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[Docs] Add gif to 15 min tutorial (#748) 

* add gif

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Mashiro 2022-12-04 11:21:40 +08:00 committed by GitHub
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4
docs/en/get_started/15_minutes.md
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@ -238,4 +238,8 @@ System environment:
2022/08/22 15:52:54 - mmengine - INFO - Epoch(val) [1][313/313] accuracy: 35.7000
```
The corresponding implementation of PyTorch and MMEngine:
![output](https://user-images.githubusercontent.com/57566630/203142869-cfe5f855-f391-4fd4-a80c-beecf1bd111f.gif)
In addition to these basic components, you can also use **executor** to easily combine and configure various training techniques, such as enabling mixed-precision training and gradient accumulation (see [OptimWrapper](../tutorials/optim_wrapper.md)), configuring the learning rate decay curve (see [Metrics & Evaluator](../tutorials/evaluation.md)), and etc.

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docs/zh_cn/get_started/15_minutes.md
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@ -235,4 +235,8 @@ System environment:
2022/08/22 15:52:54 - mmengine - INFO - Epoch(val) [1][313/313] accuracy: 35.7000
```
基于 PyTorch 和基于 MMEngine 的训练流程对比如下：
![output](https://user-images.githubusercontent.com/57566630/203142869-cfe5f855-f391-4fd4-a80c-beecf1bd111f.gif)
除了以上基础组件，你还可以利用**执行器**轻松地组合配置各种训练技巧，如开启混合精度训练和梯度累积（见 [优化器封装（OptimWrapper）](../tutorials/optim_wrapper.md)）、配置学习率衰减曲线（见 [评测指标与评测器（Metrics & Evaluator）](../tutorials/evaluation.md)）等。