Rename CANN to Ascend

CMakeLists.txt

@@ -65,8 +65,8 @@ option(ENABLE_VISION "Whether to enable vision models usage." OFF)
 option(ENABLE_TEXT "Whether to enable text models usage." OFF)
 option(ENABLE_FLYCV "Whether to enable flycv to boost image preprocess." OFF)
 option(ENABLE_TIMVX "Whether to compile for TIMVX deploy." OFF)
-option(WITH_CANN "Whether to compile for Huawei Ascend deploy with CANN." OFF)
+option(WITH_ASCEND "Whether to compile for Huawei Ascend deploy." OFF)
-option(WITH_CANN_PY "Whether to compile for Huawei Ascend deploy with CANN using python." OFF)
+option(WITH_ASCEND_PYTHON "Whether to compile for Huawei Ascend deploy using python." OFF)
 option(WITH_TIMVX "Whether to compile for TIMVX deploy." OFF)
 option(WITH_XPU "Whether to compile for KunlunXin XPU deploy." OFF)
 option(WITH_TESTING "Whether to compile with unittest." OFF)
@@ -146,7 +146,7 @@ if (WITH_TIMVX)
   include(${PROJECT_SOURCE_DIR}/cmake/timvx.cmake)
 endif()
 
-if (WITH_CANN)
+if (WITH_ASCEND)
   if(NOT ${ENABLE_LITE_BACKEND})
     set(ENABLE_LITE_BACKEND ON)
   endif()
@@ -158,8 +158,8 @@ if (WITH_CANN)
   endif()
 endif()
 
-if (WITH_CANN_PY)
+if (WITH_ASCEND_PYTHON)
-  message(WARNING "This is only for CANN python version")
+  message(WARNING "This is only for Ascend python version")
   if(NOT ${ENABLE_LITE_BACKEND})
       set(ENABLE_LITE_BACKEND ON)
   endif()
@@ -175,7 +175,7 @@ if (WITH_CANN_PY)
                 OUTPUT_VARIABLE curr_out
                 ERROR_VARIABLE  curr_out)
   if(ret EQUAL "1")
-    message(FATAL_ERROR "Failed to patchelf CANN libraries.")
+    message(FATAL_ERROR "Failed to patchelf Paddle Lite libraries when using Ascend.")
   endif()
   message(STATUS "result:${result} out:${curr_out}")
 endif()

cmake/summary.cmake

@@ -37,8 +37,8 @@ function(fastdeploy_summary)
   message(STATUS "  ENABLE_POROS_BACKEND      : ${ENABLE_POROS_BACKEND}")
   message(STATUS "  ENABLE_TRT_BACKEND        : ${ENABLE_TRT_BACKEND}")
   message(STATUS "  ENABLE_OPENVINO_BACKEND   : ${ENABLE_OPENVINO_BACKEND}")
-  message(STATUS "  WITH_CANN                 : ${WITH_CANN}")
+  message(STATUS "  WITH_ASCEND                 : ${WITH_ASCEND}")
-  message(STATUS "  WITH_CANN_PY              : ${WITH_CANN_PY}") 
+  message(STATUS "  WITH_ASCEND_PYTHON              : ${WITH_ASCEND_PYTHON}") 
   message(STATUS "  WITH_TIMVX                : ${WITH_TIMVX}")
   message(STATUS "  WITH_XPU                  : ${WITH_XPU}")
   if(ENABLE_ORT_BACKEND)

docs/cn/build_and_install/README.md

@@ -24,8 +24,8 @@
 | ENABLE_PADDLE_BACKEND   | 默认OFF，是否编译集成Paddle Inference后端(CPU/GPU上推荐打开)                             |  
 | ENABLE_LITE_BACKEND     | 默认OFF，是否编译集成Paddle Lite后端(编译Android库时需要设置为ON)                          |
 | ENABLE_RKNPU2_BACKEND   | 默认OFF，是否编译集成RKNPU2后端(RK3588/RK3568/RK3566上推荐打开)                           |
-| WITH_CANN               | 默认OFF，当在华为昇腾NPU上部署时, 需要设置为ON                                              |
+| WITH_ASCEND             | 默认OFF，当在华为昇腾NPU上部署时, 需要设置为ON                                              |
-| WITH_CANN_PY            | 默认OFF，当在华为昇腾NPU上,并使用Python部署时, 需要设置为ON                                  |
+| WITH_ASCEND_PYTHON      | 默认OFF，当在华为昇腾NPU上,并使用Python部署时, 需要设置为ON                                  |
 | ENABLE_TIMVX            | 默认OFF，需要在RV1126/RV1109上部署时，需设置为ON                                          |
 | WITH_XPU                | 默认OFF，当在昆仑芯XPU上部署时，需设置为ON                                                |
 | WITH_TIMVX              | 默认OFF，需要在RV1126/RV1109/A311D上部署时，需设置为ON                                   |

docs/cn/build_and_install/huawei_ascend.md

@@ -69,8 +69,8 @@ cd FastDeploy
 mkdir build && cd build
 
 # CMake configuration with CANN
-cmake -DWITH_CANN=ON  \
+cmake -DWITH_ASCEND=ON  \
-      -DCMAKE_INSTALL_PREFIX=fastdeploy-cann \
+      -DCMAKE_INSTALL_PREFIX=fastdeploy-ascend \
       -DENABLE_VISION=ON \
       ..
