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add doc about win and mac
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@@ -28,6 +28,9 @@
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## 2. 测试流程
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运行环境配置请参考[文档](./install.md)的内容配置tipc的运行环境。
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### 2.1 安装依赖
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- 安装PaddlePaddle >= 2.0
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- 安装PaddleOCR依赖
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@@ -89,6 +92,32 @@ bash test_tipc/prepare.sh ./test_tipc/configs/ppocr_det_mobile_params.txt 'klqua
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bash test_tipc/test_train_inference_python.sh test_tipc/configs/ppocr_det_mobile_params.txt 'klquant_whole_infer'
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```
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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:
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```
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test_tipc/output/
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|- results_python.log # 运行指令状态的日志
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|- norm_train_gpus_0_autocast_null/ # GPU 0号卡上正常训练的训练日志和模型保存文件夹
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|- pact_train_gpus_0_autocast_null/ # GPU 0号卡上量化训练的训练日志和模型保存文件夹
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......
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|- python_infer_cpu_usemkldnn_True_threads_1_batchsize_1.log # CPU上开启Mkldnn线程数设置为1,测试batch_size=1条件下的预测运行日志
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|- python_infer_gpu_usetrt_True_precision_fp16_batchsize_1.log # GPU上开启TensorRT,测试batch_size=1的半精度预测日志
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......
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```
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其中`results_python.log`中包含了每条指令的运行状态,如果运行成功会输出:
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```
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Run successfully with command - python3.7 tools/train.py -c tests/configs/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained Global.use_gpu=True Global.save_model_dir=./tests/output/norm_train_gpus_0_autocast_null Global.epoch_num=1 Train.loader.batch_size_per_card=2 !
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Run successfully with command - python3.7 tools/export_model.py -c tests/configs/det_mv3_db.yml -o Global.pretrained_model=./tests/output/norm_train_gpus_0_autocast_null/latest Global.save_inference_dir=./tests/output/norm_train_gpus_0_autocast_null!
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......
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```
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如果运行失败,会输出:
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```
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Run failed with command - python3.7 tools/train.py -c tests/configs/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained Global.use_gpu=True Global.save_model_dir=./tests/output/norm_train_gpus_0_autocast_null Global.epoch_num=1 Train.loader.batch_size_per_card=2 !
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Run failed with command - python3.7 tools/export_model.py -c tests/configs/det_mv3_db.yml -o Global.pretrained_model=./tests/output/norm_train_gpus_0_autocast_null/latest Global.save_inference_dir=./tests/output/norm_train_gpus_0_autocast_null!
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......
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```
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可以很方便的根据`results_python.log`中的内容判定哪一个指令运行错误。
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### 2.3 精度测试
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