Is it reasonable to get a threshold for all bn layers?

[zihaozhang9]

When calculating the threshold, the weight ordering of all bn layers is used. Is this reasonable?

Is there such a phenomenon:
① The first value of the network is closer to the image pixel value, and the last layer is closer to the category probability. bn's weight is not necessarily the same.
② There is a shortcut in the middle of the network. After the two convolution pixel values are superimposed, the weight parameter becomes larger. May affect bn's weight.

在计算阈值时，将使用所有bn层的权重排序。 这合理吗？
是否存在这样的现象：
①网络最前面的数值，更靠近图像像素值，最后一层更靠近类别概率。bn的weight不一定分布相同。
②在网络中间有shortcut，两个卷积像素值叠加后，weight参数变大。可能会影响bn的weight。

issues
期待您的回复。十分感谢。

[Eric-mingjie]

我们使用的就是原始的network slimming的方法，code实现了slimming的原始论文 https://arxiv.org/abs/1708.06519

slimming中全局排序bn在实验上被证明是简捷并有效的方法，对于你提的问题， 我们没有比较过每个bn层的scalng fcator，不过很有意义和值得研究，更精细的pruning可能会有更好的结果。