 
@@ -78,7 +78,7 @@ cmake -DWITH_CANN=ON  \
 make -j8
 make install
 ```  
-编译完成之后，会在当前的build目录下生成 fastdeploy-cann 目录，表示基于 PadddleLite CANN 的 FastDeploy 库编译完成。
+编译完成之后，会在当前的build目录下生成 fastdeploy-ascend 目录，表示基于 PadddleLite 的 FastDeploy 库编译完成。
 
 ## 四.基于 PaddleLite 的 Python FastDeploy 库编译
 搭建好编译环境之后，编译命令如下：
@@ -86,7 +86,7 @@ make install
 # Download the latest source code
 git clone https://github.com/PaddlePaddle/FastDeploy.git
 cd FastDeploy/python
-export WITH_CANN_PY=ON
+export WITH_ASCEND_PYTHON=ON
 export ENABLE_VISION=ON
 
 python setup.py build

examples/vision/classification/paddleclas/ascend/cpp/CMakeLists.txt

@@ -2,7 +2,7 @@ PROJECT(infer_demo C CXX)
 CMAKE_MINIMUM_REQUIRED (VERSION 3.10)
 
 # 指定下载解压后的fastdeploy库路径
-option(FASTDEPLOY_INSTALL_DIR "Path of fastdeploy-cann sdk")
+option(FASTDEPLOY_INSTALL_DIR "Path of fastdeploy-ascend sdk")
 
 include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake)
 

examples/vision/classification/paddleclas/ascend/cpp/README.md

@@ -15,7 +15,7 @@
 # 编译当前demo
 mkdir build
 cd build
-cmake .. -DFASTDEPLOY_INSTALL_DIR=../../../../../../build/fastdeploy-cann
+cmake .. -DFASTDEPLOY_INSTALL_DIR=../../../../../../build/fastdeploy-ascend
 make -j8
 cd ..
 

examples/vision/classification/paddleclas/ascend/cpp/infer.cc

@@ -25,9 +25,7 @@ void InitAndInfer(const std::string& model_dir, const std::string& image_file) {
   auto config_file = model_dir + sep + "inference_cls.yaml";
   
   fastdeploy::RuntimeOption option;
-  option.UseCANN();
+  option.UseAscend();
-  option.SetNNAdapterDeviceNames({"huawei_ascend_npu"});
-  option.SetNNAdapterContextProperties("HUAWEI_ASCEND_NPU_SELECTED_DEVICE_IDS=0");
 
   auto model = fastdeploy::vision::classification::PaddleClasModel(
       model_file, params_file, config_file, option);

examples/vision/classification/paddleclas/ascend/cpp/run.sh

@@ -2,8 +2,8 @@
 
 export GLOG_v=5
 # 设置本demo的环境变量
-# 正确设置fastdeploy-cann的安装路径
+# 正确设置fastdeploy-ascend的安装路径
-FASTDEPLOY_INSTALL_DIR="../../../../../../build/fastdeploy-cann/"
+FASTDEPLOY_INSTALL_DIR="../../../../../../build/fastdeploy-ascend/"
 # 设置fastdeploy,opencv和paddlelite相关的环境变量
 export LD_LIBRARY_PATH=$FASTDEPLOY_INSTALL_DIR/lib/:$FASTDEPLOY_INSTALL_DIR/third_libs/install/opencv/lib/:$FASTDEPLOY_INSTALL_DIR/third_libs/install/paddlelite/lib/:$LD_LIBRARY_PATH
 

examples/vision/classification/paddleclas/ascend/python/infer.py

@@ -18,10 +18,9 @@ def parse_arguments():
 
 
 def build_option():
-    option = fd.RuntimeOption()
 
-    option.use_cann()
+    option = fd.RuntimeOption()
-    option.set_lite_nnadapter_device_names(["huawei_ascend_npu"])
+    option.use_ascend()
 
     return option
 

fastdeploy/backends/lite/lite_backend.cc

@@ -89,9 +89,34 @@ void LiteBackend::BuildOption(const LiteBackendOption& option) {
         paddle::lite_api::Place{TARGET(kNNAdapter), PRECISION(kFloat)});
     valid_places.push_back(
         paddle::lite_api::Place{TARGET(kARM), PRECISION(kInt8)});
-  }else if(option_.enable_cann){
+  }else if(option_.enable_ascend){
+    
+    if(!option_.nnadapter_device_names.empty()){
       config_.set_nnadapter_device_names(option_.nnadapter_device_names);
-    config_.set_nnadapter_context_properties(option_.nnadapter_context_properties);
+    } else {
+      config_.set_nnadapter_device_names({"huawei_ascend_npu"});
+    }
+
+    if(!option_.nnadapter_context_properties.empty()){
+      config_.set_nnadapter_context_properties(nnadapter_context_properties);
+    }
+
+    if(!option_.nnadapter_model_cache_dir.empty()){
+      config_.set_nnadapter_model_cache_dir(nnadapter_model_cache_dir);
+    }
+
+    if(!option_.nnadapter_mixed_precision_quantization_config_path.empty()){
