Merge pull request #4690 from LDOUBLEV/test_v11

rename ppocr_det_mobile  to ch_ppocr_mobile_v2.0_det

test_tipc/configs/ch_ppocr_mobile_V2.0_det_FPGM/train_infer_python.txt

+===========================train_params===========================
+model_name:ocr_det
+python:python3.7
+gpu_list:0|0,1
+Global.use_gpu:True|True
+Global.auto_cast:null
+Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300
+Global.save_model_dir:./output/
+Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4
+Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
+null:null
+##
+trainer:fpgm_train
+norm_train:null
+pact_train:null
+fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:null
+null:null
+##
+===========================infer_params===========================
+Global.save_inference_dir:./output/
+Global.pretrained_model:
+norm_export:null
+quant_export:null
+fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o 
+distill_export:null
+export1:null
+export2:null
+inference_dir:null
+train_model:null
+infer_export:null
+infer_quant:False
+inference:tools/infer/predict_det.py
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16|int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+null:null
\ No newline at end of file

test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt

@@ -12,10 +12,10 @@ train_model_name:latest
 train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
 null:null
 ##
-trainer:norm_train|pact_train|fpgm_train
+trainer:norm_train
 norm_train:tools/train.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
-pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o
-fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy
+pact_train:null
+fpgm_train:null
 distill_train:null
 null:null
 null:null
@@ -28,8 +28,8 @@ null:null
 Global.save_inference_dir:./output/
 Global.pretrained_model:
 norm_export:tools/export_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o 
-quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o 
-fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o 
+quant_export:null
+fpgm_export:null
 distill_export:null
 export1:null
 export2:null

test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt

@@ -49,53 +49,3 @@ inference:tools/infer/predict_det.py
 null:null
 --benchmark:True
 null:null
-===========================cpp_infer_params===========================
-use_opencv:True
-infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
-infer_quant:False
-inference:./deploy/cpp_infer/build/ppocr det
---use_gpu:False
---enable_mkldnn:False
---cpu_threads:1|6
---rec_batch_num:1
---use_tensorrt:False
---precision:fp32
---det_model_dir:
---image_dir:./inference/ch_det_data_50/all-sum-510/
-null:null
---benchmark:True
-===========================serving_params===========================
-model_name:ocr_det
-python:python3.7
-trans_model:-m paddle_serving_client.convert
---dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
---model_filename:inference.pdmodel
---params_filename:inference.pdiparams
---serving_server:./deploy/pdserving/ppocr_det_mobile_2.0_serving/
---serving_client:./deploy/pdserving/ppocr_det_mobile_2.0_client/
-serving_dir:./deploy/pdserving
-web_service:web_service_det.py --config=config.yml --opt op.det.concurrency=1
-op.det.local_service_conf.devices:null|0
-op.det.local_service_conf.use_mkldnn:True|False
-op.det.local_service_conf.thread_num:1|6
-op.det.local_service_conf.use_trt:False|True
-op.det.local_service_conf.precision:fp32|fp16|int8
-pipline:pipeline_http_client.py|pipeline_rpc_client.py
---image_dir=../../doc/imgs
-===========================kl_quant_params===========================
-infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
-infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
-infer_quant:True
-inference:tools/infer/predict_det.py
---use_gpu:False
---enable_mkldnn:False
---cpu_threads:1|6
---rec_batch_num:1
---use_tensorrt:False
---precision:int8
---det_model_dir:
---image_dir:./inference/ch_det_data_50/all-sum-510/
-null:null
---benchmark:True
-null:null
-null:null

test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt

+===========================kl_quant_params===========================
+infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
+infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
+infer_quant:True
+inference:tools/infer/predict_det.py
+--use_gpu:False
+--enable_mkldnn:False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False
+--precision:int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+null:null
+null:null

test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_mac_cpu.txt

+===========================kl_quant_params===========================
+infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
+infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
+infer_quant:True
+inference:tools/infer/predict_det.py
+--use_gpu:False
+--enable_mkldnn:False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False
+--precision:int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+null:null
+null:null

