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Threshold.lua
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Threshold.lua
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require 'nn'
require 'cltorch'
nn.Threshold.baseUpdateOutput = nn.Threshold.updateOutput
nn.Threshold.baseUpdateGradInput = nn.Threshold.updateGradInput
local function floatToString(val)
local valstring = tostring(val)
if valstring:find('%.') or valstring:find('e') then
valstring = valstring .. 'f'
end
return valstring
end
function nn.Threshold.updateOutput(self, input)
if torch.type(input) ~= 'torch.ClTensor' then
return self:baseUpdateOutput(input)
end
self.thresholdstring = floatToString(self.threshold)
self.valstring = floatToString(self.val)
if self.inplace then
input:apply_on_gpu("*out = (*out > " .. self.thresholdstring .. ") ? *out : " .. self.valstring)
self.output = input
else
self.output:resize(input:size())
self.output:map_on_gpu(input, "*out = ( *in1 > " .. self.thresholdstring .. ") ? *in1 : " .. self.valstring)
end
return self.output
end
function nn.Threshold.updateGradInput(self, input, gradOutput)
if torch.type(input) ~= 'torch.ClTensor' then
return self:baseUpdateGradInput(input, gradOutput)
end
local nElement = self.gradInput:nElement()
self.gradInput:resizeAs(input)
if self.gradInput:nElement() ~= nElement then
self.gradInput:zero()
end
if self.inplace then
gradOutput:map2_on_gpu(input, gradOutput, "*out = (*in1 > " .. self.thresholdstring .. ") ? *in2 : 0.0f")
self.gradInput = gradOutput
else
self.gradInput:map2_on_gpu(input, gradOutput, "*out = (*in1 > " .. self.thresholdstring .. ") ? *in2 : 0.0f")
end
return self.gradInput
end