+      config_.set_nnadapter_mixed_precision_quantization_config_path(
+        nnadapter_mixed_precision_quantization_config_path
+      );
+    }
+
+    if(!option_.nnadapter_subgraph_partition_config_path.empty()){
+      config_.nnadapter_subgraph_partition_config_path(
+        nnadapter_subgraph_partition_config_path
+      );
+    }
+
     valid_places.push_back(
           paddle::lite_api::Place{TARGET(kNNAdapter), PRECISION(kInt8)});
     valid_places.push_back(

fastdeploy/backends/lite/lite_backend.h

@@ -52,7 +52,7 @@ struct LiteBackendOption {
     nnadapter_dynamic_shape_info = {{" ", {{0}}}};
   std::string nnadapter_mixed_precision_quantization_config_path = "";
   bool enable_timvx = false;
-  bool enable_cann = false;
+  bool enable_ascend = false;
   bool enable_xpu = false;
   int device_id = 0;
   int xpu_l3_workspace_size = 0xfffc00;

fastdeploy/core/fd_type.cc

@@ -62,8 +62,8 @@ std::string Str(const Device& d) {
     case Device::TIMVX:
       out = "Device::TIMVX";
       break;
-    case Device::CANN:
+    case Device::ASCEND:
-      out = "Device::CANN";
+      out = "Device::ASCEND";
       break;
     case Device::XPU:
       out = "Device::XPU";
@@ -91,8 +91,8 @@ std::ostream& operator<<(std::ostream& out,const Device& d){
   case Device::XPU:
     out << "Device::XPU";
     break;
-  case Device::CANN:
+  case Device::ASCEND:
-    out << "Device::CANN";
+    out << "Device::ASCEND";
     break;
   default:
     out << "Device::UNKOWN";

fastdeploy/core/fd_type.h

@@ -22,7 +22,7 @@
 
 namespace fastdeploy {
 
-enum FASTDEPLOY_DECL Device { CPU, GPU, RKNPU, IPU, TIMVX, XPU, CANN};
+enum FASTDEPLOY_DECL Device { CPU, GPU, RKNPU, IPU, TIMVX, XPU, ASCEND};
 
 FASTDEPLOY_DECL std::string Str(const Device& d);
 

fastdeploy/fastdeploy_model.cc

@@ -51,7 +51,7 @@ bool FastDeployModel::InitRuntimeWithSpecifiedBackend() {
   bool use_ipu = (runtime_option.device == Device::IPU);
   bool use_rknpu = (runtime_option.device == Device::RKNPU);
   bool use_timvx = (runtime_option.device == Device::TIMVX);
-  bool use_cann = (runtime_option.device == Device::CANN); 
+  bool use_ascend = (runtime_option.device == Device::ASCEND); 
   bool use_xpu = (runtime_option.device == Device::XPU);
 
   if (use_gpu) {
@@ -69,9 +69,9 @@ bool FastDeployModel::InitRuntimeWithSpecifiedBackend() {
       FDERROR << "The valid timvx backends of model " << ModelName() << " are " << Str(valid_timvx_backends) << ", " << runtime_option.backend << " is not supported." << std::endl;
       return false;
     }
-  } else if (use_cann) {
+  } else if (use_ascend) {
-    if (!IsSupported(valid_cann_backends, runtime_option.backend)) {
+    if (!IsSupported(valid_ascend_backends, runtime_option.backend)) {
-      FDERROR << "The valid cann backends of model " << ModelName() << " are " << Str(valid_cann_backends) << ", " << runtime_option.backend << " is not supported." << std::endl;
+      FDERROR << "The valid ascend backends of model " << ModelName() << " are " << Str(valid_ascend_backends) << ", " << runtime_option.backend << " is not supported." << std::endl;
       return false;
     }
   } else if (use_xpu) {
@@ -114,8 +114,8 @@ bool FastDeployModel::InitRuntimeWithSpecifiedDevice() {
     return CreateRKNPUBackend();
   } else if (runtime_option.device == Device::TIMVX) {
     return CreateTimVXBackend();
-  } else if (runtime_option.device == Device::CANN) {
+  } else if (runtime_option.device == Device::ASCEND) {
-    return CreateCANNBackend();
+    return CreateASCENDBackend();
   } else if (runtime_option.device == Device::XPU) {
     return CreateXPUBackend();
