Comments (9)
Maclory
commented on August 15, 2024
It's just for simplicity. In my opinion, two implementations are similar intrinsically.
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Feihong-cc
commented on August 15, 2024
Can I communicate with you in Chinese?（哈哈，我能和你用中文交流吗？）我有些疑问，SPSR的梯度分支本质上应该是求图像的梯度，按照数字图像处理的方法，应该是将彩色图转为灰度图，再求其的梯度图才是正常的流程。你在SPSR代码里面，是将RGB三个通道分别拆开，分别求其梯度图，这样每个通道的梯度图不一定一样，最后再concat到一起，会不会导致图像的边缘信息（高频信息）更凌乱or模糊？请问你有测试过单通道和三通道分别求的梯度图，有什么差别吗？
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Maclory
commented on August 15, 2024
concat的话能保留更多的信息，一般不会导致信息变差。两种实现我们也都试过，差别很小。
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Feihong-cc
commented on August 15, 2024
(⊙o⊙)太棒了，我又可以省去做验证的时间了！十分感谢你
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Maclory
commented on August 15, 2024
哈哈哈，不客气
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Feihong-cc
commented on August 15, 2024
hi！你好鸭，我有个小问题想请教你，你的SR分支和梯度分支的loss是相加起来，loss=sr_loss+grad_loss，这样同时求反向传播和分别backward应该是存在差别的，你有试过分开backward吗？
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Feihong-cc
commented on August 15, 2024
如果我需要将两个loss分开backward的话，需要两个optimizer吗？
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Maclory
commented on August 15, 2024
我觉得怎么实现都可以，合理就行
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Feihong-cc
commented on August 15, 2024
好的，十分感谢你~
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Related Issues (20)
- 模型的训练是如何安排的？ HOT 3
- RuntimeError: stack expects each tensor to be equal size, but got [3, 0, 0] at entry 0 and [3, 164, 0] at entry 1
- 关于梯度图 HOT 2
- About evaluation toolbox configuration. HOT 1
- 关于root中的path HOT 3
- I am running out of memory on gpu HOT 3
- Errors accur when using evaluation tool box HOT 1
- Cannot reproduce the reported performance using the pretrained checkpoint HOT 1
- 训练时预处理的lmdb部分报错 HOT 1
- 您好，我在运行您的代码的时候遇到一个问题，期待您的答复，谢谢。在运行时，可以正常训练，但是验证时，会爆显存RuntimeError:CUDA out of memory。请问是什么原因呢 HOT 4
- Test with multiple GPUs HOT 3
- blank image HOT 6
- CUDA Out Of Memory on 4900th iteration. HOT 2
- waring HOT 2
- get a Error while run generate_dataset.py.
- question about test HOT 3
- Evaluation code modification suggestion
- 关于使用工具箱测试自己的模型 HOT 1
- create model.py is not inside models folder
- About HR_size and CUDA memory
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