerThread
        S<8, 2>,    // M1N1ThreadClusterM1Xs
        S<8, 2>,    // M1N1ThreadClusterN1Xs
        S<8, 1, 1, 2>,      // ABlockTransferThreadSliceLengths_K0_M0_M1_K1
        S<2, 1, 128, 1>,    // ABlockTransferThreadClusterLengths_K0_M0_M1_K1
        S<1, 2, 0, 3>,      // ABlockTransferThreadClusterArrangeOrder
        S<1, 2, 0, 3>,      // ABlockTransferSrcAccessOrder
        S<4, 1, 1, 2>,      // ABlockTransferSrcVectorTensorLengths_K0_M0_M1_K1
        S<1, 2, 0, 3>,      // ABlockTransferSrcVectorTensorContiguousDimOrder
        S<1, 1, 1, 2>,      // ABlockTransferDstVectorTensorLengths_K0_M0_M1_K1
        S<1, 1, 8, 2>,      // BBlockTransferThreadSliceLengths_K0_N0_N1_K1
        S<16, 1, 16, 1>,    // BBlockTransferThreadClusterLengths_K0_N0_N1_K1
        S<0, 3, 1, 2>,      // BBlockTransferThreadClusterArrangeOrder
        S<0, 3, 1, 2>,      // BBlockTransferSrcAccessOrder
        S<1, 1, 8, 1>,      // BBlockTransferSrcVectorTensorLengths_K0_N0_N1_K1
        S<0, 3, 1, 2>,      // BBlockTransferSrcVectorTensorContiguousDimOrder
        S<1, 1, 1, 2>,      // BBlockTransferDstVectorTensorLengths_K0_N0_N1_K1
        S<0, 1, 2, 3, 4, 5>,    // CThreadTransferSrcDstAccessOrder
        5,      // CThreadTransferSrcDstVectorDim
        4>;     // CThreadTransferDstScalarPerVector

int main(int argc, char* argv[])
{
    namespace ctc = ck::tensor_layout::convolution;

    print_helper_msg();

    bool do_verification = true;
    int init_method      = 1;
    bool time_kernel     = false;

    ck::utils::conv::ConvParam conv_param{
        2, 1, 32, 256, 1024, {3, 3}, {14, 14}, {2, 2}, {1, 1}, {1, 1}, {1, 1}};

    ck::index_t split_k = 1;

    if(argc == 1)
    {
        // use default
    }
    else if(argc == 4)
    {
        do_verification = std::stoi(argv[1]);
        init_method     = std::stoi(argv[2]);
        time_kernel     = std::stoi(argv[3]);
    }
    else
    {
        do_verification                   = std::stoi(argv[1]);
        init_method                       = std::stoi(argv[2]);
        time_kernel                       = std::stoi(argv[3]);
        const ck::index_t num_dim_spatial = std::stoi(argv[4]);

        conv_param = ck::utils::conv::parse_conv_param(num_dim_spatial, 5, argv);
    }

    const auto in_element_op  = InElementOp{};
    const auto wei_element_op = WeiElementOp{};
    const auto out_element_op = OutElementOp{};

    if(conv_param.num_dim_spatial_ == 1)
    {
        using InLayout  = ctc::GNWC;
        using WeiLayout = ctc::GKXC;
        using OutLayout = ctc::GNWK;

        const auto in_g_n_c_wis_desc =
            ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<InLayout>(
                conv_param);

        const auto wei_g_k_c_xs_desc =
            ck::utils::conv::make_weight_host_tensor_descriptor_g_k_c_xs_packed<WeiLayout>(
                conv_param);

        const auto out_g_n_k_wos_desc =
            ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(
                conv_param);

        return run_conv_bwd_weight<1,
                                   InDataType,
                                   WeiDataType,
                                   OutDataType,
                                   InElementOp,
                                   WeiElementOp,
                                   OutElementOp,
                                   DeviceConvndBwdWeightInstance<1>>(do_verification,
                                                                     init_method,
                                                                     time_kernel,
                                                                     conv_param,
                                                                     in_g_n_c_wis_desc,
                                                                     wei_g_k_c_xs_desc,
                                                                     out_g_n_k_wos_desc,
                                                                     in_element_op,
                                                                     wei_element_op,
                                                                     out_element_op,
                                                                     split_k);
    }
    else if(conv_param.num_dim_spatial_ == 2)
    {
        using InLayout  = ctc::GNHWC;
        using WeiLayout = ctc::GKYXC;
        using OutLayout = ctc::GNHWK;

        const auto in_g_n_c_wis_desc =
            ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<InLayout>(
                conv_param);

        const auto wei_g_k_c_xs_desc =
            ck::utils::conv::make_weight_host_tensor_descriptor_g_k_c_xs_packed<WeiLayout>(
                conv_param);

        const auto out_g_n_k_wos_desc =
            ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(
                conv_param);

        return run_conv_bwd_weight<2,
                                   InDataType,
                                   WeiDataType,
                                   OutDataType,
                                   InElementOp,
                                   WeiElementOp,
                                   OutElementOp,
                                   DeviceConvndBwdWeightInstance<2>>(do_verification,
                                                                     init_method,
                                                                     time_kernel,
                                                                     conv_param,
                                                                     in_g_n_c_wis_desc,
                                                                     wei_g_k_c_xs_desc,
                                                                     out_g_n_k_wos_desc,
                                                                     in_element_op,
                                                                     wei_element_op,
                                                                     out_element_op,
                                                                     split_k);
    }
    else if(conv_param.num_dim_spatial_ == 3)
    {
        using InLayout  = ctc::GNDHWC;
        using WeiLayout = ctc::GKZYXC;
        using OutLayout = ctc::GNDHWK;

        const auto in_g_n_c_wis_desc =
            ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<InLayout>(
                conv_param);

        const auto wei_g_k_c_xs_desc =
            ck::utils::conv::make_weight_host_tensor_descriptor_g_k_c_xs_packed<WeiLayout>(
                conv_param);

        const auto out_g_n_k_wos_desc =
            ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(
                conv_param);

        return run_conv_bwd_weight<3,
                                   InDataType,
                                   WeiDataType,
                                   OutDataType,
                                   InElementOp,
                                   WeiElementOp,
                                   OutElementOp,
                                   DeviceConvndBwdWeightInstance<3>>(do_verification,
                                                                     init_method,
                                                                     time_kernel,
                                                                     conv_param,
                                                                     in_g_n_c_wis_desc,
                                                                     wei_g_k_c_xs_desc,
                                                                     out_g_n_k_wos_desc,
                                                                     in_element_op,
                                                                     wei_element_op,
                                                                     out_element_op,
                                                                     split_k);
    }

    return 0;
}