   } else if (runtime_option.device == Device::IPU) {
@@ -127,7 +127,7 @@ bool FastDeployModel::InitRuntimeWithSpecifiedDevice() {
     return false;
 #endif
   }
-  FDERROR << "Only support CPU/GPU/IPU/RKNPU/TIMVX/XPU/CANN now." << std::endl;
+  FDERROR << "Only support CPU/GPU/IPU/RKNPU/TIMVX/XPU/ASCEND now." << std::endl;
   return false;
 }
 
@@ -265,18 +265,18 @@ bool FastDeployModel::CreateXPUBackend() {
 }
 
 
-bool FastDeployModel::CreateCANNBackend() {
+bool FastDeployModel::CreateASCENDBackend() {
-  if (valid_cann_backends.size() == 0) {
+  if (valid_ascend_backends.size() == 0) {
-    FDERROR << "There's no valid cann backends for model: " << ModelName()
+    FDERROR << "There's no valid ascend backends for model: " << ModelName()
             << std::endl;
     return false;
   }
 
-  for (size_t i = 0; i < valid_cann_backends.size(); ++i) {
+  for (size_t i = 0; i < valid_ascend_backends.size(); ++i) {
-    if (!IsBackendAvailable(valid_cann_backends[i])) {
+    if (!IsBackendAvailable(valid_ascend_backends[i])) {
       continue;
     }
-    runtime_option.backend = valid_cann_backends[i];
+    runtime_option.backend = valid_ascend_backends[i];
     runtime_ = std::unique_ptr<Runtime>(new Runtime());
     if (!runtime_->Init(runtime_option)) {
       return false;

fastdeploy/fastdeploy_model.h

@@ -45,9 +45,9 @@ class FASTDEPLOY_DECL FastDeployModel {
   /** Model's valid timvx backends. This member defined all the timvx backends have successfully tested for the model
    */
   std::vector<Backend> valid_timvx_backends = {};
-  /** Model's valid cann backends. This member defined all the cann backends have successfully tested for the model
+  /** Model's valid ascend backends. This member defined all the cann backends have successfully tested for the model
    */
-  std::vector<Backend> valid_cann_backends = {};
+  std::vector<Backend> valid_ascend_backends = {};
   /** Model's valid KunlunXin xpu backends. This member defined all the KunlunXin xpu backends have successfully tested for the model
    */
   std::vector<Backend> valid_xpu_backends = {};
@@ -150,7 +150,7 @@ class FASTDEPLOY_DECL FastDeployModel {
   bool CreateRKNPUBackend();
   bool CreateTimVXBackend();
   bool CreateXPUBackend();
-  bool CreateCANNBackend();
+  bool CreateASCENDBackend();
 
   std::shared_ptr<Runtime> runtime_;
   bool runtime_initialized_ = false;

fastdeploy/pybind/runtime.cc

@@ -23,7 +23,7 @@ void BindRuntime(pybind11::module& m) {
       .def("use_gpu", &RuntimeOption::UseGpu)
       .def("use_cpu", &RuntimeOption::UseCpu)
       .def("use_rknpu2", &RuntimeOption::UseRKNPU2)
-      .def("use_cann", &RuntimeOption::UseCANN)
+      .def("use_ascend", &RuntimeOption::UseAscend)
       .def("use_xpu", &RuntimeOption::UseXpu)
       .def("set_external_stream", &RuntimeOption::SetExternalStream)
       .def("set_cpu_thread_num", &RuntimeOption::SetCpuThreadNum)
@@ -34,13 +34,13 @@ void BindRuntime(pybind11::module& m) {
       .def("use_trt_backend", &RuntimeOption::UseTrtBackend)
       .def("use_openvino_backend", &RuntimeOption::UseOpenVINOBackend)
       .def("use_lite_backend", &RuntimeOption::UseLiteBackend)
-      .def("set_lite_nnadapter_device_names", &RuntimeOption::SetLiteNNAdapterDeviceNames)
+      .def("set_lite_device_names", &RuntimeOption::SetLiteDeviceNames)
-      .def("set_lite_nnadapter_context_properties", &RuntimeOption::SetLiteNNAdapterContextProperties)
+      .def("set_lite_context_properties", &RuntimeOption::SetLiteContextProperties)
-      .def("set_lite_nnadapter_model_cache_dir", &RuntimeOption::SetLiteNNAdapterModelCacheDir)
+      .def("set_lite_model_cache_dir", &RuntimeOption::SetLiteModelCacheDir)
