[Other] Change all XPU to KunlunXin (#973)

* [FlyCV] Bump up FlyCV -> official release 1.0.0

* XPU to KunlunXin

* update

* update model link

* update doc

* update device

* update code

* useless code

Co-authored-by: DefTruth <[email protected]>
Co-authored-by: DefTruth <[email protected]>

CMakeLists.txt

@@ -66,7 +66,7 @@ option(ENABLE_TEXT "Whether to enable text models usage." OFF)
 option(ENABLE_FLYCV "Whether to enable flycv to boost image preprocess." OFF)
 option(WITH_ASCEND "Whether to compile for Huawei Ascend deploy." OFF)
 option(WITH_TIMVX "Whether to compile for TIMVX deploy." OFF)
-option(WITH_XPU "Whether to compile for KunlunXin XPU deploy." OFF)
+option(WITH_KUNLUNXIN "Whether to compile for KunlunXin XPU deploy." OFF)
 option(WITH_TESTING "Whether to compile with unittest." OFF)
 ############################# Options for Android cross compiling #########################
 option(WITH_OPENCV_STATIC "Use OpenCV static lib for Android." OFF)
@@ -148,12 +148,12 @@ if (WITH_ASCEND)
   include(${PROJECT_SOURCE_DIR}/cmake/ascend.cmake)
 endif()
 
-if (WITH_XPU)
+if (WITH_KUNLUNXIN)
   if(NOT ENABLE_LITE_BACKEND)
       set(ENABLE_LITE_BACKEND ON)
   endif()
   if(NOT CMAKE_HOST_SYSTEM_PROCESSOR MATCHES "x86_64")
-    message(FATAL_ERROR "XPU is only supported on Linux x64 platform")
+    message(FATAL_ERROR "KunlunXin XPU is only supported on Linux x64 platform")
   endif()
   if(NOT PADDLELITE_URL)
     set(PADDLELITE_URL "https://bj.bcebos.com/fastdeploy/third_libs/lite-linux-x64-xpu-20221215.tgz")

FastDeploy.cmake.in

@@ -27,7 +27,7 @@ set(OPENCV_DIRECTORY "@OPENCV_DIRECTORY@")
 set(ORT_DIRECTORY "@ORT_DIRECTORY@")
 set(OPENVINO_DIRECTORY "@OPENVINO_DIRECTORY@")
 set(RKNN2_TARGET_SOC "@RKNN2_TARGET_SOC@")
-set(WITH_XPU @WITH_XPU@)
+set(WITH_KUNLUNXIN @WITH_KUNLUNXIN@)
 
 set(FASTDEPLOY_LIBS "")
 set(FASTDEPLOY_INCS "")
@@ -246,7 +246,7 @@ if(ENABLE_PADDLE_FRONTEND)
   list(APPEND FASTDEPLOY_LIBS ${PADDLE2ONNX_LIB})
 endif()
 
-if(WITH_XPU)
+if(WITH_KUNLUNXIN)
   list(APPEND FASTDEPLOY_LIBS -lpthread -lrt -ldl)
 endif()
 

cmake/summary.cmake

@@ -39,7 +39,7 @@ function(fastdeploy_summary)
   message(STATUS "  ENABLE_OPENVINO_BACKEND   : ${ENABLE_OPENVINO_BACKEND}")
   message(STATUS "  WITH_ASCEND               : ${WITH_ASCEND}")
   message(STATUS "  WITH_TIMVX                : ${WITH_TIMVX}")
-  message(STATUS "  WITH_XPU                  : ${WITH_XPU}")
+  message(STATUS "  WITH_KUNLUNXIN            : ${WITH_KUNLUNXIN}")
   if(ENABLE_ORT_BACKEND)
     message(STATUS "  ONNXRuntime version       : ${ONNXRUNTIME_VERSION}")
   endif()

