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Confusion in function update_routing

See original GitHub issue

@brjathu Hi. I’ve read your paper and it’s great that you’ve given your code. Thanks a lot. I have a few doubts in the ConvCapsuleLayer3D layer. Could you clarify them for me?

  1. In the paper, the softmax_3D function was given, with the denominator summed over spatial positions and the capsules in the l+1 th layer. The implementation, however, uses nn.softmax whose denominator sums over only the capsules in update_routing. Could you clarify this?
  2. In the update_routing function, I am unable to understand the reshaping operations. It seems that the dimension for the batch size is being changed. Could you clarify the sizes used? Thank you.

Issue Analytics

  • State:closed
  • Created 4 years ago
  • Comments:16 (7 by maintainers)

github_iconTop GitHub Comments

HopefulRationalcommented, Aug 1, 2019

@ierosodin Hi. I have put a quick and dirty PyTorch implementation of DeepCaps as a .py file.You may have a look at that: It is being trained on transformed FashionMNIST and tested of FashionMNIST.

brjathucommented, Aug 7, 2019


Localized routing comes because, with a 3*3 kernel a nine local capsules are routed together.

Regards, R.Jathushan

On Wed, 7 Aug 2019 at 10:42, ierosodin wrote:

Hi @brjathu , I still have a few doubts. I’m wondering what’s the meaning of “localized voting” you have mentioned in the paper. For example, for each capsule in capsule layer l+1, what are the capsules it routes in capsule layer l? Every capsule in layer l across all of the location? or just in a limited kernel. Thanks!

Sincerely, Tony

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