norm-mwe.lua

require 'nn'
require 'image'

desc = nn.Sequential()
desc:add( nn.SpatialConvolution( 1, 10, 3, 3, 1, 1 ) )
desc:add( nn.Tanh() )
desc:add( nn.SpatialLPPooling( 10, 2, 2, 2 ) )
desc:add( nn.SpatialSubtractiveNormalization( 10, image.gaussian(5) ) )
desc:add( nn.View( 10, -1 ) )

x1 = torch.randn(5, 1, 64, 64)
x2 = torch.randn(5, 1, 64, 64)

s = nn.Sequential()
t = nn.ParallelTable()
t:add(desc)
--t:add(desc:clone())
t:add(desc:clone('weight', 'bias', 'gradWeight', 'gradBias'))
s:add(t):add(nn.PairwiseDistance(2))

y = s:forward({x1, x2})
print(y)