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local Threshold, parent = torch.class('nn.Threshold','nn.Module')
function Threshold:__init(th,v,ip)
parent.__init(self)
self.threshold = th or 1e-6
self.val = v or 0
if (th and type(th) ~= 'number') or (v and type(v) ~= 'number') then
error('nn.Threshold(threshold, value)')
end
-- default for inplace is false
self.inplace = ip or false
if (ip and type(ip) ~= 'boolean') then
error('in-place flag must be boolean')
end
self:validateParameters()
end
function Threshold:updateOutput(input)
self:validateParameters()
input.THNN.Threshold_updateOutput(
input:cdata(),
self.output:cdata(),
self.threshold,
self.val,
self.inplace
)
return self.output
end
function Threshold:updateGradInput(input, gradOutput)
self:validateParameters()
input.THNN.Threshold_updateGradInput(
input:cdata(),
gradOutput:cdata(),
self.gradInput:cdata(),
self.threshold,
self.val,
self.inplace
)
return self.gradInput
end
function Threshold:validateParameters()
self.inplace = self.inplace or false -- backwards compatibility pre inplace
if self.inplace then
if self.val > self.threshold then
error('in-place processing requires value (' .. self.val ..
') not exceed threshold (' .. self.threshold .. ')')
end
end
end
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