您可以使用表模塊,看看這個頁面:https://github.com/torch/nn/blob/master/doc/table.md
net = nn.Sequential()
triple = nn.ParallelTable()
duplicate = nn.ConcatTable()
duplicate:add(nn.Identity())
duplicate:add(nn.Identity())
triple:add(duplicate)
triple:add(nn.Identity())
net:add(triple)
net:add(nn.FlattenTable())
-- at this point the network transforms {X,Y} into {X,X,Y}
separate = nn.ConcatTable()
separate:add(nn.SelectTable(1))
separate:add(nn.NarrowTable(2,2))
net:add(separate)
-- now you get {X,{X,Y}}
parallel_XY = nn.ParallelTable()
parallel_XY:add(nn.Identity()) -- preserves X
parallel_XY:add(...) -- whatever you want to do from {X,Y}
net:add(parallel)
parallel_Xresult = nn.ParallelTable()
parallel_Xresult:add(...) -- whatever you want to do from {X,result}
net:add(parallel_Xresult)
output = net:forward({X,Y})
的想法是先從{X,Y}
,複製X
並做你的作業。這顯然有點複雜,nngraph
應該是在這裏做的。
'X'是輸入還是網絡? – fonfonx
X和Y都是輸入。示例代碼只有一個輸入 –
那麼'X = nn.Sequential()'? – fonfonx