--- a
+++ b/code/expand.lua
@@ -0,0 +1,66 @@
+function expand(net)
+	convCount = 0
+	poolCount = 0
+	for i=1,net:size() do
+		if torch.typename(net:get(i)) == 'nn.SpatialConvolution' then
+			convCount = convCount + 1
+			nInputPlane = net:get(i).nInputPlane
+			nOutputPlane = net:get(i).nOutputPlane
+			kW = net:get(i).kW
+			kH = net:get(i).kH
+			dilationW = 2^(convCount-1)
+			dilationH = 2^(convCount-1)
+			net:insert(nn.SpatialDilatedConvolution(nInputPlane,nOutputPlane,kW,kH,1,1,0,0,dilationW,dilationH), i+1)
+			net:get(i+1).weight = net:get(i).weight
+			net:get(i+1).bias = net:get(i).bias
+			net:remove(i)
+		elseif torch.typename(net:get(i)) == 'nn.SpatialMaxPooling' then
+			poolCount = poolCount + 1
+			kW = net:get(i).kW
+			kH = net:get(i).kH
+			dilationW = 2^(poolCount-1)
+			dilationH = 2^(poolCount-1)
+			net:insert(nn.SpatialDilatedMaxPooling(kW,kH,1,1,0,0,dilationW,dilationH), i+1)
+			net:get(i+1).weight = net:get(i).weight
+			net:get(i+1).bias = net:get(i).bias
+			net:remove(i)
+		elseif torch.typename(net:get(i)) == 'nn.View' then
+			net:insert(nn.Identity(),i+1)
+			net:remove(i)
+		elseif torch.typename(net:get(i)) == 'nn.Linear' then
+			convCount = convCount + 1
+			j = i - 1
+			while true do
+				if torch.typename(net:get(j)) == 'nn.SpatialDilatedConvolution' then
+					break
+				end
+				j = j - 1
+			end
+			local nInputPlane = net:get(j).nOutputPlane
+
+			local outputSize = net:get(i).weight:size(1)
+			local inputSize = net:get(i).weight:size(2)
+
+			local nOutputPlane = outputSize
+			kW = torch.sqrt(inputSize/nInputPlane)
+			kH = kW
+			dilationW = 2^(convCount-1)
+			dilationH = 2^(convCount-1)
+
+			net:insert(nn.SpatialDilatedConvolution(nInputPlane,nOutputPlane,kW,kH,1,1,0,0,dilationW,dilationH), i+1)
+			net:get(i+1).weight = net:get(i).weight:resize(nOutputPlane,nInputPlane,kH,kW)
+			net:get(i+1).bias = net:get(i).bias
+			net:remove(i)
+		elseif torch.typename(net:get(i)) == 'nn.LogSoftMax' then
+			net:insert(nn.SpatialLogSoftMax(), i+1)
+			net:remove(i)
+		end
+	end
+	for i=net:size(),1,-1 do
+		if torch.typename(net:get(i)) == 'nn.Identity' then
+			net:remove(i)
+		end
+	end
+
+	return net
+end