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Parallel.lua
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Parallel.lua
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local Parallel, parent = torch.class('nn.Parallel', 'nn.Container')
function Parallel:__init(inputDimension,outputDimension)
parent.__init(self)
self.modules = {}
self.inputDimension = inputDimension
self.outputDimension = outputDimension
end
function Parallel:updateOutput(input)
local nModule=input:size(self.inputDimension)
local outputs = {}
self.totalOutputSize = self.totalOutputSize or torch.LongStorage()
local totalOutputSize = self.totalOutputSize
for i=1,nModule do
local currentInput = input:select(self.inputDimension,i)
local currentOutput = self.modules[i]:updateOutput(currentInput)
table.insert(outputs, currentOutput)
local outputSize = currentOutput:size(self.outputDimension)
if i == 1 then
totalOutputSize:resize(currentOutput:dim()):copy(currentOutput:size())
else
totalOutputSize[self.outputDimension] = totalOutputSize[self.outputDimension] + outputSize
end
end
self.output:resize(totalOutputSize)
local offset = 1
for i=1,nModule do
local currentOutput = outputs[i]
local outputSize = currentOutput:size(self.outputDimension)
self.output:narrow(self.outputDimension, offset, outputSize):copy(currentOutput)
offset = offset + currentOutput:size(self.outputDimension)
end
return self.output
end
function Parallel:updateGradInput(input, gradOutput)
local nModule=input:size(self.inputDimension)
self.gradInput:resizeAs(input)
local offset = 1
for i=1,nModule do
local module=self.modules[i]
local currentInput = input:select(self.inputDimension,i)
local currentOutput = module.output
local outputSize = currentOutput:size(self.outputDimension)
local currentGradOutput = gradOutput:narrow(self.outputDimension, offset, outputSize)
local currentGradInput = module:updateGradInput(currentInput, currentGradOutput)
self.gradInput:select(self.inputDimension,i):copy(currentGradInput)
offset = offset + outputSize
end
return self.gradInput
end
function Parallel:accGradParameters(input, gradOutput, scale)
local nModule=input:size(self.inputDimension)
local offset = 1
for i=1,nModule do
local module = self.modules[i]
local currentOutput = module.output
local outputSize = currentOutput:size(self.outputDimension)
module:accGradParameters(
input:select(self.inputDimension,i),
gradOutput:narrow(self.outputDimension, offset,outputSize),
scale
)
offset = offset + outputSize
end
end
function Parallel:accUpdateGradParameters(input, gradOutput, lr)
local nModule=input:size(self.inputDimension)
local offset = 1
for i=1,nModule do
local module = self.modules[i];
local currentOutput = module.output
module:accUpdateGradParameters(
input:select(self.inputDimension,i),
gradOutput:narrow(self.outputDimension, offset,
currentOutput:size(self.outputDimension)),
lr)
offset = offset + currentOutput:size(self.outputDimension)
end
end
function Parallel:__tostring__()
local tab = ' '
local line = '\n'
local next = ' |`-> '
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 .. next .. '(' .. 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