F1 network is not same as orignal paper

thanks for your sharing code and I have a question to ask you
1.the F1 network is not same as orignal paper,did you modify it?
2.in paper in the F1 network the first conv is CR(4,20,2,2), and 2 means weight sharing parameters, each map in conv evenly divided into 2 by 2 region ,and I don't know in F1 network where reflect 2 by 2 region?

[luoyetx]

Since Caffe doesn't support Local Convolution Layer, Yes, I modify the network structure and use the traditional Convolution Layer.

[liz6688]

@luoyetx cafffe doesn't support local convolution layer, which deep learning toolbox support?

[luoyetx]

@liz6688 I'm using no local convolution layer. Just traditional convolution layer and some modifications to the network structure.

[liz6688]

@luoyetx I'm trying to implement the F1 network as orignal paper, do you know which deep learning toolbox support local convolution layer?

[luoyetx]

@liz6688 It seems torch support local convolution layer, look docs here, but it's Lua, and seems pytorch current don't have this feature, track this issue. Actually, Caffe does have unofficial implement of Local Conv, view this issue for more information.

[liz6688]

@luoyetx THX