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

#include <iostream>

#include "utils.hpp"

#include <hipdnn_data_sdk/utilities/Tensor.hpp>
#include <hipdnn_data_sdk/utilities/Workspace.hpp>
#include <hipdnn_frontend.hpp>

int main()
{
    using InputType = hipdnn_data_sdk::types::half;

    const int64_t n0 = 837400;
    const int64_t n1 = 15;

    auto buildMultiMarginLossGraph = [=](hipdnnHandle_t handle) {
        auto graph = std::make_shared<hipdnn_frontend::graph::Graph>();

        graph->set_name("multi_margin_loss_graph")
            .set_io_data_type(hipdnn_frontend::getDataTypeEnumFromType<InputType>())
            .set_intermediate_data_type(hipdnn_frontend::getDataTypeEnumFromType<InputType>())
            .set_compute_data_type(hipdnn_frontend::DataType::FLOAT);

        auto input = std::make_shared<hipdnn_frontend::graph::TensorAttributes>(
            hipdnn_frontend::graph::Tensor_attributes()
                .set_name("input")
                .set_dim({n0, n1})
                .set_stride({n1 * 2, 1}));

        auto target = std::make_shared<hipdnn_frontend::graph::TensorAttributes>(
            hipdnn_frontend::graph::Tensor_attributes()
                .set_name("target")
                .set_dim({n0})
                .set_stride({2})
                .set_data_type(hipdnn_frontend::DataType::INT64));

        auto weight = std::make_shared<hipdnn_frontend::graph::TensorAttributes>(
            hipdnn_frontend::graph::Tensor_attributes().set_name("weight").set_dim({n1}).set_stride(
                {2}));

        auto multiMarginLossAttributes = hipdnn_frontend::graph::MultiMarginLossAttributes()
                                             .set_p(1)
                                             .set_margin(1.0f)
                                             .set_reduction(hipdnn_frontend::ReductionMode::AVG)
                                             .set_name("multi_margin_loss");

        auto output = graph->multi_margin_loss(input, target, weight, multiMarginLossAttributes);
        output->set_output(true);

        // build graph
        HIPDNN_FE_CHECK(graph->build(handle));

        return std::make_tuple(graph, input, target, weight, output);
    };

    auto backend = hipdnn_frontend::detail::hipdnnBackend();
    if(!backend)
    {
        std::cout << "Create backend failed.\n";
        return 1;
    }

    hipdnnHandle_t handle;
    HIPDNN_CHECK(backend->create(&handle));

    auto [graph, input, target, weight, output] = buildMultiMarginLossGraph(handle);

    hipdnn_data_sdk::utilities::Tensor<InputType> inputTensor(input->get_dim(),
                                                              input->get_stride());
    hipdnn_data_sdk::utilities::Tensor<int64_t> targetTensor(target->get_dim(),
                                                             target->get_stride());
    hipdnn_data_sdk::utilities::Tensor<InputType> weightTensor(weight->get_dim(),
                                                               weight->get_stride());
    hipdnn_data_sdk::utilities::Tensor<InputType> outputTensor(output->get_dim(),
                                                               output->get_stride());

    std::unordered_map<int64_t, void*> variantPack;
    variantPack[input->get_uid()] = inputTensor.memory().deviceData();
    variantPack[target->get_uid()] = targetTensor.memory().deviceData();
    variantPack[weight->get_uid()] = weightTensor.memory().deviceData();
    variantPack[output->get_uid()] = outputTensor.memory().deviceData();

    int64_t workspaceSize = 0;
    HIPDNN_FE_CHECK(graph->get_workspace_size(workspaceSize));
    const hipdnn_data_sdk::utilities::Workspace workspace(static_cast<size_t>(workspaceSize));

    HIPDNN_FE_CHECK(graph->execute(handle, variantPack, workspace.get()));

    std::cout << "MultiMarginLoss graph execution complete.\n";

    HIPDNN_CHECK(backend->destroy(handle));
    return 0;
}