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local HardTanh, parent = torch.class('nn.HardTanh', 'nn.Module')
function HardTanh:__init(min_value, max_value, inplace)
parent.__init(self)
self.min_val = min_value or -1
self.max_val = max_value or 1
self.inplace = inplace or false
if (inplace and type(inplace) ~= 'boolean') then
error('in-place flag must be boolean')
end
assert(self.max_val>self.min_val, 'max_value must be larger than min_value')
end
function HardTanh:updateOutput(input)
self.min_val = self.min_val or -1
self.max_val = self.max_val or 1
input.THNN.HardTanh_updateOutput(
input:cdata(),
self.output:cdata(),
self.min_val,
self.max_val,
self.inplace or false
)
return self.output
end
function HardTanh:updateGradInput(input, gradOutput)
input.THNN.HardTanh_updateGradInput(
input:cdata(),
gradOutput:cdata(),
self.gradInput:cdata(),
self.min_val,
self.max_val,
self.inplace or false
)
return self.gradInput
end
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