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local SpatialConvolutionCUDA, parent = torch.class('nn.SpatialConvolutionCUDA', 'nn.Module')
function SpatialConvolutionCUDA:__init(nInputPlane, nOutputPlane, kW, kH, dW, dH)
parent.__init(self)
dW = dW or 1
dH = dH or 1
self.nInputPlane = nInputPlane
self.nOutputPlane = nOutputPlane
self.kW = kW
self.kH = kH
self.dW = dW
self.dH = dH
self.weight = torch.Tensor(nInputPlane, kH, kW, nOutputPlane)
self.gradWeight = torch.Tensor(nInputPlane, kH, kW, nOutputPlane)
self:reset()
end
function SpatialConvolutionCUDA:reset(stdv)
if stdv then
stdv = stdv * math.sqrt(3)
else
stdv = 1/math.sqrt(self.kW*self.kH*self.nInputPlane)
end
self.weight:uniform(-stdv, stdv)
end
function SpatialConvolutionCUDA:updateOutput(input)
return input.nn.SpatialConvolutionCUDA_updateOutput(self, input)
end
function SpatialConvolutionCUDA:updateGradInput(input, gradOutput)
return input.nn.SpatialConvolutionCUDA_updateGradInput(self, input, gradOutput)
end
function SpatialConvolutionCUDA:accGradParameters(input, gradOutput, scale)
return input.nn.SpatialConvolutionCUDA_accGradParameters(self, input, gradOutput, scale)
end
function SpatialConvolutionCUDA:copy(sc)
local weight = sc.weight:clone()
weight:resize(sc.nOutputPlane, sc.nInputPlane * sc.kH * sc.kW)
weight = weight:t():contiguous()
weight:resize(sc.nInputPlane, sc.kH, sc.kW, sc.nOutputPlane)
self.weight:copy(weight)
end
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