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------------------------------------------------------------------------
--[[ DepthConcat ]]--
-- Concatenates the output of Convolutions along the depth dimension
-- (nOutputFrame). This is used to implement the DepthConcat layer
-- of the Going deeper with convolutions paper :
-- http://arxiv.org/pdf/1409.4842v1.pdf
-- The normal Concat Module can't be used since the spatial dimensions
-- of tensors to be concatenated may have different values. To deal with
-- this, we select the largest spatial dimensions and add zero-padding
-- around the smaller dimensions.
------------------------------------------------------------------------
local DepthConcat, _ = torch.class('nn.DepthConcat', 'nn.Concat')
function DepthConcat:windowNarrow(output, currentOutput, offset)
local outputWindow = output:narrow(self.dimension, offset, currentOutput:size(self.dimension))
for dim=1,self.outputSize:size(1) do
local currentSize = currentOutput:size(dim)
if dim ~= self.dimension and self.outputSize[dim] ~= currentSize then
-- 5x5 vs 3x3 -> start = [(5-3)/2] + 1 = 2 (1 pad each side)
-- 9x9 vs 5x5 -> start = [(9-5)/2] + 1 = 3 (2 pad each side)
-- 9x9 vs 4x4 -> start = [(9-4)/2] + 1 = 3.5 (2 pad, 3 pad)
local start = math.floor(((self.outputSize[dim] - currentSize) / 2) + 1)
outputWindow = outputWindow:narrow(dim, start, currentSize)
end
end
return outputWindow
end
function DepthConcat: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)
for dim=1,self.outputSize:size(1) do
if dim ~= self.dimension then
-- take the maximum size (shouldn't change anything for batch dim)
self.outputSize[dim] = math.max(self.outputSize[dim], currentOutput:size(dim))
end
end
end
end
self.output:resize(self.outputSize):zero() --zero for padding
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = outs[i]
local outputWindow = self:windowNarrow(self.output, currentOutput, offset)
outputWindow:copy(currentOutput)
offset = offset + currentOutput:size(self.dimension)
end
return self.output
end
function DepthConcat:updateGradInput(input, gradOutput)
self.gradInput:resizeAs(input)
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = module.output
local gradOutputWindow = self:windowNarrow(gradOutput, currentOutput, offset)
local currentGradInput = self:rethrowErrors(module, i, 'updateGradInput', input, gradOutputWindow)
if i==1 then
self.gradInput:copy(currentGradInput)
else
self.gradInput:add(currentGradInput)
end
offset = offset + currentOutput:size(self.dimension)
end
return self.gradInput
end
function DepthConcat:accGradParameters(input, gradOutput, scale)
scale = scale or 1
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = module.output
local gradOutputWindow = self:windowNarrow(gradOutput, currentOutput, offset)
self:rethrowErrors(module, i, 'accGradParameters', input, gradOutputWindow, scale)
offset = offset + currentOutput:size(self.dimension)
end
end
function DepthConcat: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 gradOutputWindow = self:windowNarrow(gradOutput, currentOutput, offset)
local currentGradInput = self:rethrowErrors(module, i, 'backward', input, gradOutputWindow)
if i==1 then
self.gradInput:copy(currentGradInput)
else
self.gradInput:add(currentGradInput)
end
offset = offset + currentOutput:size(self.dimension)
end
return self.gradInput
end
function DepthConcat:accUpdateGradParameters(input, gradOutput, lr)
local offset = 1
for i,module in ipairs(self.modules) do
local currentOutput = module.output
local gradOutputWindow = self:windowNarrow(gradOutput, currentOutput, offset)
self:rethrowErrors(module, i, 'accUpdateGradParameters', input, gradOutputWindow, lr)
offset = offset + currentOutput:size(self.dimension)
end
end
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