HarmonyOS 鸿蒙Next中调用HIAI推理模型，显示模型不兼容和Process执行失败。

HarmonyOS 鸿蒙Next中调用HIAI推理模型，显示模型不兼容和Process执行失败。

环境：

• hwhiai-ddk-5.0.1.0-next
• DDK_tools_5.0.1.0-next
• ohos ndk version : 5.0.0.12 和 6.0.0.37
• 手机型号：nove 14，系统：Hormony Next 5.0

通过 param get | gerp "hiai" 查询到:

const.hiai.vendor.hiaiversion = 101.530.010.010
const.hiai.hiaiapiversion = 3.0
startup.service.ctl.hiaiserver = 2
startup.service.ctl.hiaiserver.pid = 888

测试模型reset18, 尝试了两种来源：

• model_zoo
• 通过omg自行转换onnx到om模型

目前的问题是：

1. CheckModelCompatibility 返回模型不兼容
2. 如果忽略不兼容信息，继续执行，则能正常读取模型输入输出信息，但是在 Process 返回 AI_FAILED 状态

下面是测试代码(多余的 status 检查已经去掉，仅保留了报错的)：

int main() {
    printf("Hello, HIAI Model Manager!\n");
    hiai::AIStatus status = hiai::AI_SUCCESS;
    std::shared_ptr<hiai::AiModelMngerClient> modelManagerClient = std::make_shared<hiai::AiModelMngerClient>();
    status = modelManagerClient->Init(nullptr);
    
    hiai::AiModelBuilder modelBuilder(modelManagerClient);
    hiai::MemBuffer* modelBuffer = modelBuilder.InputMemBufferCreate("/data/local/tmp/resnet18.om");

    std::shared_ptr<hiai::AiModelDescription> modelDesc = std::make_shared<hiai::AiModelDescription>(
        "resnet18", hiai::AiModelDescription_Frequency_HIGH, hiai::HIAI_FRAMEWORK_NONE,
        hiai::HIAI_MODELTYPE_OFFLINE, hiai::AiModelDescription_DeviceType_NPU);

    status = modelDesc->SetModelBuffer(modelBuffer->GetMemBufferData(), modelBuffer->GetMemBufferSize());
    bool isModelCompatible = false;
    status = modelManagerClient->CheckModelCompatibility(*modelDesc, isModelCompatible);
    // 总是在这里报兼容性失败
    if (!isModelCompatible) {
        std::cerr << "Model is not compatible.T_T" << std::endl;
        // 忽略错误
        // modelBuilder.MemBufferDestroy(modelBuffer);
        // return -1;
    }
    
    std::vector<std::shared_ptr<hiai::AiModelDescription>> modelDescs;
    modelDescs.push_back(modelDesc);
    status = modelManagerClient->Load(modelDescs);

    std::vector<hiai::TensorDimension> inputDims, outputDims;
    std::vector<std::shared_ptr<hiai::AiTensor>> inputTensors, outputTensors;
    status = modelManagerClient->GetModelIOTensorDim(
        modelDesc->GetName(), inputDims, outputDims);
    
    // 正常读取模型输入输出信息
    for (const auto& dim : inputDims) {
        std::cout << "Input Tensor Dimension: "
                  << "Number: " << dim.GetNumber()
                  << ", Channel: " << dim.GetChannel()
                  << ", Height: " << dim.GetHeight()
                  << ", Width: " << dim.GetWidth() << std::endl;
        std::shared_ptr<hiai::AiTensor> inputTensor = std::make_shared<hiai::AiTensor>();
        hiai::AIStatus initStatus = inputTensor->Init(&dim);
        random_setAiTensor(inputTensor);
        inputTensors.push_back(inputTensor);
        printf("iptr: %p, size: %u\n", inputTensor->GetBuffer(), inputTensor->GetSize());
    }
    // 正常读取模型输入输出信息
    for (const auto& dim : outputDims) {
        std::cout << "Output Tensor Dimension: "
                  << "Number: " << dim.GetNumber()
                  << ", Channel: " << dim.GetChannel()
                  << ", Height: " << dim.GetHeight()
                  << ", Width: " << dim.GetWidth() << std::endl;
        std::shared_ptr<hiai::AiTensor> outputTensor = std::make_shared<hiai::AiTensor>();
        hiai::AIStatus initStatus = outputTensor->Init(&dim);
        outputTensors.push_back(outputTensor);
        printf("optr: %p, size: %u\n", outputTensor->GetBuffer(), outputTensor->GetSize());
    }
    hiai::AiContext context;
    context.AddPara("resnet18", modelDesc->GetName());
    int istamp = 0;
    status = modelManagerClient->Process(context, inputTensors, outputTensors, 1000, istamp);
    // 推理错误
    if (status != hiai::AI_SUCCESS) {
        std::cerr << "Failed to process model: " << status << std::endl;
        modelBuilder.MemBufferDestroy(modelBuffer);
        return -1;
    }
    return 0;
}