【Hackathon No.13】 #33
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zhiboniu
previously approved these changes
Mar 15, 2022
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| 去除了Pytorch中`momentum`的相关参数。 | ||
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| 同时，为了保持与paddle其他lrscheduler相关的api保持一致，将`base_lr`修改为`learning_rate`，`max_lr`修改为`max_learning_rate`，此修改有待商榷。 |
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这里我觉得如果策略只用到一个lr，用learning_rate就可以了。如果用到两个相关联的lr，可能base_learning_rate和max_learning_rate意思更清楚一些
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| 测试考虑的case如下： | ||
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| - 动态图，静态图，与numpy的结果保持一致； |
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除了API TEST中用numpy实现验证，本地可以跟pytorch实现做验证。然后多参考其他优化器的验证代码是怎么做的。
DDDivano
reviewed
Mar 15, 2022
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| ## 命名与参数设计 | ||
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| API设计为`paddle.optim.lr.CyclicLR(learning_rate,max_learning_rate,step_size_up,step_size_down, mode='triangular',gamma=1.,scale_fn=None,scale_mode='cycle',last_epoch=-1,verbose=False)` |
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paddle优化器相关都在 paddle.optimizer下，这里叫optim是有什么考虑还是写错了？
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不好意思，缩写写习惯了，稍后将会更新
zhiboniu
approved these changes
Mar 15, 2022
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你的PR 已合入community库，请进行后续代码开发，并将代码提交至paddle仓库 |
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为paddle新增CyclicLR优化调度器