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local PReLU, parent = torch.class('nn.PReLU','nn.Module')
function PReLU:__init(nOutputPlane)
parent.__init(self)
-- if no argument provided, use shared model (weight is scalar)
self.nOutputPlane = nOutputPlane or 0
self.weight = torch.Tensor(nOutputPlane or 1):fill(0.25)
self.gradWeight = torch.Tensor(nOutputPlane or 1)
end
function PReLU:updateOutput(input)
input.THNN.PReLU_updateOutput(
input:cdata(),
self.output:cdata(),
self.weight:cdata(),
self.nOutputPlane
)
return self.output
end
function PReLU:updateGradInput(input, gradOutput)
input.THNN.PReLU_updateGradInput(
input:cdata(),
gradOutput:cdata(),
self.gradInput:cdata(),
self.weight:cdata(),
self.nOutputPlane
)
return self.gradInput
end
function PReLU:accGradParameters(input, gradOutput, scale)
self.gradWeightBuf = self.gradWeightBuf or input.new()
self.gradWeightBuf2 = self.gradWeightBuf2 or input.new()
input.THNN.PReLU_accGradParameters(
input:cdata(),
gradOutput:cdata(),
self.gradInput:cdata(),
self.weight:cdata(),
self.gradWeight:cdata(),
self.gradWeightBuf:cdata(),
self.gradWeightBuf2:cdata(),
self.nOutputPlane,
scale or 1
)
return self.gradWeight
end
function PReLU:clearState()
nn.utils.clear(self, 'gradWeightBuf', 'gradWeightBuf2')
return parent.clearState(self)
end
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