docs/README.md

@@ -8,7 +8,7 @@
 - [Build and Install FastDeploy Library on GPU Platform](en/build_and_install/gpu.md)
 - [Build and Install FastDeploy Library on CPU Platform](en/build_and_install/cpu.md)
 - [Build and Install FastDeploy Library on IPU Platform](en/build_and_install/ipu.md)
-- [Build and Install FastDeploy Library on KunlunXin XPU Platform](en/build_and_install/xpu.md)
+- [Build and Install FastDeploy Library on KunlunXin XPU Platform](en/build_and_install/kunlunxin.md)
 - [Build and Install on RV1126 Platform](en/build_and_install/rv1126.md)
 - [Build and Install on RK3588 and RK356X Platform](en/build_and_install/rknpu2.md)
 - [Build and Install on A311D Platform](en/build_and_install/a311d.md)

docs/README_CN.md

@@ -8,7 +8,7 @@
 - [GPU部署环境编译安装](cn/build_and_install/gpu.md)
 - [CPU部署环境编译安装](cn/build_and_install/cpu.md)
 - [IPU部署环境编译安装](cn/build_and_install/ipu.md)
-- [昆仑芯XPU部署环境编译安装](cn/build_and_install/xpu.md)
+- [昆仑芯XPU部署环境编译安装](cn/build_and_install/kunlunxin.md)
 - [瑞芯微RV1126部署环境编译安装](cn/build_and_install/rv1126.md)
 - [瑞芯微RK3588部署环境编译安装](cn/build_and_install/rknpu2.md)
 - [晶晨A311D部署环境编译安装](cn/build_and_install/a311d.md)

docs/README_EN.md

@@ -8,7 +8,7 @@
 - [Build and Install FastDeploy Library on GPU Platform](en/build_and_install/gpu.md)
 - [Build and Install FastDeploy Library on CPU Platform](en/build_and_install/cpu.md)
 - [Build and Install FastDeploy Library on IPU Platform](en/build_and_install/ipu.md)
-- [Build and Install FastDeploy Library on KunlunXin XPU Platform](en/build_and_install/xpu.md)
+- [Build and Install FastDeploy Library on KunlunXin XPU Platform](en/build_and_install/kunlunxin.md)
 - [Build and Install on RV1126 Platform](en/build_and_install/rv1126.md)
 - [Build and Install on RK3588 Platform](en/build_and_install/rknpu2.md)
 - [Build and Install on A311D Platform](en/build_and_install/a311d.md)

docs/cn/build_and_install/README.md

@@ -14,7 +14,7 @@
 - [瑞芯微RV1126部署环境](rv1126.md)
 - [瑞芯微RK3588部署环境](rknpu2.md)
 - [晶晨A311D部署环境](a311d.md)
-- [昆仑芯XPU部署环境](xpu.md)
+- [昆仑芯XPU部署环境](kunlunxin.md)
 - [华为昇腾部署环境](huawei_ascend.md)
 
 
@@ -27,7 +27,7 @@
 | 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_ASCEND             | 默认OFF，当在华为昇腾NPU上部署时, 需要设置为ON                                              |
-| WITH_XPU                | 默认OFF，当在昆仑芯XPU上部署时，需设置为ON                                                |
+| WITH_KUNLUNXIN          | 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                                   |
 | ENABLE_TRT_BACKEND      | 默认OFF，是否编译集成TensorRT后端(GPU上推荐打开)                                          |
 | ENABLE_OPENVINO_BACKEND | 默认OFF，是否编译集成OpenVINO后端(CPU上推荐打开)                                          |

docs/cn/build_and_install/xpu.md → docs/cn/build_and_install/kunlunxin.md

@@ -1,4 +1,4 @@
-[English](../../en/build_and_install/xpu.md) | 简体中文
+[English](../../en/build_and_install/kunlunxin.md) | 简体中文
 
 # 昆仑芯 XPU 部署环境编译安装
 
@@ -10,7 +10,7 @@ FastDeploy 基于 Paddle Lite 后端支持在昆仑芯 XPU 上进行部署推理
 相关编译选项说明如下：  
 |编译选项|默认值|说明|备注|  
 |:---|:---|:---|:---|  
-| WITH_XPU| OFF | 需要在XPU上部署时需要设置为ON | - |
+| WITH_KUNLUNXIN| OFF | 需要在昆仑芯XPU上部署时需要设置为ON | - |
 | ENABLE_ORT_BACKEND | OFF | 是否编译集成ONNX Runtime后端 | - |
 | ENABLE_PADDLE_BACKEND | OFF | 是否编译集成Paddle Inference后端 | - |
 | ENABLE_OPENVINO_BACKEND | OFF | 是否编译集成OpenVINO后端 | - |
@@ -41,11 +41,11 @@ cd FastDeploy
 mkdir build && cd build
 
 # CMake configuration with KunlunXin xpu toolchain
-cmake -DWITH_XPU=ON  \
+cmake -DWITH_KUNLUNXIN=ON  \
       -DWITH_GPU=OFF  \ # 不编译 GPU
       -DENABLE_ORT_BACKEND=ON  \ # 可选择开启 ORT 后端
       -DENABLE_PADDLE_BACKEND=ON  \ # 可选择开启 Paddle 后端
-      -DCMAKE_INSTALL_PREFIX=fastdeploy-xpu \
+      -DCMAKE_INSTALL_PREFIX=fastdeploy-kunlunxin \
       -DENABLE_VISION=ON \ # 是否编译集成视觉模型的部署模块，可选择开启
       -DOPENCV_DIRECTORY=/usr/lib/x86_64-linux-gnu/cmake/opencv4 \
       ..
@@ -54,14 +54,14 @@ cmake -DWITH_XPU=ON  \
 make -j8
 make install
 ```  
-编译完成之后，会生成 fastdeploy-xpu 目录，表示基于 Paddle Lite 的 FastDeploy 库编译完成。
+编译完成之后，会生成 fastdeploy-kunlunxin 目录，表示基于 Paddle Lite 的 FastDeploy 库编译完成。
 
 ## Python 编译
 编译命令如下：
 ```bash
 git clone https://github.com/PaddlePaddle/FastDeploy.git
 cd FastDeploy/python
-export WITH_XPU=ON
+export WITH_KUNLUNXIN=ON
 export WITH_GPU=OFF
 export ENABLE_ORT_BACKEND=ON
 export ENABLE_PADDLE_BACKEND=ON

docs/en/build_and_install/README.md

@@ -15,7 +15,7 @@ English | [中文](../../cn/build_and_install/README.md)
 - [Build and Install on RV1126 Platform](rv1126.md)
 - [Build and Install on RK3588 Platform](rknpu2.md)
 - [Build and Install on A311D Platform](a311d.md)
-- [Build and Install on KunlunXin XPU Platform](xpu.md)
+- [Build and Install on KunlunXin XPU Platform](kunlunxin.md)
 
 
 ## Build options
@@ -29,7 +29,7 @@ English | [中文](../../cn/build_and_install/README.md)
 | ENABLE_VISION | Default OFF，whether to enable vision models deployment module |
 | ENABLE_TEXT | Default OFF，whether to enable text models deployment module |
 | WITH_GPU | Default OFF, if build on GPU, this needs to be ON |
-| WITH_XPU | Default OFF，if deploy on KunlunXin XPU，this needs to be ON |
+| WITH_KUNLUNXIN | Default OFF，if deploy on KunlunXin XPU，this needs to be ON |
 | WITH_TIMVX | Default OFF，if deploy on RV1126/RV1109/A311D，this needs to be ON |
 | WITH_ASCEND | Default OFF，if deploy on Huawei Ascend，this needs to be ON |
 | CUDA_DIRECTORY | Default /usr/local/cuda, if build on GPU, this defines the path of CUDA(>=11.2) |

docs/en/build_and_install/xpu.md → docs/en/build_and_install/kunlunxin.md

@@ -1,4 +1,4 @@
-English | [中文](../../cn/build_and_install/xpu.md)
+English | [中文](../../cn/build_and_install/kunlunxin.md)
 
 # How to Build KunlunXin XPU Deployment Environment
 
@@ -10,7 +10,7 @@ The relevant compilation options are described as follows:
 |Compile Options|Default Values|Description|Remarks|  
 |:---|:---|:---|:---|  
 | ENABLE_LITE_BACKEND | OFF | It needs to be set to ON when compiling the RK library| - |  
-| WITH_XPU | OFF | It needs to be set to ON when compiling the KunlunXin XPU library| - |
+| WITH_KUNLUNXIN | OFF | It needs to be set to ON when compiling the KunlunXin XPU library| - |
 | ENABLE_ORT_BACKEND | OFF | whether to intergrate ONNX Runtime backend | - |
 | ENABLE_PADDLE_BACKEND | OFF | whether to intergrate Paddle Inference backend | - |
 | ENABLE_OPENVINO_BACKEND | OFF | whether to intergrate OpenVINO backend | - |
@@ -44,11 +44,11 @@ cd FastDeploy
 mkdir build && cd build
 
 # CMake configuration with KunlunXin xpu toolchain
-cmake -DWITH_XPU=ON  \
+cmake -DWITH_KUNLUNXIN=ON  \
       -DWITH_GPU=OFF  \
       -DENABLE_ORT_BACKEND=ON  \
       -DENABLE_PADDLE_BACKEND=ON  \
-      -DCMAKE_INSTALL_PREFIX=fastdeploy-xpu \
+      -DCMAKE_INSTALL_PREFIX=fastdeploy-kunlunxin \
       -DENABLE_VISION=ON \
       -DOPENCV_DIRECTORY=/usr/lib/x86_64-linux-gnu/cmake/opencv4 \
       ..
@@ -57,14 +57,14 @@ cmake -DWITH_XPU=ON  \
 make -j8
 make install
 ```  
-After the compilation is complete, the fastdeploy-xpu directory will be generated, indicating that the Padddle Lite based FastDeploy library has been compiled.
+After the compilation is complete, the fastdeploy-kunlunxin directory will be generated, indicating that the Padddle Lite based FastDeploy library has been compiled.
 
 ## Python compile
 The compilation command is as follows:
 ```bash
 git clone https://github.com/PaddlePaddle/FastDeploy.git
 cd FastDeploy/python
-export WITH_XPU=ON
+export WITH_KUNLUNXIN=ON
 export WITH_GPU=OFF
 export ENABLE_ORT_BACKEND=ON
 export ENABLE_PADDLE_BACKEND=ON

examples/multimodal/stable_diffusion/README.md

@@ -41,7 +41,7 @@ python infer.py --model_dir stable-diffusion-v1-4/ --scheduler "pndm" --backend
 python infer.py --model_dir stable-diffusion-v1-5/ --scheduler "euler_ancestral" --backend paddle
 
