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【Hackathon 5th No.40】为 Paddle 新增 ASGD API 中文文档 #6412
【Hackathon 5th No.40】为 Paddle 新增 ASGD API 中文文档 #6412
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感谢你贡献飞桨文档,文档预览构建中,Docs-New 跑完后即可预览,预览链接:http://preview-pr-6412.paddle-docs-preview.paddlepaddle.org.cn/documentation/docs/zh/api/index_cn.html |
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映射文档需要让用户能低成本转写过来,多出来的三个参数是不符合论文的吗
| params | parameters | 表示指定优化器需要优化的参数,仅参数名不一致 | | ||
| lr | learning_rate | 学习率,用于参数更新的计算。参数默认值不一致, Pytorch 默认为 `0.0001`, Paddle 默认为 `0.001`,Paddle 需保持与 Pytorch 一致 | | ||
| lambd | - | 衰变项,与 weight_decay 功能重叠,暂无转写方式 | | ||
| alpha | - | eta 更新的 power,暂无转写方式 | |
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这个参数不需要吗
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不需要
| lr | learning_rate | 学习率,用于参数更新的计算。参数默认值不一致, Pytorch 默认为 `0.0001`, Paddle 默认为 `0.001`,Paddle 需保持与 Pytorch 一致 | | ||
| lambd | - | 衰变项,与 weight_decay 功能重叠,暂无转写方式 | | ||
| alpha | - | eta 更新的 power,暂无转写方式 | | ||
| t0 | - | 开始求平均值的点,暂无转写方式 | |
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这个参数不需要吗
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同上
| ------------- | ------------------- | ----------------------------------------------------------------------------------------------------------------------- | | ||
| params | parameters | 表示指定优化器需要优化的参数,仅参数名不一致 | | ||
| lr | learning_rate | 学习率,用于参数更新的计算。参数默认值不一致, Pytorch 默认为 `0.0001`, Paddle 默认为 `0.001`,Paddle 需保持与 Pytorch 一致 | | ||
| lambd | - | 衰变项,与 weight_decay 功能重叠,暂无转写方式 | |
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这个与weight_decay功能一致的话,有办法替代实现吗
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这个不需要转换。这个在 torch 的实现中会用到,在 paddle 的实现中没有这个参数的。
| foreach | - | 是否使用优化器的 foreach 实现。Paddle 无此参数,一般对网络训练结果影响不大,可直接删除 | | ||
| maximize | - | 根据目标最大化参数,而不是最小化。Paddle 无此参数,暂无转写方式 | | ||
| differentiable| - | 是否应通过训练中的优化器步骤进行自动微分。Paddle 无此参数,一般对网络训练结果影响不大,可直接删除 | | ||
| - | batch_num | 完成一个 epoch 所需迭代的次数。 PyTorch 无此参数,Paddle 需要根据样本数据设置 | |
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这个可以写下具体的设置方式吗
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Done
多出来的三个参数目前看来是冗余的。 |
@zhwesky2010 老师您看还有其它的问题 |
你认为torch的实现有问题,所以目前看来alpha、lambda、to、maximize这四个参数会出现无法转换的情况对吗,也就是如果用户用了这4个参数中任意一个,都无法用paddle实现同等的效果? |
是这样的,这个优化器的一个关键部分是历史梯度信息,它需要历史梯度信息参与到参数更新中去。在现版本的 torch 实现中,历史梯度信息被保存到了 ax 中,但是在参数更新的过程中, ax 并没有起作用。有人反应过这个问题(见 |
@zhwesky2010 不忙的时候再看一下哈⸂⸂⸜(രᴗര )⸝⸃⸃ |
@WintersMontagne10335 那在转写时,这几个参数建议是可以直接删掉吗,对最终的结果影响大吗,或者是不是把torch.optim.ASGD转写成paddle.optimizer.SGD,这里转写都是单纯从结果上来看 |
如果要转写成 ASGD ,建议直接删掉。 |
@zhwesky2010 再看一下哈 |
目前来看这个API应该还是无法转的,底层公式也不太一样,如果torch以后更新了上面这个bug的问题,咱们有可能转吗 |
我会跟进的~~有调整的话,我会做对接。 |
``` | ||
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注:Pytorch 的 ASGD 是有问题的。 | ||
Pytorch 相比 Paddle 支持更多其他参数,具体如下: |
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那目前这两个API实现差异还是比较大的,对 torch.optim.ASGD
直接转成 paddle.optimizer.ASGD
结果肯定是对不上的,所以在映射文档里写明白原因吧:torch的问题、为何实现不一致、如果使用paddle的ASGD结果会对不上但不一定影响最终收敛,或者自行尝试其他优化器,让用户知道这里有坑不容易对齐。
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然后就按 功能缺失 来处理吧,后面torch如果更新了再调整
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修改了一下,您看可以嘛
@zhwesky2010 您看还有需要补充订正的嘛 |
@@ -0,0 +1,83 @@ | |||
## [ 功能缺失 ]torch.optim.ASGD |
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如果你写了参数映射的方式,那就还是按 torch参数更多 吧
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Done
| t0 | - | 开始求平均值的点,可直接删除 | | ||
| weight_decay | weight_decay | 权重衰减。参数默认值不一致, Pytorch 默认为 `0`, Paddle 默认为 `None`,Paddle 需保持与 Pytorch 一致 | | ||
| foreach | - | 是否使用优化器的 foreach 实现。Paddle 无此参数,一般对网络训练结果影响不大,可直接删除 | | ||
| maximize | - | 根据目标最大化参数,而不是最小化。Paddle 无此参数,可直接删除 | |
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Done
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LGTM for api docs
@zhwesky2010 改好啦,还有别的要订正嘛 |
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LGTM
为 Paddle 新增 ASGD API 中文文档