test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_windows_gpu_cpu.txt

+===========================kl_quant_params===========================
+infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
+infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
+infer_quant:True
+inference:tools/infer/predict_det.py
+--use_gpu:False
+--enable_mkldnn:False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False
+--precision:int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+null:null
+null:null

test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt

+===========================train_params===========================
+model_name:ocr_det
+python:python3.7
+gpu_list:0|0,1
+Global.use_gpu:True|True
+Global.auto_cast:null
+Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300
+Global.save_model_dir:./output/
+Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4
+Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:null
+null:null
+##
+===========================infer_params===========================
+Global.save_inference_dir:./output/
+Global.pretrained_model:
+norm_export:null
+quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o 
+fpgm_export:null
+distill_export:null
+export1:null
+export2:null
+inference_dir:null
+train_model:null
+infer_export:null
+infer_quant:False
+inference:tools/infer/predict_det.py
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16|int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+null:null
\ No newline at end of file

test_tipc/docs/jeston_test_train_inference_python.md

@@ -47,11 +47,11 @@ Jeston端基础训练预测功能测试的主程序为`test_train_inference_pyth
 ```
 - 模式3：whole_infer，不训练，全量数据预测，走通开源模型评估、动转静，检查inference model预测时间和精度;
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_infer_python_jetson.txt 'whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt 'whole_infer'
 # 用法1:
-bash test_tipc/test_inference_jeston.sh ./test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_infer_python_jetson.txt 'whole_infer'
+bash test_tipc/test_inference_jeston.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt 'whole_infer'
 # 用法2: 指定GPU卡预测，第三个传入参数为GPU卡号
-bash test_tipc/test_inference_jeston.sh ./test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_infer_python_jetson.txt 'whole_infer' '1'
+bash test_tipc/test_inference_jeston.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/model_linux_gpu_normal_normal_infer_python_jetson.txt 'whole_infer' '1'
 ```
 
 运行相应指令后，在`test_tipc/output`文件夹下自动会保存运行日志。如`lite_train_lite_infer`模式下，会运行训练+inference的链条，因此，在`test_tipc/output`文件夹有以下文件：

test_tipc/docs/mac_test_train_inference_python.md

@@ -57,36 +57,35 @@ Mac端无GPU，环境准备只需要Python环境即可，安装PaddlePaddle等
 ```shell
 # 同linux端运行不同的是，Mac端测试使用新的配置文件mac_ppocr_det_mobile_params.txt，
 # 配置文件中默认去掉了GPU和mkldnn相关的测试链条
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'lite_train_lite_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'lite_train_lite_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'lite_train_lite_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'lite_train_lite_infer'
 ```  
 
 - 模式2：lite_train_whole_infer，使用少量数据训练，一定量数据预测，用于验证训练后的模型执行预测，预测速度是否合理；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'lite_train_whole_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt  'lite_train_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'lite_train_whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt  'lite_train_whole_infer'
 ```  
 
 - 模式3：whole_infer，不训练，全量数据预测，走通开源模型评估、动转静，检查inference model预测时间和精度;
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_infer'
 # 用法1:
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_infer'
 # 用法2: 指定GPU卡预测，第三个传入参数为GPU卡号
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_infer' '1'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_infer' '1'
 ```  
 
 - 模式4：whole_train_whole_infer，CE： 全量数据训练，全量数据预测，验证模型训练精度，预测精度，预测速度；（Mac端不建议运行此模式）
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_train_whole_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_train_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_train_whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'whole_train_whole_infer'
 ```  
 
 - 模式5：klquant_whole_infer，测试离线量化；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt 'klquant_whole_infer'
-
-bash test_tipc/test_train_inference_python.sh test_tipc/configs/ppocr_det_mobile/train_mac_cpu_normal_normal_infer_python_mac_cpu.txt  'klquant_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_mac_cpu.txt  'klquant_whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_mac_cpu.txt  'klquant_whole_infer'
 ```
 
