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require 'nn'
require 'graph'
nngraph = {}
torch.include('nngraph','nest.lua')
torch.include('nngraph','node.lua')
torch.include('nngraph','gmodule.lua')
torch.include('nngraph','graphinspecting.lua')
torch.include('nngraph','JustTable.lua')
torch.include('nngraph','ModuleFromCriterion.lua')
-- handy functions
local utils = paths.dofile('utils.lua')
local istensor = torch.isTensor
local istable = utils.istable
local istorchclass = utils.istorchclass
-- simpler todot functions
nngraph.simple_print = paths.dofile('simple_print.lua')
-- Modify the __call function to hack into nn.Module
local Module = torch.getmetatable('nn.Module')
function Module:__call__(...)
local nArgs = select("#", ...)
assert(nArgs <= 1, 'Use {input1, input2} to pass multiple inputs.')
local input = ...
if nArgs == 1 and input == nil then
error(utils.expectingNodeErrorMessage(input, 'inputs', 1))
end
-- Disallow passing empty table, in case someone passes a table with some
-- typo'd variable name in.
if type(input) == 'table' and next(input) == nil then
error('cannot pass an empty table of inputs. To indicate no incoming ' ..
'connections, leave the second set of parens blank.')
end
if not istable(input) then
input = {input}
end
local mnode = nngraph.Node({module=self})
local dnode
for i = 1, table.maxn(input) do
dnode = input[i]
if torch.typename(dnode) ~= 'nngraph.Node' then
error(utils.expectingNodeErrorMessage(dnode, 'inputs', i))
end
mnode:add(dnode,true)
end
return mnode
end
local Criterion = torch.getmetatable('nn.Criterion')
function Criterion:__call__(...)
return nn.ModuleFromCriterion(self)(...)
end
return nngraph
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