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node.lua
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local utils = paths.dofile('utils.lua')
local istensor = torch.isTensor
local istable = utils.istable
local istorchclass = utils.istorchclass
require 'debug'
local nnNode,parent = torch.class('nngraph.Node','graph.Node')
function nnNode:__init(data)
parent.__init(self,data)
self.data.annotations = self.data.annotations or {}
self.data.mapindex = self.data.mapindex or {}
if not self.data.annotations._debugLabel then
self:_makeDebugLabel(debug.getinfo(6, 'Sl'))
end
end
--[[ Build a string label which will be used a tooltip when
making a graph.]]
function nnNode:_makeDebugLabel(dinfo)
if dinfo then
self.data.annotations._debugLabel = string.format('[%s]:%d',
dinfo.short_src, dinfo.currentline, dinfo.name)
end
end
-- domap ensures that this node will keep track of the order its children are added.
-- mapindex is a forward/backward list
-- index = self.data.mapindex[child.data]
-- child.data = self.data.mapindex[index]
function nnNode:add(child,domap)
parent.add(self,child)
if domap then
local mapindex = self.data.mapindex
local data = child.data
assert(not mapindex[data], "Don't pass the same input twice.")
table.insert(mapindex,data)
mapindex[data] = #mapindex
end
end
-- this function returns noutput number of new nodes
-- that each take a single component of the output of this
-- node in the order they are returned.
function nnNode:split(noutput)
assert(noutput >= 2, "splitting to one output is not supported")
local debugLabel = self.data.annotations._debugLabel
local mnode = nngraph.Node({nSplitOutputs=noutput, annotations={_debugLabel=debugLabel .. '-mnode'}})
mnode:add(self,true)
local selectnodes = {}
for i=1,noutput do
local node = nngraph.Node({selectindex=i,input={}, annotations={_debugLabel=debugLabel .. '-' .. i}})
node:add(mnode,true)
table.insert(selectnodes,node)
end
return unpack(selectnodes)
end
function nnNode:annotate(annotations)
for k, v in pairs(annotations) do
self.data.annotations[k] = v
end
return self
end
function nnNode:graphNodeName()
if self.data.annotations.name then
return self.data.annotations.name .. ' (' .. self.id .. ')'
else
return 'Node' .. self.id
end
end
function nnNode:graphNodeAttributes()
self.data.annotations.graphAttributes =
self.data.annotations.graphAttributes or {}
if not self.data.annotations.graphAttributes.tooltip then
self.data.annotations.graphAttributes.tooltip =
self.data.annotations._debugLabel
end
return self.data.annotations.graphAttributes
end
local function getNanFlag(data)
if data:nElement() == 0 then
return ''
end
local isNan = (data:ne(data):sum() > 0)
if isNan then
return 'NaN'
end
if data:max() == math.huge then
return 'inf'
end
if data:min() == -math.huge then
return '-inf'
end
return ''
end
function nnNode:label()
local lbl = {}
local function getstr(data)
if not data then return '' end
if istensor(data) then
local nanFlag = getNanFlag(data)
local tensorType = 'Tensor'
if data:type() ~= torch.Tensor():type() then
tensorType = data:type()
end
return tensorType .. '[' .. table.concat(data:size():totable(),'x') .. ']' .. nanFlag
elseif istable(data) then
local tstr = {}
for i,v in ipairs(data) do
table.insert(tstr, getstr(v))
end
return '{' .. table.concat(tstr,',') .. '}'
else
return tostring(data):gsub('\n','\\l')
end
end
local function getmapindexstr(mapindex)
local tstr = {}
for i,data in ipairs(mapindex) do
local inputId = 'Node' .. (data.forwardNodeId or '')
table.insert(tstr, inputId)
end
return '{' .. table.concat(tstr,',') .. '}'
end
for k,v in pairs(self.data) do
local vstr = ''
if k== 'mapindex' then
if #v > 1 then
vstr = getmapindexstr(v)
table.insert(lbl, k .. ' = ' .. vstr)
end
elseif k== 'forwardNodeId' or k== 'annotations' then
-- the forwardNodeId is not displayed in the label.
else
vstr = getstr(v)
table.insert(lbl, k .. ' = ' .. vstr)
end
end
local desc
if self.data.annotations.description then
desc = 'desc = ' .. self.data.annotations.description .. '\\n'
else
desc = ''
end
return desc .. table.concat(lbl,"\\l")
end