-      .def("set_lite_nnadapter_dynamic_shape_info", &RuntimeOption::SetLiteNNAdapterDynamicShapeInfo)
+      .def("set_lite_dynamic_shape_info", &RuntimeOption::SetLiteDynamicShapeInfo)
-      .def("set_lite_nnadapter_subgraph_partition_path", &RuntimeOption::SetLiteNNAdapterSubgraphPartitionPath)
+      .def("set_lite_subgraph_partition_path", &RuntimeOption::SetLiteSubgraphPartitionPath)
-      .def("set_lite_nnadapter_mixed_precision_quantization_config_path", &RuntimeOption::SetLiteNNAdapterMixedPrecisionQuantizationConfigPath)
+      .def("set_lite_mixed_precision_quantization_config_path", &RuntimeOption::SetLiteMixedPrecisionQuantizationConfigPath)
-      .def("set_lite_nnadapter_subgraph_partition_config_buffer", &RuntimeOption::SetLiteNNAdapterSubgraphPartitionConfigBuffer)
+      .def("set_lite_subgraph_partition_config_buffer", &RuntimeOption::SetLiteSubgraphPartitionConfigBuffer)
       .def("set_paddle_mkldnn", &RuntimeOption::SetPaddleMKLDNN)
       .def("set_openvino_device", &RuntimeOption::SetOpenVINODevice)
       .def("set_openvino_shape_info", &RuntimeOption::SetOpenVINOShapeInfo)

fastdeploy/runtime.cc

@@ -258,9 +258,9 @@ void RuntimeOption::UseXpu(int xpu_id,
   device = Device::XPU;
 }
 
-void RuntimeOption::UseCANN(){
+void RuntimeOption::UseAscend(){
-  enable_cann = true;
+  enable_ascend = true;
-  device = Device::CANN;
+  device = Device::ASCEND;
 }
 
 void RuntimeOption::SetExternalStream(void* external_stream) {
@@ -382,37 +382,37 @@ void RuntimeOption::SetLiteOptimizedModelDir(
   lite_optimized_model_dir = optimized_model_dir;
 }
 
-void RuntimeOption::SetLiteNNAdapterSubgraphPartitionPath(
+void RuntimeOption::SetLiteSubgraphPartitionPath(
     const std::string& nnadapter_subgraph_partition_config_path) {
   lite_nnadapter_subgraph_partition_config_path =
       nnadapter_subgraph_partition_config_path;
 }
 
-void RuntimeOption::SetLiteNNAdapterSubgraphPartitionConfigBuffer(
+void RuntimeOption::SetLiteSubgraphPartitionConfigBuffer(
       const std::string& nnadapter_subgraph_partition_config_buffer){
   lite_nnadapter_subgraph_partition_config_buffer = nnadapter_subgraph_partition_config_buffer;
 }
 
-void RuntimeOption::SetLiteNNAdapterDeviceNames(const std::vector<std::string>& nnadapter_device_names){
+void RuntimeOption::SetLiteDeviceNames(const std::vector<std::string>& nnadapter_device_names){
   lite_nnadapter_device_names = nnadapter_device_names; 
 }
 
-void RuntimeOption::SetLiteNNAdapterContextProperties(const std::string& nnadapter_context_properties){
+void RuntimeOption::SetLiteContextProperties(const std::string& nnadapter_context_properties){
   lite_nnadapter_context_properties = nnadapter_context_properties; 
 }
 
-void RuntimeOption::SetLiteNNAdapterModelCacheDir(const std::string& nnadapter_model_cache_dir){
+void RuntimeOption::SetLiteModelCacheDir(const std::string& nnadapter_model_cache_dir){
   lite_nnadapter_model_cache_dir = nnadapter_model_cache_dir;
 }
 
 
-void RuntimeOption::SetLiteNNAdapterDynamicShapeInfo(
+void RuntimeOption::SetLiteDynamicShapeInfo(
       const std::map<std::string, std::vector<std::vector<int64_t>>>&
           nnadapter_dynamic_shape_info){
   lite_nnadapter_dynamic_shape_info = nnadapter_dynamic_shape_info; 
 }
 
-void RuntimeOption::SetLiteNNAdapterMixedPrecisionQuantizationConfigPath(
+void RuntimeOption::SetLiteMixedPrecisionQuantizationConfigPath(
       const std::string& nnadapter_mixed_precision_quantization_config_path){
         lite_nnadapter_mixed_precision_quantization_config_path = nnadapter_mixed_precision_quantization_config_path;
 }
