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您好,在看完您的文章后,我有一些不清楚的地方想向您请教一下,图六中关于两个分支的权重值,在网络训练时该如何呈现出来?或者在网络训练完毕后,如何得知每个块中对应的两个分支的权重值?希望您有空的话,可以解决一下我的疑惑。谢谢您的指教!!!
The text was updated successfully, but these errors were encountered:
x = attention * ax[:,0].view(a,1,1,1) + non_attention * ax[:,1].view(a,1,1,1) 您好,可以通过直接看 ax 的值得到
x = attention * ax[:,0].view(a,1,1,1) + non_attention * ax[:,1].view(a,1,1,1)
Sorry, something went wrong.
谢谢您的回答,由于我的代码水平很薄弱,如果只有一个AAB时,我能懂您的意思,但是当在整体网络中运用self.AAB_trunk = make_layer(AAB_block_f, nb)时,我并不清楚该如何写出相应代码,来输出每个AAB中的ax值,不知道您是否可以再帮忙解答一下,万分感谢!!
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您好,在看完您的文章后,我有一些不清楚的地方想向您请教一下,图六中关于两个分支的权重值,在网络训练时该如何呈现出来?或者在网络训练完毕后,如何得知每个块中对应的两个分支的权重值?希望您有空的话,可以解决一下我的疑惑。谢谢您的指教!!!
The text was updated successfully, but these errors were encountered: