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local Mul, parent = torch.class('nn.Mul', 'nn.Module')
function Mul:__init()
parent.__init(self)
self.weight = torch.Tensor(1)
self.gradWeight = torch.Tensor(1)
self:reset()
end
function Mul:reset(stdv)
if stdv then
stdv = stdv * math.sqrt(3)
else
stdv = 1./math.sqrt(self.weight:size(1))
end
self.weight:uniform(-stdv, stdv);
end
function Mul:updateOutput(input)
self.output:resizeAs(input):copy(input);
self.output:mul(self.weight[1]);
return self.output
end
function Mul:updateGradInput(input, gradOutput)
self.gradInput:resizeAs(input):zero()
self.gradInput:add(self.weight[1], gradOutput)
return self.gradInput
end
function Mul:accGradParameters(input, gradOutput, scale)
scale = scale or 1
self.gradWeight[1] = self.gradWeight[1] + scale*input:dot(gradOutput);
end
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