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32 appears to come from the previous out_channels, but I can't tell what 6 * 6 are doing. Is this arbitrary, or is it preventing some kind of dimension mismatch? If I am implementing my own capsule network with new dimensions, do I need to be careful about how I pick this value?
Thanks,
Will
The text was updated successfully, but these errors were encountered:
Hi,
6 * 6 comes from the following:
input(MNIST) size is 28^2(capsule network was tried on MNIST).
First convolution layer has 9 kernel size with stride 1, making its output ceil((28 - kernel_size + 1) / stride_size)^2 = 20^2.
Primary capsule side has another convolution layer inside, but this time it has stride = 2. The same formula, gives: ceil((20 - kernel_size + 1) / stride_size)^2 = 6 * 6. I hope the rest is comprehendible.
32 appears to come from the previous out_channels, but I can't tell what 6 * 6 are doing. Is this arbitrary, or is it preventing some kind of dimension mismatch? If I am implementing my own capsule network with new dimensions, do I need to be careful about how I pick this value?
According to my understanding,
num_route_nodes
should be the length of the vote vectors that are used as input to dynamic routing.In the example code, this value is set according to:
32
appears to come from the previousout_channels
, but I can't tell what6 * 6
are doing. Is this arbitrary, or is it preventing some kind of dimension mismatch? If I am implementing my own capsule network with new dimensions, do I need to be careful about how I pick this value?Thanks,
Will
The text was updated successfully, but these errors were encountered: