Confusion in function update_routing

@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.

[HopefulRational]

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

[brjathu]

Hi,

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 [e-mail] wrote:

Hi @brjathu https://github.com/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

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/brjathu/deepcaps/issues/4?email_source=notifications&email_token=ABZNVOM5UGSMGOVJALAOA73QDJVFJA5CNFSM4IHAP2D2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD3XL43Q#issuecomment-518962798, or mute the thread https://github.com/notifications/unsubscribe-auth/ABZNVOIGGV7DVNYMRJRPEE3QDJVFJANCNFSM4IHAP2DQ .