fix GPUID setting and LOG_PATH

deploy/slim/quant_post_static.py

@@ -41,6 +41,8 @@ def main():
                      'inference.pdmodel')) and os.path.exists(
                          os.path.join(config["Global"]["save_inference_dir"],
                                       'inference.pdiparams'))
+    if "Query" in config["DataLoader"]["Eval"]:
+        config["DataLoader"]["Eval"] = config["DataLoader"]["Eval"]["Query"]
     config["DataLoader"]["Eval"]["sampler"]["batch_size"] = 1
     config["DataLoader"]["Eval"]["loader"]["num_workers"] = 0
 

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_serving/
+--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_serving/
+--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPHGNet_small_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./PPHGNet_small_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPHGNet_small_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPHGNet_small_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPLCNet_x1_0_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./PPLCNet_x1_0_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNet_x1_0_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNet_x1_0_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPLCNetV2_base_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./PPLCNetV2_base_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNetV2_base_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNetV2_base_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_kl_quant_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:SwinTransformer_tiny_patch4_window7_224_KL
+cpp_infer_type:cls
+cls_inference_model_dir:./SwinTransformer_tiny_patch4_window7_224_kl_quant_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer.tar
+det_inference_url:
+infer_quant:False
+inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
+use_gpu:True|False
+enable_mkldnn:False
+cpu_threads:1
+batch_size:1
+use_tensorrt:False
+precision:fp32
+image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
+benchmark:False
+generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:SwinTransformer_tiny_patch4_window7_224_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_serving/
+--serving_client:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:SwinTransformer_tiny_patch4_window7_224_KL
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_serving/
+--serving_client:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/docs/test_inference_cpp.md

@@ -7,26 +7,30 @@ Linux GPU/CPU C++ 推理功能测试的主程序为`test_inference_cpp.sh`，可
 - 推理相关：
 
 |    算法名称     |                  模型名称                  | device_CPU | device_GPU |
-| :-------------: | :---------------------------------------: | :--------: | :--------: |
+| :-------------: | :----------------------------------------: | :--------: | :--------: |
 |   MobileNetV3   |           MobileNetV3_large_x1_0           |    支持    |    支持    |
 |   MobileNetV3   |         MobileNetV3_large_x1_0_KL          |    支持    |    支持    |
 |    PP-ShiTu     | PPShiTu_general_rec、PPShiTu_mainbody_det  |    支持    |    支持    |
-|    PP-ShiTu     |           PPShiTu_mainbody_det            |    支持    |    支持    |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5_KL     |    支持    |    支持    |
 |     PPHGNet     |               PPHGNet_small                |    支持    |    支持    |
+|     PPHGNet     |              PPHGNet_small_KL              |    支持    |    支持    |
 |     PPHGNet     |                PPHGNet_tiny                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_25                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_35                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x0_5                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_75                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x1_0                |    支持    |    支持    |
+|     PPLCNet     |              PPLCNet_x1_0_KL               |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x1_5                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x2_0                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x2_5                |    支持    |    支持    |
 |    PPLCNetV2    |               PPLCNetV2_base               |    支持    |    支持    |
+|    PPLCNetV2    |             PPLCNetV2_base_KL              |    支持    |    支持    |
 |     ResNet      |                  ResNet50                  |    支持    |    支持    |
 |     ResNet      |                ResNet50_vd                 |    支持    |    支持    |
 |     ResNet      |               ResNet50_vd_KL               |    支持    |    支持    |
 | SwinTransformer |  SwinTransformer_tiny_patch4_window7_224   |    支持    |    支持    |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_KL |    支持    |    支持    |
 
 ## 2. 测试流程(以**ResNet50**为例)
 
@@ -244,20 +248,20 @@ bash test_tipc/prepare.sh test_tipc/config/ResNet/ResNet50_linux_gpu_normal_norm
 测试方法如下所示，希望测试不同的模型文件，只需更换为自己的参数配置文件，即可完成对应模型的测试。
 
 ```shell
-bash test_tipc/test_inference_cpp.sh ${your_params_file}
+bash test_tipc/test_inference_cpp.sh ${your_params_file} cpp_infer
 ```
 
 以`ResNet50`的`Linux GPU/CPU C++推理测试`为例，命令如下所示。
 
 ```shell
-bash test_tipc/test_inference_cpp.sh test_tipc/config/ResNet/ResNet50_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
+bash test_tipc/test_inference_cpp.sh test_tipc/config/ResNet/ResNet50_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt cpp_infer
 ```
 
