diff --git a/test_tipc/supplementary/readme.md b/test_tipc/supplementary/readme.md index 0d35f9451f5004498cdbd001edfb2dfe2244ebb7..b630b0f30b23b71c0dd21def2a45fee01023fe82 100644 --- a/test_tipc/supplementary/readme.md +++ b/test_tipc/supplementary/readme.md @@ -3,7 +3,7 @@ Linux端基础训练预测功能测试的主程序为test_train_python.sh,可以测试基于Python的模型训练、评估等基本功能,包括裁剪、量化、蒸馏训练。 -![](./tipc_train.png) +![](./test_tipc/tipc_train.png) 测试链条如上图所示,主要测试内容有带共享权重,自定义OP的模型的正常训练和slim相关功能训练流程是否正常。 @@ -28,23 +28,23 @@ pip3 install -r requirements.txt - 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; ``` -bash test_tipc/test_train_python.sh ./test_tipc/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'lite_train_lite_infer' +bash test_tipc/test_train_python.sh ./test_tipc/train_infer_python.txt 'lite_train_lite_infer' ``` - 模式2:whole_train_whole_infer,使用全量数据训练,用于快速验证训练到预测的走通流程,验证模型最终训练精度; ``` -bash test_tipc/test_train_python.sh ./test_tipc/ch_ppocr_mobile_v2.0_det/train_infer_python.txt 'whole_train_whole_infer' +bash test_tipc/test_train_python.sh ./test_tipc/train_infer_python.txt 'whole_train_whole_infer' ``` 如果是运行量化裁剪等训练方式,需要使用不同的配置文件。量化训练的测试指令如下: ``` -bash test_tipc/test_train_python.sh ./test_tipc/ch_ppocr_mobile_v2.0_det/train_infer_python_PACT.txt 'lite_train_lite_infer' +bash test_tipc/test_train_python.sh ./test_tipc/train_infer_python_PACT.txt 'lite_train_lite_infer' ``` 同理,FPGM裁剪的运行方式如下: ``` -bash test_tipc/test_train_python.sh ./test_tipc/ch_ppocr_mobile_v2.0_det/train_infer_python_FPGM.txt 'lite_train_lite_infer' +bash test_tipc/test_train_python.sh ./test_tipc/train_infer_python_FPGM.txt 'lite_train_lite_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'模式运行后,在test_tipc/extra_output文件夹有以下文件: