Comments (1)
YimianDai
commented on August 24, 2024
这个问题，我在另外一个 issue 已经回答过了，https://github.com/YimianDai/open-aff/issues/3。
我没有想过「防止数值太小梯度消失」这回事。既然有了 batch normalization，我相信乘不乘 2 是不会有影响的。简单的说，就是为了保证跟 X + Y 一样，两者前面的系数总和为 （1 + 1 = 2），所以乘了一个 2。
至于 iAFF 没用，因为我不觉得乘不乘 2 会有什么影响，所以写得时候没注意这个。刚开始写代码的时候写得随意了，类的名称也没有好好取，跑完实验后才发现 params 里面跟代码里的名称绑死了，如果为了美化代码要改名称，那必须重跑实验。因为 GPU 资源有限，所以我就没重跑，现在的代码就是最初的样子，所以写得随意了些。。。
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Related Issues (20)
- AFF-FPN HOT 3
- ASKCResNetFPN
- 您好，请问AFF模块中的最后一步为什么要乘以2？有什么意义呢？希望收到您的回复 HOT 2
- TypeError: forward() missing 1 required positional argument: 'residual' HOT 2
- resnet50预训练模型 HOT 3
- module -> self.global_att2
- __init__() takes from 1 to 3 positional arguments but 6 were given
- 代码中AFF模块中，为什么要用2×呢？ HOT 1
- 请教 这种特征融合思路能否应用到 NLP 中？
- 可否进行实现三种特征图的融合 HOT 1
- Concat and fusion instead of add in iAFF and AFF
- iAFF类的forward函数中, xg2 = self.global_att(xi) 这一行是不是笔误 HOT 1
- 运行模块时报错请教 HOT 1
- aff使用于fpn或者Unet结构 HOT 2
- When the website will be ready?
- 为何将iaff加入到resnet第一层会报如下错误：TypeError: forward() missing 1 required positional argument: 'residual'
- 您好可以发一下iAFF-ResNeXt-50-32x4d训练ImageNet的权重文件吗
- ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 256, 1, 1]) HOT 2
- 关于BN层 HOT 2
- 请问怎么在pytorch直接使用AFF呀？ HOT 1
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