 # 在昆仑芯XPU上推理
-python infer.py --model_dir stable-diffusion-v1-5/ --scheduler "euler_ancestral" --backend paddle-xpu
+python infer.py --model_dir stable-diffusion-v1-5/ --scheduler "euler_ancestral" --backend paddle-kunlunxin
 ```
 
 #### 参数说明
@@ -52,7 +52,7 @@ python infer.py --model_dir stable-diffusion-v1-5/ --scheduler "euler_ancestral"
 |----------|--------------|
 | --model_dir | 导出后模型的目录。 |
 | --model_format | 模型格式。默认为`'paddle'`，可选列表：`['paddle', 'onnx']`。 |
-| --backend | 推理引擎后端。默认为`paddle`，可选列表：`['onnx_runtime', 'paddle', 'paddle-xpu']`，当模型格式为`onnx`时，可选列表为`['onnx_runtime']`。 |
+| --backend | 推理引擎后端。默认为`paddle`，可选列表：`['onnx_runtime', 'paddle', 'paddle-kunlunxin']`，当模型格式为`onnx`时，可选列表为`['onnx_runtime']`。 |
 | --scheduler | StableDiffusion 模型的scheduler。默认为`'pndm'`。可选列表：`['pndm', 'euler_ancestral']`，StableDiffusio模型对应的scheduler可参考[ppdiffuser模型列表](https://github.com/PaddlePaddle/PaddleNLP/tree/develop/ppdiffusers/examples/textual_inversion)。|
 | --unet_model_prefix | UNet模型前缀。默认为`unet`。 |
 | --vae_model_prefix | VAE模型前缀。默认为`vae_decoder`。 |

examples/multimodal/stable_diffusion/infer.py

@@ -69,7 +69,7 @@ def parse_arguments():
         type=str,
         default='paddle',
         # Note(zhoushunjie): Will support 'tensorrt', 'paddle-tensorrt' soon.
-        choices=['onnx_runtime', 'paddle', 'paddle-xpu'],
+        choices=['onnx_runtime', 'paddle', 'paddle-kunlunxin'],
         help="The inference runtime backend of unet model and text encoder model."
     )
     parser.add_argument(
@@ -175,9 +175,9 @@ def create_trt_runtime(model_dir,
     return fd.Runtime(option)
 
 
-def create_xpu_runtime(model_dir, model_prefix, device_id=0):
+def create_kunlunxin_runtime(model_dir, model_prefix, device_id=0):
     option = fd.RuntimeOption()
-    option.use_xpu(
+    option.use_kunlunxin(
         device_id,
         l3_workspace_size=(64 * 1024 * 1024 - 4 * 1024),
         locked=False,
@@ -306,18 +306,18 @@ def get_scheduler(args):
             dynamic_shape=unet_dynamic_shape,
             device_id=args.device_id)
         print(f"Spend {time.time() - start : .2f} s to load unet model.")
-    elif args.backend == "paddle-xpu":
+    elif args.backend == "paddle-kunlunxin":
         print("=== build text_encoder_runtime")
-        text_encoder_runtime = create_xpu_runtime(
+        text_encoder_runtime = create_kunlunxin_runtime(
             args.model_dir,
             args.text_encoder_model_prefix,
             device_id=args.device_id)
         print("=== build vae_decoder_runtime")
-        vae_decoder_runtime = create_xpu_runtime(
+        vae_decoder_runtime = create_kunlunxin_runtime(
             args.model_dir, args.vae_model_prefix, device_id=args.device_id)
         print("=== build unet_runtime")
         start = time.time()
-        unet_runtime = create_xpu_runtime(
+        unet_runtime = create_kunlunxin_runtime(
             args.model_dir, args.unet_model_prefix, device_id=args.device_id)
         print(f"Spend {time.time() - start : .2f} s to load unet model.")
     pipe = StableDiffusionFastDeployPipeline(

examples/text/ernie-3.0/cpp/README.md

@@ -35,8 +35,8 @@ tar xvfz ernie-3.0-medium-zh-afqmc.tgz
 # GPU Inference
 ./seq_cls_infer_demo --device gpu --model_dir ernie-3.0-medium-zh-afqmc
 
-# XPU 推理
-./seq_cls_infer_demo --device xpu --model_dir ernie-3.0-medium-zh-afqmc
+# KunlunXin XPU 推理
+./seq_cls_infer_demo --device kunlunxin --model_dir ernie-3.0-medium-zh-afqmc
 ```
 The result returned after running is as follows：
 ```bash

examples/text/ernie-3.0/cpp/seq_cls_infer.cc

@@ -32,7 +32,7 @@ const char sep = '/';
 DEFINE_string(model_dir, "", "Directory of the inference model.");
 DEFINE_string(vocab_path, "", "Path of the vocab file.");
 DEFINE_string(device, "cpu",
-              "Type of inference device, support 'cpu', 'xpu' or 'gpu'.");
+              "Type of inference device, support 'cpu', 'kunlunxin' or 'gpu'.");
 DEFINE_string(backend, "onnx_runtime",
               "The inference runtime backend, support: ['onnx_runtime', "
               "'paddle', 'openvino', 'tensorrt', 'paddle_tensorrt']");
@@ -61,8 +61,8 @@ bool CreateRuntimeOption(fastdeploy::RuntimeOption* option) {
                      << ", param_path = " << param_path << std::endl;
   option->SetModelPath(model_path, param_path);
 
-  if (FLAGS_device == "xpu") {
-    option->UseXpu();
+  if (FLAGS_device == "kunlunxin") {
+    option->UseKunlunXin();
     return true;
   } else if (FLAGS_device == "gpu") {
     option->UseGpu();

examples/text/ernie-3.0/python/README.md

@@ -40,8 +40,8 @@ python seq_cls_infer.py --device cpu --model_dir ernie-3.0-medium-zh-afqmc
 # GPU Inference
 python seq_cls_infer.py --device gpu --model_dir ernie-3.0-medium-zh-afqmc
 
-# XPU Inference
-python seq_cls_infer.py --device xpu --model_dir ernie-3.0-medium-zh-afqmc
+# KunlunXin XPU Inference
+python seq_cls_infer.py --device kunlunxin --model_dir ernie-3.0-medium-zh-afqmc
 
