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

#include <iomanip>
#include <vector>
#include <iostream>

#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_elementwise_3d_impl.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"

#include "ck/library/tensor_operation_instance/gpu/transpose_3d.hpp"

using F16 = ck::half_t;
using F32 = float;

using ADataType = F16;
using BDataType = F16;

using PassThrough = ck::tensor_operation::element_wise::PassThrough;

struct SimpleDeviceMem
{
    SimpleDeviceMem() = delete;

    SimpleDeviceMem(std::size_t mem_size) : p_mem_{}
    {
        (void)hipMalloc(static_cast<void**>(&p_mem_), mem_size);
    }

    void* GetDeviceBuffer() { return p_mem_; }

    ~SimpleDeviceMem() { (void)hipFree(p_mem_); }

    void* p_mem_;
};

int main()
{
    const int N = 16;
    const int C = 8;
    const int D = 8;
    const int H = 8;
    const int W = 8;

    std::vector<std::size_t> ncdhw = {N, C, D, H, W};
    std::vector<std::size_t> nchwd = {N, C, H, W, D};
    // Tensor<ADataType> a(ncdhw);
    // Tensor<BDataType> b(nchwd);

    auto size = N * C * D * H * W;

    // a.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});

    std::array<ck::index_t, 5> ab_lengths{N, C, H, W, D};
    std::array<ck::index_t, 5> a_strides = {C * D * H * W, D * H * W, 1, D * H, D};
    std::array<ck::index_t, 5> b_strides = {C * H * W * D, H * W * D, W * D, D, 1};

    SimpleDeviceMem a_dev_buf(sizeof(ADataType) * size);
    SimpleDeviceMem b_dev_buf(sizeof(BDataType) * size);

    std::array<const void*, 1> input = {a_dev_buf.GetDeviceBuffer()};
    std::array<void*, 1> output      = {b_dev_buf.GetDeviceBuffer()};

    using DeviceElementwisePermuteInstance =
        ck::tensor_operation::device::DeviceElementwise3dImpl<ck::Tuple<ADataType>,
                                                              ck::Tuple<BDataType>,
                                                              PassThrough,
                                                              2,
                                                              2,
                                                              1,
                                                              8,
                                                              8,
                                                              8,
                                                              ck::Sequence<8>,
                                                              ck::Sequence<1>>;

    // get device op instances
    const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
        DeviceElementwisePermuteInstance>::GetInstances();

    std::cout << "found " << op_ptrs.size() << " instances" << std::endl;
    std::string best_op_name;
    bool found            = false;
    int best_op_id        = -1;
    float best_ave_time   = std::numeric_limits<float>::max();
    float best_gb_per_sec = 0;

    // profile device operation instances
    std::cout << "Run all instances and do timing" << std::endl;

    for(int i = 0; i < op_ptrs.size(); ++i)
    {
        auto& op_ptr = op_ptrs[i];

        auto argument_ptr = op_ptr->MakeArgumentPointer(
            ab_lengths, {a_strides}, {b_strides}, input, output, PassThrough{});

        auto invoker_ptr = op_ptr->MakeInvokerPointer();

        std::string op_name = op_ptr->GetTypeString();

        if(op_ptr->IsSupportedArgument(argument_ptr.get()))
        {
            float ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true});

            std::size_t num_byte =
                sizeof(ADataType) * (ncdhw[0] * ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]) +
                sizeof(BDataType) * (ncdhw[0] * ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]);

            float gb_per_sec = num_byte / 1.E6 / ave_time;

            std::cout << "Perf: " << std::setw(10) << ave_time << " ms, " << gb_per_sec << " GB/s, "
                      << op_name << std::endl;

            if(ave_time < best_ave_time)
            {
                found           = true;
                best_op_id      = i;
                best_op_name    = op_name;
                best_ave_time   = ave_time;
                best_gb_per_sec = gb_per_sec;
            }
        }
        else
        {
            std::cout << op_name << " does not support this problem" << std::endl;
        }
    }

    std::cout << "Best Perf: " << best_ave_time << " ms, " << best_gb_per_sec << " GB/s, "
              << best_op_name << std::endl;

    // run the best intance
    {
        auto& op_ptr = op_ptrs[best_op_id];
        std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
                  << std::endl;

        auto argument_ptr = op_ptr->MakeArgumentPointer(
            ab_lengths, {a_strides}, {b_strides}, input, output, PassThrough{});

        auto invoker_ptr = op_ptr->MakeInvokerPointer();

        if(op_ptr->IsSupportedArgument(argument_ptr.get()))
        {
            invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, false});
        }

        std::cout << "Done" << std::endl;
    }

    return 0;
}
