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.
31 lines
908 B
Lua
31 lines
908 B
Lua
if nn.LeakyReLU then
|
|
return nn.LeakyReLU
|
|
end
|
|
|
|
local LeakyReLU, parent = torch.class('nn.LeakyReLU','nn.Module')
|
|
|
|
function LeakyReLU:__init(negative_scale)
|
|
parent.__init(self)
|
|
self.negative_scale = negative_scale or 0.333
|
|
self.negative = torch.Tensor()
|
|
end
|
|
|
|
function LeakyReLU:updateOutput(input)
|
|
self.output:resizeAs(input):copy(input):abs():add(input):div(2)
|
|
self.negative:resizeAs(input):copy(input):abs():add(-1.0, input):mul(-0.5*self.negative_scale)
|
|
self.output:add(self.negative)
|
|
|
|
return self.output
|
|
end
|
|
|
|
function LeakyReLU:updateGradInput(input, gradOutput)
|
|
self.gradInput:resizeAs(gradOutput)
|
|
-- filter positive
|
|
self.negative:sign():add(1)
|
|
torch.cmul(self.gradInput, gradOutput, self.negative)
|
|
-- filter negative
|
|
self.negative:add(-1):mul(-1 * self.negative_scale):cmul(gradOutput)
|
|
self.gradInput:add(self.negative)
|
|
|
|
return self.gradInput
|
|
end
|