 输出结果如下，表示命令运行成功。
 
 ```shell
-Run successfully with command - ./deploy/cpp/build/clas_system -c inference_cls.yaml > ./test_tipc/output/ResNet50/cls_cpp_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log 2>&1!
-Run successfully with command - ./deploy/cpp/build/clas_system -c inference_cls.yaml > ./test_tipc/output/ResNet50/cls_cpp_infer_cpu_usemkldnn_False_threads_1_precision_fp32_batchsize_1.log 2>&1!
+Run successfully with command - ResNet50 - ./deploy/cpp/build/clas_system -c inference_cls.yaml > ./test_tipc/output/ResNet50/cpp_infer/cpp_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log 2>&1!
+Run successfully with command - ResNet50 - ./deploy/cpp/build/clas_system -c inference_cls.yaml > ./test_tipc/output/ResNet50/cpp_infer/cpp_infer_cpu_usemkldnn_False_threads_1_precision_fp32_batchsize_1.log 2>&1!
 ```
 
 最终log中会打印出结果，如下所示
@@ -308,6 +312,6 @@ Current total inferen time cost: 5449.39 ms.
     Top5: class_id: 265, score: 0.0420, label: toy poodle
 
 ```
-详细log位于`./test_tipc/output/ResNet50/cls_cpp_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log`和`./test_tipc/output/ResNet50/cls_cpp_infer_cpu_usemkldnn_False_threads_1_precision_fp32_batchsize_1.log`中。
+详细log位于`./test_tipc/output/ResNet50/cpp_infer/cpp_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log`和`./test_tipc/output/ResNet50/cpp_infer_cpu_usemkldnn_False_threads_1_precision_fp32_batchsize_1.log`中。
 
 如果运行失败，也会在终端中输出运行失败的日志信息以及对应的运行命令。可以基于该命令，分析运行失败的原因。

test_tipc/docs/test_serving_infer_cpp.md

@@ -8,25 +8,30 @@ Linux GPU/CPU C++ 服务化部署测试的主程序为`test_serving_infer_cpp.sh
 - 推理相关：
 
 |    算法名称     |                  模型名称                  | device_CPU | device_GPU |
-| :-------------: | :---------------------------------------: | :--------: | :--------: |
+| :-------------: | :----------------------------------------: | :--------: | :--------: |
 |   MobileNetV3   |           MobileNetV3_large_x1_0           |    支持    |    支持    |
 |   MobileNetV3   |         MobileNetV3_large_x1_0_KL          |    支持    |    支持    |
 |    PP-ShiTu     | PPShiTu_general_rec、PPShiTu_mainbody_det  |    支持    |    支持    |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5_KL     |    支持    |    支持    |
 |     PPHGNet     |               PPHGNet_small                |    支持    |    支持    |
+|     PPHGNet     |              PPHGNet_small_KL              |    支持    |    支持    |
 |     PPHGNet     |                PPHGNet_tiny                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_25                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_35                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x0_5                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_75                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x1_0                |    支持    |    支持    |
+|     PPLCNet     |              PPLCNet_x1_0_KL               |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x1_5                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x2_0                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x2_5                |    支持    |    支持    |
 |    PPLCNetV2    |               PPLCNetV2_base               |    支持    |    支持    |
+|    PPLCNetV2    |             PPLCNetV2_base_KL              |    支持    |    支持    |
 |     ResNet      |                  ResNet50                  |    支持    |    支持    |
 |     ResNet      |                ResNet50_vd                 |    支持    |    支持    |
 |     ResNet      |               ResNet50_vd_KL               |    支持    |    支持    |
 | SwinTransformer |  SwinTransformer_tiny_patch4_window7_224   |    支持    |    支持    |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_KL |    支持    |    支持    |
 
 
 ## 2. 测试流程

test_tipc/docs/test_serving_infer_python.md

@@ -8,25 +8,30 @@ Linux GPU/CPU PYTHON 服务化部署测试的主程序为`test_serving_infer_pyt
 - 推理相关：
 
 |    算法名称     |                  模型名称                  | device_CPU | device_GPU |
-| :-------------: | :---------------------------------------: | :--------: | :--------: |
+| :-------------: | :----------------------------------------: | :--------: | :--------: |
 |   MobileNetV3   |           MobileNetV3_large_x1_0           |    支持    |    支持    |
 |   MobileNetV3   |         MobileNetV3_large_x1_0_KL          |    支持    |    支持    |
 |    PP-ShiTu     | PPShiTu_general_rec、PPShiTu_mainbody_det  |    支持    |    支持    |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5_KL     |    支持    |    支持    |
 |     PPHGNet     |               PPHGNet_small                |    支持    |    支持    |
+|     PPHGNet     |              PPHGNet_small_KL              |    支持    |    支持    |
 |     PPHGNet     |                PPHGNet_tiny                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_25                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_35                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x0_5                |    支持    |    支持    |
 |     PPLCNet     |               PPLCNet_x0_75                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x1_0                |    支持    |    支持    |
+|     PPLCNet     |              PPLCNet_x1_0_KL               |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x1_5                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x2_0                |    支持    |    支持    |
 |     PPLCNet     |                PPLCNet_x2_5                |    支持    |    支持    |
 |    PPLCNetV2    |               PPLCNetV2_base               |    支持    |    支持    |
+|    PPLCNetV2    |             PPLCNetV2_base_KL              |    支持    |    支持    |
 |     ResNet      |                  ResNet50                  |    支持    |    支持    |
 |     ResNet      |                ResNet50_vd                 |    支持    |    支持    |
 |     ResNet      |               ResNet50_vd_KL               |    支持    |    支持    |
 | SwinTransformer |  SwinTransformer_tiny_patch4_window7_224   |    支持    |    支持    |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_KL |    支持    |    支持    |
 
 
 ## 2. 测试流程

test_tipc/prepare.sh

@@ -208,7 +208,7 @@ fi
 if [[ ${MODE} = "serving_infer" ]]; then
     # prepare serving env
     python_name=$(func_parser_value "${lines[2]}")
-    if [[ ${model_name} =~ "ShiTu" ]]; then
+    if [[ ${model_name} = "PPShiTu" ]]; then
         cls_inference_model_url=$(func_parser_value "${lines[3]}")
         cls_tar_name=$(func_get_url_file_name "${cls_inference_model_url}")
         det_inference_model_url=$(func_parser_value "${lines[4]}")

test_tipc/test_inference_cpp.sh

@@ -63,7 +63,7 @@ function func_shitu_cpp_inference(){
                         if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then
                             precison="int8"
                         fi
-                        _save_log_path="${_log_path}/shitu_cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
+                        _save_log_path="${_log_path}/cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
                         eval $transform_index_cmd
                         command="${generate_yaml_cmd} --type shitu --batch_size ${batch_size} --mkldnn ${use_mkldnn} --gpu ${use_gpu} --cpu_thread ${threads} --tensorrt False --precision ${precision} --data_dir ${_img_dir} --benchmark True --cls_model_dir ${cpp_infer_model_dir} --det_model_dir ${cpp_det_infer_model_dir} --gpu_id ${GPUID}"
                         eval $command
@@ -87,7 +87,7 @@ function func_shitu_cpp_inference(){
                         continue
                     fi
                     for batch_size in ${cpp_batch_size_list[*]}; do
-                        _save_log_path="${_log_path}/shitu_cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
+                        _save_log_path="${_log_path}/cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
                         eval $transform_index_cmd
                         command="${generate_yaml_cmd} --type shitu --batch_size ${batch_size} --mkldnn False --gpu ${use_gpu} --cpu_thread 1 --tensorrt ${use_trt} --precision ${precision} --data_dir ${_img_dir} --benchmark True --cls_model_dir ${cpp_infer_model_dir} --det_model_dir ${cpp_det_infer_model_dir} --gpu_id ${GPUID}"
                         eval $command
@@ -125,7 +125,7 @@ function func_cls_cpp_inference(){
                         if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then
                             precison="int8"
                         fi
-                        _save_log_path="${_log_path}/cls_cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
+                        _save_log_path="${_log_path}/cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
 
                         command="${generate_yaml_cmd} --type cls --batch_size ${batch_size} --mkldnn ${use_mkldnn} --gpu ${use_gpu} --cpu_thread ${threads} --tensorrt False --precision ${precision} --data_dir ${_img_dir} --benchmark True --cls_model_dir ${cpp_infer_model_dir} --gpu_id ${GPUID}"
                         eval $command
@@ -149,7 +149,7 @@ function func_cls_cpp_inference(){
                         continue
                     fi
                     for batch_size in ${cpp_batch_size_list[*]}; do
-                        _save_log_path="${_log_path}/cls_cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
+                        _save_log_path="${_log_path}/cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
                         command="${generate_yaml_cmd} --type cls --batch_size ${batch_size} --mkldnn False --gpu ${use_gpu} --cpu_thread 1 --tensorrt ${use_trt} --precision ${precision} --data_dir ${_img_dir} --benchmark True --cls_model_dir ${cpp_infer_model_dir} --gpu_id ${GPUID}"
                         eval $command
                         command="${_script} > ${_save_log_path} 2>&1"

test_tipc/test_serving_infer_python.sh

@@ -310,7 +310,7 @@ echo "################### run test ###################"
 
 export Count=0
 IFS="|"
-if [[ ${model_name} =~ "ShiTu" ]]; then
+if [[ ${model_name} = "PPShiTu" ]]; then
     func_serving_rec
 else
     func_serving_cls