tensorrt使用parser解析UFF模型

class Logger : public ILogger       //1.创建logger
            {
        void log(Severity severity, const char* msg) override
        {
            if (severity != Severity::kINFO)
                std::cout << msg << std::endl;
        }} gLogger;
void createngine() //生成 engine
{
    //创建builder
    IBuilder* builder = createInferBuilder(gLogger);

    //创建network
    INetworkDefinition* network = builder->createNetworkV2(0U);

    //创建parser
    IUffParser* parser = createUffParser();

    //注册网络输入输出  (输入名和输出名可在.uff文件中找到)
    parser->registerInput("inputs", DimsCHW(1, 576 , 960), UffInputOrder::kNCHW);
    parser->registerOutput("generator/deconv/BiasAdd");

    //使用parser，填充network  （DataType::kFLOAT（fp32） DataType::kHALF(fp16)）
    parser->parse("/home/xxxx.uff",
                  *network,
                  nvinfer1::DataType::kHALF);

    //创建config并设置最大的工作空间
    IBuilderConfig* config = builder->createBuilderConfig();
    config->setMaxWorkspaceSize(1 << 30);

    //创建engine
    ICudaEngine* engine = builder->buildEngineWithConfig(*network,*config);

    //序列化保存engine到文件
    IHostMemory *serializedModel = engine->serialize();
    ofstream p("xxxx.engine");
    p.write(reinterpret_cast<const char*>(serializedModel->data()), serializedModel->size());

    //释放资源
    parser->destroy();
    network->destroy();
    builder->destroy();
    engine->destroy();
    serializedModel->destroy();
    config->destroy();
    return;
}