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

#include <hipdnn_frontend/Types.hpp>
#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 n = 16; // Batch size
    const int64_t c = 10; // Number of classes

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

        graph->set_name("soft_margin_loss_backward_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({n, c})
                .set_stride({c, 1}));

        auto target = std::make_shared<hipdnn_frontend::graph::TensorAttributes>(
            hipdnn_frontend::graph::Tensor_attributes()
                .set_name("target")
                .set_dim({n, c})
                .set_stride({c, 1}));

        auto doutput = std::make_shared<hipdnn_frontend::graph::TensorAttributes>(
            hipdnn_frontend::graph::Tensor_attributes()
                .set_name("doutput")
                .set_dim({n, c})
                .set_stride({c, 1}));

        auto softMarginLossBackwardAttributes
            = hipdnn_frontend::graph::SoftMarginLossBackwardAttributes()
                  .set_name("soft_margin_loss_backward")
                  .set_reduction(hipdnn_frontend::ReductionMode::NONE);

        auto dinput = graph->soft_margin_loss_backward(
            input, target, doutput, softMarginLossBackwardAttributes);
        dinput->set_output(true);

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

        return std::make_tuple(graph, input, target, doutput, dinput);
    };

    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, doutput, dinput] = buildSoftMarginLossBackwardGraph(handle);

    hipdnn_data_sdk::utilities::Tensor<InputType> inputTensor(input->get_dim(),
                                                              input->get_stride());
    hipdnn_data_sdk::utilities::Tensor<InputType> targetTensor(target->get_dim(),
                                                               target->get_stride());
    hipdnn_data_sdk::utilities::Tensor<InputType> doutputTensor(doutput->get_dim(),
                                                                doutput->get_stride());
    hipdnn_data_sdk::utilities::Tensor<InputType> dinputTensor(dinput->get_dim(),
                                                               dinput->get_stride());

    std::unordered_map<int64_t, void*> variantPack;
    variantPack[input->get_uid()] = inputTensor.memory().deviceData();
    variantPack[target->get_uid()] = targetTensor.memory().deviceData();
    variantPack[doutput->get_uid()] = doutputTensor.memory().deviceData();
    variantPack[dinput->get_uid()] = dinputTensor.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 << "SoftMarginLossBackward graph execution complete.\n";

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