Comments (4)
设置filter的时候需要令它们的 总感受野=kernel size。例如当kernel size = 15时,你可以如下设置filters:
(1 + 15*2 - 9)/1 + 1 = 23 # 对单位kernel(size=1)进行卷积,第一次需要padding = kernel size,步长为1
(23 - 5)/1 + 1 = 19 # 之后padding为0
(19 - 3)/1 + 1 = 17
(17 - 3)/1 + 1 = 15
(15 - 1)/1 + 1 = 15 # 卷积后正好与kernel size相等
因此kernel size == 15时,filters可以设置[9, 5, 3, 3, 1],同样,kernel size==19时,filters为[11, 7, 3, 3, 1].
祝好
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谢谢作者的耐心讲解!祝您科研道路一帆风顺!
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作者您好,您源码中的首次padding为kernelsize - 1而非kernelsize,所以kernel size == 15时,filters可设置[9, 5, 3, 1],同样,kernel size==19时,filters可设置[11, 7, 3, 1]。不过您的思路加深了我对该设置以及动态卷积过程的理解,感谢您的耐心分享,祝您一切顺利!
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作者您好,您源码中的首次padding为kernelsize - 1而非kernelsize,所以kernel size == 15时,filters可设置[9, 5, 3, 1],同样,kernel size==19时,filters可设置[11, 7, 3, 1]。不过您的思路加深了我对该设置以及动态卷积过程的理解,感谢您的耐心分享,祝您一切顺利!
padding确实是我弄错了,感谢指正hah。
祝好
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