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local Padding, parent = torch.class('nn.Padding', 'nn.Module')
-- pad puts in [pad] amount of [value] over dimension [dim], starting at index [index] in that dimension. If pad<0, index counts from the left. If pad>0 index counts from the right
-- index = 1 pads before index 1. index = 2 pads starting before index 2 and after index 1 in dimension [dim]
function Padding:__init(dim, pad, nInputDim, value, index)
self.value = value or 0
self.index = index or 1
self.dim = dim
self.pad = pad
self.nInputDim = nInputDim
self.outputSize = torch.LongStorage()
parent.__init(self)
end
function Padding:updateOutput(input)
self.outputSize:resize(input:dim())
self.outputSize:copy(input:size())
local dim = self.dim
if self.nInputDim and input:dim() ~= self.nInputDim then
dim = dim + 1
end
self.outputSize[dim] = self.outputSize[dim] + math.abs(self.pad)
self.output:resize(self.outputSize)
self.output:fill(self.value)
local index = self.index
local pad = self.pad
if pad > 0 then
index = input:size(dim) - index + 2
else
pad = -pad
end
if index == 1 then
self.output:narrow(dim, 1 + pad, input:size(dim)):copy(input)
elseif index == input:size(dim) + 1 then
self.output:narrow(dim, 1, input:size(dim)):copy(input)
else
self.output:narrow(dim, 1, index - 1):copy(input:narrow(dim, 1, index - 1))
self.output:narrow(dim, index + pad, input:size(dim) - (index - 1)):copy(input:narrow(dim, index, input:size(dim) - (index - 1)))
end
return self.output
end
function Padding:updateGradInput(input, gradOutput)
self.gradInput:resizeAs(input)
local dim = self.dim
if self.nInputDim and input:dim() ~= self.nInputDim then
dim = dim + 1
end
local index = self.index
local pad = self.pad
if pad > 0 then
index = input:size(dim) - index + 2
else
pad = -pad
end
if index == 1 then
self.gradInput:copy(gradOutput:narrow(dim, 1 + pad, input:size(dim)))
elseif index == input:size(dim) + 1 then
self.gradInput:copy(gradOutput:narrow(dim, 1, input:size(dim)))
else
self.gradInput:narrow(dim, 1, index - 1):copy(gradOutput:narrow(dim, 1, index - 1))
self.gradInput:narrow(dim, index, input:size(dim) - (index - 1)):copy(gradOutput:narrow(dim, index + pad, input:size(dim) - (index - 1)))
end
return self.gradInput
end
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