fcn

convertLiner2Conv.lua

require 'nn'

-- you just need to provide the linear module you want to convert,
-- and the dimensions of the field of view of the linear layer
function convertLinear2Conv1x1(linmodule,in_size)
   local s_in = linmodule.weight:size(2)/(in_size[1]*in_size[2])
   local s_out = linmodule.weight:size(1)
   local convmodule = nn.SpatialConvolutionMM(s_in,s_out,in_size[1],in_size[2],1,1)
   convmodule.weight:copy(linmodule.weight)
   convmodule.bias:copy(linmodule.bias)
   return convmodule
end

input = torch.rand(3,6,6)

m = nn.Linear(3*6*6,10)

mm = convertLinear2Conv1x1(m,{6,6})

output_lin = m:forward(input:view(3*6*6))
output_conv = mm:forward(input)