Hi all,
Is it possible to "multiply" a layer in channel direction, and have the parameter 'group' not be equal 1 (e.g.: 3 times the number of channels, and group = 3), and then finetune from weights trained on the original net? The weights in each group should all start from the original weights.
And what happens if you deploy it with the original weights?
Will caffe load the original weights for each of the groups, or will there just be an error (probably not), or will it just have random/starting weights for the two last groups while the first group gets the correct weights?
I was just wondering, because this would save me some copy-pasting of the whole net. And make the net.prototxt smaller.
A more general question would be: What happens if loading a net with weights that don't completely fit the original shape; is there any broadcasting happening?
Would be very cool if anyone has some experience with / knowledge in this :)