liuzhuang13 / slimming

Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.

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

zihaozhang9 opened this issue · comments

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。