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fix error links in model zoo files for master
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@ -50,8 +50,8 @@ EfficientNet总体网络架构如下:
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- 框架
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- [MindSpore](https://www.mindspore.cn/install)
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- 如需查看详情,请参见如下资源:
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- [MindSpore 教程](https://www.mindspore.cn/tutorial/training/zh-CN/master/index.html)
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- [MindSpore Python API](https://www.mindspore.cn/doc/api_python/zh-CN/master/index.html)
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- [MindSpore 教程](https://www.mindspore.cn/tutorials/zh-CN/master/index.html)
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- [MindSpore Python API](https://www.mindspore.cn/docs/api/zh-CN/master/index.html)
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# 脚本说明
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@ -56,8 +56,8 @@ Dataset used: [omniglot](https://github.com/brendenlake/omniglot)
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- Framework
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- [MindSpore](https://www.mindspore.cn/install/en)
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- For more information, please check the resources below:
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- [MindSpore Tutorials](https://www.mindspore.cn/tutorial/training/en/master/index.html)
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- [MindSpore Python API](https://www.mindspore.cn/doc/api_python/en/master/index.html)
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- [MindSpore Tutorials](https://www.mindspore.cn/tutorials/en/master/index.html)
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- [MindSpore Python API](https://www.mindspore.cn/docs/api/en/master/index.html)
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# [Quick Start](#contents)
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@ -432,7 +432,7 @@ train_parallel1/log:epcoh: 2 step: 97, loss is 1.7133579
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...
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```
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> About rank_table.json, you can refer to the [distributed training tutorial](https://www.mindspore.cn/tutorials/en/master/distributed_training.html).
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> About rank_table.json, you can refer to the [distributed training tutorial](https://www.mindspore.cn/tutorials/zh-CN/master/distributed_training.html).
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> **Attention** This will bind the processor cores according to the `device_num` and total processor numbers. If you don't expect to run pretraining with binding processor cores, remove the operations about `taskset` in `scripts/run_distribute_train.sh`
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##### Run vgg19 on GPU
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