北向用例新增对离线模型接口、错误码参数的实现

Signed-off-by: Nscholar-lc <1936194231@qq.com>
Signed-off-by: Nwangchuanxia <wangchuanxia@huawei.com>
Signed-off-by: Nscholar-lc <1936194231@qq.com>

ai/neural_network_runtime/v2_0/common/mock_idevice.cpp

@@ -206,6 +206,13 @@ int32_t MockIDevice::PrepareModel(const Model& model, const ModelConfig& config,
     return HDF_SUCCESS;
 }
 
+int32_t MockIDevice::PrepareOfflineModel(const std::vector<SharedBuffer>& offlineModels, const ModelConfig& config,
+     sptr<OHOS::HDI::Nnrt::V2_0::IPreparedModel>& preparedModel)
+{
+    preparedModel = new (std::nothrow) V2_0::MockIPreparedModel();
+    return V2_0::NNRT_ReturnCode::NNRT_SUCCESS;
+}
+
 int32_t MockIDevice::PrepareModelFromModelCache(const std::vector<SharedBuffer>& modelCache, const ModelConfig& config,
     sptr<IPreparedModel>& preparedModel)
 {
@@ -251,10 +258,9 @@ int32_t MockIPreparedModel::GetVersion(uint32_t &majorVersion, uint32_t &minorVe
 }
 
 int32_t MockIPreparedModel::Run(const std::vector<IOTensor>& inputs, const std::vector<IOTensor>& outputs,
-    std::vector<std::vector<int32_t>>& outputsDims, std::vector<bool>& isOutputBufferEnough)
+    std::vector<std::vector<int32_t>>& outputsDims)
 {
     outputsDims = {{1, 2, 2, 1}};
-    isOutputBufferEnough = {true};
     return HDF_SUCCESS;
 }
 

ai/neural_network_runtime/v2_0/common/mock_idevice.h

@@ -70,6 +70,9 @@ public:
 
     int32_t PrepareModel(const Model& model, const ModelConfig& config, sptr<IPreparedModel>& preparedModel) override;
 
+    int32_t PrepareOfflineModel(const std::vector<SharedBuffer>& offlineModels, const ModelConfig& config,
+        sptr<OHOS::HDI::Nnrt::V2_0::IPreparedModel>& preparedModel) override;
+
     int32_t PrepareModelFromModelCache(const std::vector<SharedBuffer>& modelCache, const ModelConfig& config,
          sptr<IPreparedModel>& preparedModel) override;
 
@@ -108,7 +111,7 @@ class MockIPreparedModel : public IPreparedModel {
 public:
     int32_t ExportModelCache(std::vector<SharedBuffer>& modelCache) override;
     int32_t Run(const std::vector<IOTensor>& inputs, const std::vector<IOTensor>& outputs,
-    std::vector<std::vector<int32_t>>& outputsDims, std::vector<bool>& isOutputBufferEnough) override;
+    std::vector<std::vector<int32_t>>& outputsDims) override;
     int32_t GetInputDimRanges(std::vector<std::vector<uint32_t>>& minInputDims, std::vector<std::vector<uint32_t>>& maxInputDims) override;
     int32_t GetVersion(uint32_t &majorVersion, uint32_t &minorVersion) override;
     MockIPreparedModel() = default;

ai/neural_network_runtime/v2_0/interface/src/MemoryTest.cpp

@@ -805,7 +805,7 @@ HWTEST_F(MemoryTest, SUB_AI_NNRt_Func_North_Executor_Memory_Run_0200, Function |
     OH_NNExecutor *executor = OH_NNExecutor_Construct(compilation);
     ASSERT_NE(nullptr, executor);
     uint32_t inputIndex = 0;
-    for (auto i = 0; i < graphArgs.operands.size(); i++) {
+    for (size_t i = 0; i < graphArgs.operands.size(); i++) {
         const OHNNOperandTest &operandTem = graphArgs.operands[i];
         auto quantParam = operandTem.quantParam;
         OH_NN_Tensor operand = {operandTem.dataType, (uint32_t)operandTem.shape.size(), operandTem.shape.data(),