Comments (4)
fungtion
commented on September 23, 2024
shuffle operation here
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kikiYa99
commented on September 23, 2024
所以这样的意思是，虽然每次的epoch没有取完所有的源域样本，但是因为样本随机，所以在多个epoch之后仍然被全部都训练了是嘛？
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fungtion
commented on September 23, 2024
Yes, you can customize a sampler to make all the data get trained.
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kikiYa99
commented on September 23, 2024
好的明白了，谢谢！
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Related Issues (14)
- how to use DANN for a net performing regression instead of classification? HOT 4
- 关于域分类器的error HOT 1
- The domain classifier loss is not decreasing. HOT 4
- 下载的文件 HOT 1
- 救命！帮帮我！ HOT 1
- what's the difference between x.view_as(x) and x? HOT 2
- 关于模型classifier中dropout的问题 HOT 1
- Pytorch version is not consistent in README and Dockfile HOT 2
- why this model is not care about the label of taget dataset?..
- why don't use the optimizer.zero_grad() HOT 1
- dataset HOT 1
- Expected more than 1 value per channel when training, got input size torch.Size([1, 100]) HOT 1
- Size of target domain HOT 3
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