 运行相应指令后，在`test_tipc/output`文件夹下自动会保存运行日志。如`lite_train_lite_infer`模式下，会运行训练+inference的链条，因此，在`test_tipc/output`文件夹有以下文件：

test_tipc/docs/test_train_inference_python.md

@@ -64,35 +64,35 @@ Linux端基础训练预测功能测试的主程序为`test_train_inference_pytho
 
 - 模式1：lite_train_lite_infer，使用少量数据训练，用于快速验证训练到预测的走通流程，不验证精度和速度；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt 'lite_train_lite_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt 'lite_train_lite_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'lite_train_lite_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'lite_train_lite_infer'
 ```  
 
 - 模式2：lite_train_whole_infer，使用少量数据训练，一定量数据预测，用于验证训练后的模型执行预测，预测速度是否合理；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt  'lite_train_whole_infer'
-bash test_tipc/test_train_inference_python.sh ../test_tipc/configs/ppocr_det_mobile/train_infer_python.txt 'lite_train_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt  'lite_train_whole_infer'
+bash test_tipc/test_train_inference_python.sh ../test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'lite_train_whole_infer'
 ```  
 
 - 模式3：whole_infer，不训练，全量数据预测，走通开源模型评估、动转静，检查inference model预测时间和精度;
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt 'whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'whole_infer'
 # 用法1:
-bash test_tipc/test_train_inference_python.sh ../test_tipc/configs/ppocr_det_mobile/train_infer_python.txt 'whole_infer'
+bash test_tipc/test_train_inference_python.sh ../test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'whole_infer'
 # 用法2: 指定GPU卡预测，第三个传入参数为GPU卡号
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt 'whole_infer' '1'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'whole_infer' '1'
 ```  
 
 - 模式4：whole_train_whole_infer，CE： 全量数据训练，全量数据预测，验证模型训练精度，预测精度，预测速度；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt 'whole_train_whole_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt 'whole_train_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'whole_train_whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'whole_train_whole_infer'
 ```  
 
 - 模式5：klquant_whole_infer，测试离线量化；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt  'klquant_whole_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_infer_python.txt  'klquant_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt  'klquant_whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt  'klquant_whole_infer'
 ```
 
 运行相应指令后，在`test_tipc/output`文件夹下自动会保存运行日志。如'lite_train_lite_infer'模式下，会运行训练+inference的链条，因此，在`test_tipc/output`文件夹有以下文件：

test_tipc/docs/win_test_train_inference_python.md

@@ -58,35 +58,35 @@ Windows端基础训练预测功能测试的主程序为`test_train_inference_pyt
 
 - 模式1：lite_train_lite_infer，使用少量数据训练，用于快速验证训练到预测的走通流程，不验证精度和速度；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'lite_train_lite_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'lite_train_lite_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'lite_train_lite_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'lite_train_lite_infer'
 ```  
 
 - 模式2：lite_train_whole_infer，使用少量数据训练，一定量数据预测，用于验证训练后的模型执行预测，预测速度是否合理；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'lite_train_whole_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'lite_train_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'lite_train_whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'lite_train_whole_infer'
 ```  
 
 - 模式3：whole_infer，不训练，全量数据预测，走通开源模型评估、动转静，检查inference model预测时间和精度;
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_infer'
 # 用法1:
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_infer'
 # 用法2: 指定GPU卡预测，第三个传入参数为GPU卡号
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_infer' '1'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_infer' '1'
 ```  
 
