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local ClassNLLCriterion, parent = torch.class('nn.ClassNLLCriterion', 'nn.Criterion')
function ClassNLLCriterion:__init()
parent.__init(self)
self.sizeAverage = true
end
function ClassNLLCriterion:updateOutput(input, target)
if input:dim() == 1 then
self.output = -input[target]
elseif input:dim() == 2 then
local output = 0
for i=1,target:size(1) do
output = output - input[i][target[i]]
end
if self.sizeAverage then
output = output / target:size(1)
end
self.output = output
else
error('matrix or vector expected')
end
return self.output
end
function ClassNLLCriterion:updateGradInput(input, target)
self.gradInput:resizeAs(input)
self.gradInput:zero()
if input:dim() == 1 then
self.gradInput[target] = -1
else
local z = -1
if self.sizeAverage then
z = z / target:size(1)
end
local gradInput = self.gradInput
for i=1,target:size(1) do
gradInput[i][target[i]] = z
end
end
return self.gradInput
end
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