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v0.5.0 adaption (#814)
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‎configs/det/dbnet/README.md

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@@ -288,7 +288,7 @@ msrun --worker_num=2 --local_worker_num=2 python tools/train.py --config configs
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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=2 --local_worker_num=2 python tools/train.py --config configs/det/dbnet/db_r50_icdar15.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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The training result (including checkpoints, per-epoch performance and curves) will be saved in the directory parsed by the arg `ckpt_save_dir` in yaml config file. The default directory is `./tmp_det`.
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‎configs/det/dbnet/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=2 --local_worker_num=2 python tools/train.py --config configs/det/dbnet/db_r50_icdar15.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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训练结果（包括checkpoint、每个epoch的性能和曲线图）将被保存在yaml配置文件的`ckpt_save_dir`参数配置的路径下，默认为`./tmp_det`。
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‎configs/det/dbnet/README_CN_PP-OCRv3.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/det/dbnet/db_mobilenetv3_ppocrv3.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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* 单卡训练

‎configs/det/east/README.md

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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/det/east/east_r50_icdar15.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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The training result (including checkpoints, per-epoch performance and curves) will be saved in the directory parsed by the arg `ckpt_save_dir` in yaml config file. The default directory is `./tmp_det`.
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‎configs/det/east/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/det/east/east_r50_icdar15.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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训练结果（包括checkpoint、每个epoch的性能和曲线图）将被保存在yaml配置文件的`ckpt_save_dir`参数配置的路径下，默认为`./tmp_det`。
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‎configs/det/psenet/README.md

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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/det/psenet/pse_r152_icdar15.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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The training result (including checkpoints, per-epoch performance and curves) will be saved in the directory parsed by the arg `ckpt_save_dir` in yaml config file. The default directory is `./tmp_det`.

‎configs/det/psenet/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/det/psenet/pse_r152_icdar15.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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训练结果（包括checkpoint、每个epoch的性能和曲线图）将被保存在yaml配置文件的`ckpt_save_dir`参数配置的路径下，默认为`./tmp_det`。
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‎configs/layout/yolov8/README.md

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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/layout/yolov8/yolov8n.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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* Standalone Training

‎configs/layout/yolov8/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/layout/yolov8/yolov8n.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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* 单卡训练

‎configs/rec/abinet/README.md

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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/rec/abinet/abinet_resnet45_en.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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The pre-trained model needs to be loaded during ABINet model training, and the weight of the pre-trained model is
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from [abinet_pretrain_en.ckpt](https://download.mindspore.cn/toolkits/mindocr/abinet/abinet_pretrain_en-821ca20b.ckpt). It is needed to add the path of the pretrained weight to the model pretrained in "configs/rec/abinet/abinet_resnet45_en.yaml".

‎configs/rec/abinet/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/rec/abinet/abinet_resnet45_en.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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ABINet模型训练时需要加载预训练模型，预训练模型的权重来自[abinet_pretrain_en.ckpt](https://download.mindspore.cn/toolkits/mindocr/abinet/abinet_pretrain_en-821ca20b.ckpt)，需要在“configs/rec/abinet/abinet_resnet45_en.yaml”中model的pretrained添加预训练权重的路径。

‎configs/rec/crnn/README.md

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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/rec/crnn/crnn_resnet34.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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‎configs/rec/crnn/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/rec/crnn/crnn_resnet34.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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* 单卡训练

‎configs/rec/master/README.md

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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/master/master_resnet31.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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‎configs/rec/master/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/master/master_resnet31.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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‎configs/rec/rare/README.md

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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/rare/rare_resnet34.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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* Standalone Training

‎configs/rec/rare/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/rare/rare_resnet34.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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* 单卡训练

‎configs/rec/robustscanner/README.md

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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/robustscanner/robustscanner_resnet31.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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* Standalone Training

‎configs/rec/robustscanner/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/robustscanner/robustscanner_resnet31.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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* 单卡训练

‎configs/rec/svtr/README.md

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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/rec/svtr/svtr_tiny_8p.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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‎configs/rec/svtr/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/rec/svtr/svtr_tiny_8p.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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‎configs/rec/svtr/README_CN_PP-OCRv3.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/svtr/svtr_ppocrv3_ch.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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‎configs/rec/visionlan/README.md

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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/visionlan/visionlan_resnet45_LF_2.yaml
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/visionlan/visionlan_resnet45_LA.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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The training result (including checkpoints, per-epoch performance and curves) will be saved in the directory parsed by the arg `ckpt_save_dir` in yaml config file. The default directory is `./tmp_visionlan`.
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‎configs/rec/visionlan/README_CN.md

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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/visionlan/visionlan_resnet45_LF_2.yaml
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msrun --bind_core=True --worker_num=4 --local_worker_num=4 python tools/train.py --config configs/rec/visionlan/visionlan_resnet45_LA.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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训练结果（包括checkpoints、每个阶段的性能和loss曲线）将保存在yaml配置文件中由参数`ckpt_save_dir`解析的目录中。默认目录为`./tmp_visionlan`。
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‎configs/table/README.md

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@@ -144,7 +144,7 @@ msrun --worker_num=8 --local_worker_num=8 python tools/train.py --config configs
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# Based on verification,binding cores usually results in performance acceleration.Please configure the parameters and run.
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/table/table_master.yaml
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```
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/master/model_train/parallel/msrun_launcher.html).
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**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/docs/en/r2.5.0/model_train/parallel/msrun_launcher.html).
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The training result (including checkpoints, per-epoch performance and curves) will be saved in the directory parsed by the arg `ckpt_save_dir` in yaml config file. The default directory is `./tmp_table`.

‎configs/table/README_CN.md

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# 经验证，绑核在大部分情况下有性能加速，请配置参数并运行
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msrun --bind_core=True --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/table/table_master.yaml
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```
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/master/model_train/parallel/msrun_launcher.html).
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**注意:** 有关 msrun 配置的更多信息，请参考[此处](https://www.mindspore.cn/docs/zh-CN/r2.5.0/model_train/parallel/msrun_launcher.html).
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训练结果（包括checkpoint、每个epoch的性能和曲线图）将被保存在yaml配置文件的`ckpt_save_dir`参数配置的路径下，默认为`./tmp_table`。
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