@@ -586,7 +586,7 @@ bool Runtime::Init(const RuntimeOption& _option) {
     FDINFO << "Runtime initialized with Backend::OPENVINO in "
            << Str(option.device) << "." << std::endl;
   } else if (option.backend == Backend::LITE) {
-    FDASSERT(option.device == Device::CPU || option.device == Device::TIMVX || option.device == Device::XPU || option.device == Device::CANN,
+    FDASSERT(option.device == Device::CPU || option.device == Device::TIMVX || option.device == Device::XPU || option.device == Device::ASCEND,
              "Backend::LITE only supports Device::CPU/Device::TIMVX/Device::XPU.");
     CreateLiteBackend();
     FDINFO << "Runtime initialized with Backend::LITE in " << Str(option.device)
@@ -843,7 +843,7 @@ void Runtime::CreateLiteBackend() {
   lite_option.nnadapter_dynamic_shape_info = option.lite_nnadapter_dynamic_shape_info;
   lite_option.nnadapter_mixed_precision_quantization_config_path = option.lite_nnadapter_mixed_precision_quantization_config_path;
   lite_option.enable_timvx = option.enable_timvx;
-  lite_option.enable_cann = option.enable_cann;
+  lite_option.enable_ascend = option.enable_ascend;
   lite_option.enable_xpu = option.enable_xpu;
   lite_option.device_id  = option.device_id;
   lite_option.xpu_l3_workspace_size  = option.xpu_l3_workspace_size;

fastdeploy/runtime.h

@@ -102,8 +102,8 @@ struct FASTDEPLOY_DECL RuntimeOption {
   /// Use TimVX to inference
   void UseTimVX();
 
-  /// Use CANN to inference
+  /// Use Huawei Ascend to inference
-  void UseCANN();
+  void UseAscend();
 
   ///
   /// \brief Turn on XPU.
@@ -224,46 +224,46 @@ struct FASTDEPLOY_DECL RuntimeOption {
   void SetLiteOptimizedModelDir(const std::string& optimized_model_dir);
 
   /**
-   * @brief Set nnadapter subgraph partition path for Paddle Lite backend.
+   * @brief Set subgraph partition path for Paddle Lite backend.
    */
-  void SetLiteNNAdapterSubgraphPartitionPath(
+  void SetLiteSubgraphPartitionPath(
       const std::string& nnadapter_subgraph_partition_config_path);
 
   /**
-   * @brief Set nnadapter subgraph partition path for Paddle Lite backend.
+   * @brief Set subgraph partition path for Paddle Lite backend.
    */
-  void SetLiteNNAdapterSubgraphPartitionConfigBuffer(
+  void SetLiteSubgraphPartitionConfigBuffer(
       const std::string& nnadapter_subgraph_partition_config_buffer);
 
   /**
-   * @brief Set nnadapter device name for Paddle Lite backend.
+   * @brief Set device name for Paddle Lite backend.
    */
-  void SetLiteNNAdapterDeviceNames(
+  void SetLiteDeviceNames(
       const std::vector<std::string>& nnadapter_device_names);
 
   /**
-   * @brief Set nnadapter context properties for Paddle Lite backend.
+   * @brief Set context properties for Paddle Lite backend.
    */
-  void  SetLiteNNAdapterContextProperties(
+  void  SetLiteContextProperties(
       const std::string& nnadapter_context_properties);
 
   /**
-   * @brief Set nnadapter model cache dir for Paddle Lite backend.
+   * @brief Set model cache dir for Paddle Lite backend.
    */
-  void SetLiteNNAdapterModelCacheDir(
+  void SetLiteModelCacheDir(
       const std::string& nnadapter_model_cache_dir);
 
   /**
-   * @brief Set nnadapter dynamic shape info for Paddle Lite backend.
+   * @brief Set dynamic shape info for Paddle Lite backend.
    */
-  void SetLiteNNAdapterDynamicShapeInfo(
+  void SetLiteDynamicShapeInfo(
       const std::map<std::string, std::vector<std::vector<int64_t>>>&
           nnadapter_dynamic_shape_info);
 
   /**
-   * @brief Set nnadapter mixed precision quantization config path for Paddle Lite backend.
+   * @brief Set mixed precision quantization config path for Paddle Lite backend.