 ```
 The result returned after running is as follows:

examples/text/ernie-3.0/python/seq_cls_infer.py

@@ -35,8 +35,8 @@ def parse_arguments():
         "--device",
         type=str,
         default='cpu',
-        choices=['gpu', 'cpu', 'xpu'],
-        help="Type of inference device, support 'cpu', 'xpu' or 'gpu'.")
+        choices=['gpu', 'cpu', 'kunlunxin'],
+        help="Type of inference device, support 'cpu', 'kunlunxin' or 'gpu'.")
     parser.add_argument(
         "--backend",
         type=str,
@@ -94,8 +94,8 @@ def create_fd_runtime(self, args):
         model_path = os.path.join(args.model_dir, "infer.pdmodel")
         params_path = os.path.join(args.model_dir, "infer.pdiparams")
         option.set_model_path(model_path, params_path)
-        if args.device == 'xpu':
-            option.use_xpu()
+        if args.device == 'kunlunxin':
+            option.use_kunlunxin()
             option.use_paddle_lite_backend()
             return fd.Runtime(option)
         if args.device == 'cpu':

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

@@ -96,13 +96,13 @@ void IpuInfer(const std::string& model_dir, const std::string& image_file) {
   std::cout << res.Str() << std::endl;
 }
 
-void XpuInfer(const std::string& model_dir, const std::string& image_file) {
+void KunlunXinInfer(const std::string& model_dir, const std::string& image_file) {
   auto model_file = model_dir + sep + "inference.pdmodel";
   auto params_file = model_dir + sep + "inference.pdiparams";
   auto config_file = model_dir + sep + "inference_cls.yaml";
 
   auto option = fastdeploy::RuntimeOption();
-  option.UseXpu();
+  option.UseKunlunXin();
   auto model = fastdeploy::vision::classification::PaddleClasModel(
       model_file, params_file, config_file, option);
   if (!model.Initialized()) {
@@ -179,7 +179,7 @@ int main(int argc, char* argv[]) {
                  "e.g ./infer_demo ./ResNet50_vd ./test.jpeg 0"
               << std::endl;
     std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
-                 "with gpu; 2: run with gpu and use tensorrt backend; 3: run with ipu; 4: run with xpu."
+                 "with gpu; 2: run with gpu and use tensorrt backend; 3: run with ipu; 4: run with kunlunxin."
               << std::endl;
     return -1;
   }
@@ -193,7 +193,7 @@ int main(int argc, char* argv[]) {
   } else if (std::atoi(argv[3]) == 3) {
     IpuInfer(argv[1], argv[2]);
   } else if (std::atoi(argv[3]) == 4) {
-    XpuInfer(argv[1], argv[2]);
+    KunlunXinInfer(argv[1], argv[2]);
   } else if (std::atoi(argv[3]) == 5) {
     AscendInfer(argv[1], argv[2]);
   }

examples/vision/classification/paddleclas/python/README.md

@@ -25,8 +25,8 @@ python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg -
 python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device gpu --use_trt True --topk 1
 # IPU推理（注意：IPU推理首次运行会有序列化模型的操作，有一定耗时，需要耐心等待）
 python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device ipu --topk 1
-# XPU推理
-python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device xpu --topk 1
+# 昆仑芯XPU推理
+python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device kunlunxin --topk 1
 # 华为昇腾NPU推理
 python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device ascend --topk 1
 ```

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

@@ -17,7 +17,7 @@ def parse_arguments():
         "--device",
         type=str,
         default='cpu',
-        help="Type of inference device, support 'cpu' or 'gpu' or 'ipu' or 'xpu' or 'ascend' ."
+        help="Type of inference device, support 'cpu' or 'gpu' or 'ipu' or 'kunlunxin' or 'ascend' ."
     )
     parser.add_argument(
         "--use_trt",
@@ -36,8 +36,8 @@ def build_option(args):
     if args.device.lower() == "ipu":
         option.use_ipu()
 
-    if args.device.lower() == "xpu":
-        option.use_xpu()
+    if args.device.lower() == "kunlunxin":
+        option.use_kunlunxin()
 
     if args.device.lower() == "ascend":
         option.use_ascend()