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Concat.lua
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Concat.lua
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local Concat, parent = torch.class('nn.Concat', 'nn.Container')
function Concat:__init(dimension)
parent.__init(self)
self.outputSize = torch.LongStorage()
self.dimension = dimension
end
function Concat:updateOutput(input)
self.outputSize = self.outputSize or torch.LongStorage()
local outs = {}
for i=1,#self.modules do
local currentOutput = self:rethrowErrors(self.modules[i], i, 'updateOutput', input)
outs[i] = currentOutput
if i == 1 then
self.outputSize:resize(currentOutput:dim()):copy(currentOutput:size())
else
self.outputSize[self.dimension] = self.outputSize[self.dimension] + currentOutput:size(self.dimension)
end
end
self.output:resize(self.outputSize)
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = outs[i]
self.output:narrow(self.dimension, offset, currentOutput:size(self.dimension)):copy(currentOutput)
offset = offset + currentOutput:size(self.dimension)
end
return self.output
end
function Concat:updateGradInput(input, gradOutput)
self.gradInput:resizeAs(input)
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = module.output
local currentGradInput = self:rethrowErrors(module, i, 'updateGradInput', input, gradOutput:narrow(self.dimension, offset, currentOutput:size(self.dimension)))
if currentGradInput then -- if the module does not produce a gradInput (for example first layer), then ignore it and move on.
if i==1 then
self.gradInput:copy(currentGradInput)
else
self.gradInput:add(currentGradInput)
end
end
offset = offset + currentOutput:size(self.dimension)
end
return self.gradInput
end
function Concat:accGradParameters(input, gradOutput, scale)
scale = scale or 1
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = module.output
self:rethrowErrors(module, i, 'accGradParameters',
input,
gradOutput:narrow(self.dimension, offset, currentOutput:size(self.dimension)),
scale)
offset = offset + currentOutput:size(self.dimension)
end
end
function Concat:backward(input, gradOutput, scale)
self.gradInput:resizeAs(input)
scale = scale or 1
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = module.output
local currentGradInput = self:rethrowErrors(module, i, 'backward', input, gradOutput:narrow(self.dimension, offset, currentOutput:size(self.dimension)), scale)
if currentGradInput then -- if the module does not produce a gradInput (for example first layer), then ignore it and move on.
if i==1 then
self.gradInput:copy(currentGradInput)
else
self.gradInput:add(currentGradInput)
end
end
offset = offset + currentOutput:size(self.dimension)
end
return self.gradInput
end
function Concat:accUpdateGradParameters(input, gradOutput, lr)
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = module.output
self:rethrowErrors(module, i, 'accUpdateGradParameters',
input,
gradOutput:narrow(self.dimension, offset, currentOutput:size(self.dimension)),
lr)
offset = offset + currentOutput:size(self.dimension)
end
end
function Concat:__tostring__()
local tab = ' '
local line = '\n'
local next = ' |`-> '
local lastNext = ' `-> '
local ext = ' | '
local extlast = ' '
local last = ' ... -> '
local str = torch.type(self)
str = str .. ' {' .. line .. tab .. 'input'
for i=1,#self.modules do
if i == #self.modules then
str = str .. line .. tab .. lastNext .. '(' .. i .. '): ' .. tostring(self.modules[i]):gsub(line, line .. tab .. extlast)
else
str = str .. line .. tab .. next .. '(' .. i .. '): ' .. tostring(self.modules[i]):gsub(line, line .. tab .. ext)
end
end
str = str .. line .. tab .. last .. 'output'
str = str .. line .. '}'
return str
end