 - 模式4：whole_train_whole_infer，CE： 全量数据训练，全量数据预测，验证模型训练精度，预测精度，预测速度；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_train_whole_infer'
-bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_train_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_train_whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'whole_train_whole_infer'
 ```  
 
 - 模式5：klquant_whole_infer，测试离线量化；
 ```shell
-bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt  'klquant_whole_infer'
-bash test_tipc/test_train_inference_python.sh test_tipc/configs/ppocr_det_mobile/train_windows_gpu_normal_normal_infer_python_windows_cpu_gpu.txt   'klquant_whole_infer'
+bash test_tipc/prepare.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_windows_gpu_cpu.txt  'klquant_whole_infer'
+bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_windows_gpu_cpu.txt  'klquant_whole_infer'
 ```
 
 

test_tipc/test_train_inference_python.sh

@@ -90,34 +90,36 @@ infer_value1=$(func_parser_value "${lines[50]}")
 
 # parser klquant_infer
 if [ ${MODE} = "klquant_whole_infer" ]; then
-    dataline=$(awk 'NR==85 NR==101{print}'  $FILENAME)
+    dataline=$(awk 'NR==1 NR==17{print}'  $FILENAME)
     lines=(${dataline})
+    model_name=$(func_parser_value "${lines[1]}")
+    python=$(func_parser_value "${lines[2]}")
     # parser inference model 
-    infer_model_dir_list=$(func_parser_value "${lines[1]}")
-    infer_export_list=$(func_parser_value "${lines[2]}")
-    infer_is_quant=$(func_parser_value "${lines[3]}")
+    infer_model_dir_list=$(func_parser_value "${lines[3]}")
+    infer_export_list=$(func_parser_value "${lines[4]}")
+    infer_is_quant=$(func_parser_value "${lines[5]}")
     # parser inference 
-    inference_py=$(func_parser_value "${lines[4]}")
-    use_gpu_key=$(func_parser_key "${lines[5]}")
-    use_gpu_list=$(func_parser_value "${lines[5]}")
-    use_mkldnn_key=$(func_parser_key "${lines[6]}")
-    use_mkldnn_list=$(func_parser_value "${lines[6]}")
-    cpu_threads_key=$(func_parser_key "${lines[7]}")
-    cpu_threads_list=$(func_parser_value "${lines[7]}")
-    batch_size_key=$(func_parser_key "${lines[8]}")
-    batch_size_list=$(func_parser_value "${lines[8]}")
-    use_trt_key=$(func_parser_key "${lines[9]}")
-    use_trt_list=$(func_parser_value "${lines[9]}")
-    precision_key=$(func_parser_key "${lines[10]}")
-    precision_list=$(func_parser_value "${lines[10]}")
-    infer_model_key=$(func_parser_key "${lines[11]}")
-    image_dir_key=$(func_parser_key "${lines[12]}")
-    infer_img_dir=$(func_parser_value "${lines[12]}")
-    save_log_key=$(func_parser_key "${lines[13]}")
-    benchmark_key=$(func_parser_key "${lines[14]}")
-    benchmark_value=$(func_parser_value "${lines[14]}")
-    infer_key1=$(func_parser_key "${lines[15]}")
-    infer_value1=$(func_parser_value "${lines[15]}")
+    inference_py=$(func_parser_value "${lines[6]}")
+    use_gpu_key=$(func_parser_key "${lines[7]}")
+    use_gpu_list=$(func_parser_value "${lines[7]}")
+    use_mkldnn_key=$(func_parser_key "${lines[8]}")
+    use_mkldnn_list=$(func_parser_value "${lines[8]}")
+    cpu_threads_key=$(func_parser_key "${lines[9]}")
+    cpu_threads_list=$(func_parser_value "${lines[9]}")
+    batch_size_key=$(func_parser_key "${lines[10]}")
+    batch_size_list=$(func_parser_value "${lines[10]}")
+    use_trt_key=$(func_parser_key "${lines[11]}")
+    use_trt_list=$(func_parser_value "${lines[11]}")
+    precision_key=$(func_parser_key "${lines[12]}")
+    precision_list=$(func_parser_value "${lines[12]}")
+    infer_model_key=$(func_parser_key "${lines[13]}")
+    image_dir_key=$(func_parser_key "${lines[14]}")
+    infer_img_dir=$(func_parser_value "${lines[14]}")
+    save_log_key=$(func_parser_key "${lines[15]}")
+    benchmark_key=$(func_parser_key "${lines[16]}")
+    benchmark_value=$(func_parser_value "${lines[16]}")
+    infer_key1=$(func_parser_key "${lines[17]}")
+    infer_value1=$(func_parser_value "${lines[17]}")
 fi
 
 LOG_PATH="./test_tipc/output"