    */
-  void SetLiteNNAdapterMixedPrecisionQuantizationConfigPath(
+  void SetLiteMixedPrecisionQuantizationConfigPath(
       const std::string& nnadapter_mixed_precision_quantization_config_path);
 
   /**
@@ -434,7 +434,7 @@ struct FASTDEPLOY_DECL RuntimeOption {
   std::string lite_nnadapter_mixed_precision_quantization_config_path = "";
 
   bool enable_timvx = false;
-  bool enable_cann = false;
+  bool enable_ascend = false;
   bool enable_xpu = false;
 
   // ======Only for Trt Backend=======

fastdeploy/vision/classification/ppcls/model.cc

@@ -29,7 +29,7 @@ PaddleClasModel::PaddleClasModel(const std::string& model_file,
                           Backend::LITE};
     valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
     valid_timvx_backends = {Backend::LITE};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
     valid_xpu_backends = {Backend::LITE};
     valid_ipu_backends = {Backend::PDINFER};
   } else if (model_format == ModelFormat::ONNX) {

fastdeploy/vision/detection/contrib/yolov5/yolov5.cc

@@ -29,7 +29,7 @@ YOLOv5::YOLOv5(const std::string& model_file, const std::string& params_file,
     valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
     valid_xpu_backends = {Backend::LITE};
     valid_timvx_backends = {Backend::LITE};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
   }
   runtime_option = custom_option;
   runtime_option.model_format = model_format;

fastdeploy/vision/detection/contrib/yolov6.cc

@@ -72,7 +72,7 @@ YOLOv6::YOLOv6(const std::string& model_file, const std::string& params_file,
   } else {
     valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::LITE};
     valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
   }
   runtime_option = custom_option;
   runtime_option.model_format = model_format;

fastdeploy/vision/detection/contrib/yolov7/yolov7.cc

@@ -27,7 +27,7 @@ YOLOv7::YOLOv7(const std::string& model_file, const std::string& params_file,
   } else {
     valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::LITE};
     valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
   }
   runtime_option = custom_option;
   runtime_option.model_format = model_format;

fastdeploy/vision/detection/ppdet/model.h

@@ -39,7 +39,7 @@ class FASTDEPLOY_DECL PicoDet : public PPDetBase {
                         Backend::PDINFER, Backend::LITE};
     valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
     valid_rknpu_backends = {Backend::RKNPU2};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
     initialized = Initialize();
   }
 
@@ -66,7 +66,7 @@ class FASTDEPLOY_DECL PPYOLOE : public PPDetBase {
                         Backend::PDINFER, Backend::LITE};
     valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
     valid_timvx_backends = {Backend::LITE};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
     initialized = Initialize();
   }
 
@@ -91,7 +91,7 @@ class FASTDEPLOY_DECL PPYOLO : public PPDetBase {
                 model_format) {
     valid_cpu_backends = {Backend::PDINFER, Backend::LITE};
     valid_gpu_backends = {Backend::PDINFER};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
     initialized = Initialize();
   }
 
@@ -109,7 +109,7 @@ class FASTDEPLOY_DECL YOLOv3 : public PPDetBase {
     valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER,
                         Backend::LITE};
     valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
     initialized = Initialize();
   }
 
@@ -127,7 +127,7 @@ class FASTDEPLOY_DECL PaddleYOLOX : public PPDetBase {
     valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER,
                         Backend::LITE};
     valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
     initialized = Initialize();
   }
 
@@ -176,7 +176,7 @@ class FASTDEPLOY_DECL SSD : public PPDetBase {
                 model_format) {
     valid_cpu_backends = {Backend::PDINFER, Backend::LITE};
     valid_gpu_backends = {Backend::PDINFER};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
     initialized = Initialize();
   }
 

fastdeploy/vision/ocr/ppocr/classifier.cc

@@ -32,7 +32,7 @@ Classifier::Classifier(const std::string& model_file,
   } else {
     valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::OPENVINO, Backend::LITE};
     valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
   }
   runtime_option = custom_option;
   runtime_option.model_format = model_format;

fastdeploy/vision/ocr/ppocr/dbdetector.cc

@@ -32,7 +32,7 @@ DBDetector::DBDetector(const std::string& model_file,
   } else {
     valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::OPENVINO, Backend::LITE};
     valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
-    valid_cann_backends = {Backend::LITE};
+    valid_ascend_backends = {Backend::LITE};
   }
 
   runtime_option = custom_option;

fastdeploy/vision/ocr/ppocr/rec_preprocessor.cc

@@ -91,7 +91,7 @@ bool RecognizerPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTenso
       real_index = indices[i];
     }
     FDMat* mat = &(images->at(real_index));
-#if defined(WITH_CANN) || defined(WITH_CANN_PY)
+#if defined(WITH_ASCEND) || defined(WITH_ASCEND_PYTHON)
     OcrRecognizerResizeImageOnAscend(mat, rec_image_shape_); 
 #else
     OcrRecognizerResizeImage(mat, max_wh_ratio, rec_image_shape_);

fastdeploy/vision/ocr/ppocr/recognizer.cc

@@ -34,7 +34,7 @@ Recognizer::Recognizer(const std::string& model_file,
   } else {
     valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::OPENVINO, Backend::LITE};
     valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
-    valid_cann_backends = {Backend::LITE}; 
+    valid_ascend_backends = {Backend::LITE}; 
   }
 
   runtime_option = custom_option;

fastdeploy/vision/segmentation/ppseg/model.cc

@@ -29,7 +29,7 @@ PaddleSegModel::PaddleSegModel(const std::string& model_file,
   valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
   valid_rknpu_backends = {Backend::RKNPU2};
   valid_timvx_backends = {Backend::LITE};
-  valid_cann_backends = {Backend::LITE};
+  valid_ascend_backends = {Backend::LITE};
   runtime_option = custom_option;
   runtime_option.model_format = model_format;
   runtime_option.model_file = model_file;

python/fastdeploy/runtime.py

@@ -283,10 +283,10 @@ class RuntimeOption:
                    rknpu2_core=rknpu2.CoreMask.RKNN_NPU_CORE_0):
         return self._option.use_rknpu2(rknpu2_name, rknpu2_core)
 
-    def use_cann(self):
+    def use_ascend(self):
         """Inference with Huawei Ascend NPU
         """
-        return self._option.use_cann()
+        return self._option.use_ascend()
 
     def set_cpu_thread_num(self, thread_num=-1):
         """Set number of threads if inference with CPU
@@ -342,47 +342,44 @@ class RuntimeOption:
         """
         return self.use_lite_backend()
 
-    def set_lite_nnadapter_device_names(self, device_names):
+    def set_lite_device_names(self, device_names):
         """Set nnadapter device name for Paddle Lite backend.
         """
-        return self._option.set_lite_nnadapter_device_names(device_names)
+        return self._option.set_lite_device_names(device_names)
 
-    def set_lite_nnadapter_context_properties(self, context_properties):
+    def set_lite_context_properties(self, context_properties):
         """Set nnadapter context properties for Paddle Lite backend.
         """
-        return self._option.set_lite_nnadapter_context_properties(
+        return self._option.set_lite_context_properties(context_properties)
-            context_properties)
 
-    def set_lite_nnadapter_model_cache_dir(self, model_cache_dir):
+    def set_lite_model_cache_dir(self, model_cache_dir):
         """Set nnadapter model cache dir for Paddle Lite backend.
         """
-        return self._option.set_lite_nnadapter_model_cache_dir(model_cache_dir)
+        return self._option.set_lite_model_cache_dir(model_cache_dir)
 
-    def set_lite_nnadapter_dynamic_shape_info(self, dynamic_shape_info):
+    def set_lite_dynamic_shape_info(self, dynamic_shape_info):
         """ Set nnadapter dynamic shape info for Paddle Lite backend.
         """
-        return self._option.set_lite_nnadapter_dynamic_shape_info(
+        return self._option.set_lite_dynamic_shape_info(dynamic_shape_info)
-            dynamic_shape_info)
 
-    def set_lite_nnadapter_subgraph_partition_path(self,
+    def set_lite_subgraph_partition_path(self, subgraph_partition_path):
-                                                   subgraph_partition_path):
         """ Set nnadapter subgraph partition path for Paddle Lite backend.
         """
-        return self._option.set_lite_nnadapter_subgraph_partition_path(
+        return self._option.set_lite_subgraph_partition_path(
             subgraph_partition_path)
 
-    def set_lite_nnadapter_subgraph_partition_config_buffer(
+    def set_lite_subgraph_partition_config_buffer(self,
-            self, subgraph_partition_buffer):
+                                                  subgraph_partition_buffer):
         """ Set nnadapter subgraph partition buffer for Paddle Lite backend.
         """
-        return self._option.set_lite_nnadapter_subgraph_partition_config_buffer(
+        return self._option.set_lite_subgraph_partition_config_buffer(
             subgraph_partition_buffer)
 
-    def set_lite_nnadapter_mixed_precision_quantization_config_path(
+    def set_lite_mixed_precision_quantization_config_path(
             self, mixed_precision_quantization_config_path):
         """ Set nnadapter mixed precision quantization config path for Paddle Lite backend..
         """
-        return self._option.set_lite_nnadapter_mixed_precision_quantization_config_path(
+        return self._option.set_lite_mixed_precision_quantization_config_path(
             mixed_precision_quantization_config_path)
 
     def set_paddle_mkldnn(self, use_mkldnn=True):

python/setup.py

@@ -56,8 +56,7 @@ if os.getenv("BUILD_ON_CPU", "OFF") == "ON":
 setup_configs = dict()
 setup_configs["ENABLE_RKNPU2_BACKEND"] = os.getenv("ENABLE_RKNPU2_BACKEND",
                                                    "OFF")
-setup_configs["WITH_CANN"] = os.getenv("WITH_CANN", "OFF")
+setup_configs["WITH_ASCEND_PYTHON"] = os.getenv("WITH_ASCEND_PYTHON", "OFF")
-setup_configs["WITH_CANN_PY"] = os.getenv("WITH_CANN_PY", "OFF")
 setup_configs["ENABLE_ORT_BACKEND"] = os.getenv("ENABLE_ORT_BACKEND", "OFF")
 setup_configs["ENABLE_OPENVINO_BACKEND"] = os.getenv("ENABLE_OPENVINO_BACKEND",
                                                      "OFF")