8dea362bed
- Memory compression by snappy (lua-csnappy) - Use RGB-wise Weighted MSE(R*0.299, G*0.587, B*0.114) instead of MSE - Aggressive cropping for edge region and some change.
25 lines
728 B
Lua
25 lines
728 B
Lua
local RGBWeightedMSECriterion, parent = torch.class('mynn.RGBWeightedMSECriterion','nn.Criterion')
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function RGBWeightedMSECriterion:__init(w)
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parent.__init(self)
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self.weight = w:clone()
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self.diff = torch.Tensor()
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self.loss = torch.Tensor()
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end
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function RGBWeightedMSECriterion:updateOutput(input, target)
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self.diff:resizeAs(input):copy(input)
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for i = 1, input:size(1) do
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self.diff[i]:add(-1, target[i]):cmul(self.weight)
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end
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self.loss:resizeAs(self.diff):copy(self.diff):cmul(self.diff)
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self.output = self.loss:mean()
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return self.output
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end
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function RGBWeightedMSECriterion:updateGradInput(input, target)
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self.gradInput:resizeAs(input):copy(self.diff)
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return self.gradInput
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end
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