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local VolumetricMaxUnpooling, parent = torch.class('nn.VolumetricMaxUnpooling', 'nn.Module')
function VolumetricMaxUnpooling:__init(poolingModule)
parent.__init(self)
assert(torch.type(poolingModule)=='nn.VolumetricMaxPooling', 'Argument must be a nn.VolumetricMaxPooling module')
assert(poolingModule.kT==poolingModule.dT and poolingModule.kH==poolingModule.dH and poolingModule.kW==poolingModule.dW, "The size of pooling module's kernel must be equal to its stride")
self.pooling = poolingModule
end
function VolumetricMaxUnpooling:setParams()
self.indices = self.pooling.indices
self.otime = self.pooling.itime
self.oheight = self.pooling.iheight
self.owidth = self.pooling.iwidth
self.dT = self.pooling.dT
self.dH = self.pooling.dH
self.dW = self.pooling.dW
self.padT = self.pooling.padT
self.padH = self.pooling.padH
self.padW = self.pooling.padW
end
function VolumetricMaxUnpooling:updateOutput(input)
self:setParams()
input.THNN.VolumetricMaxUnpooling_updateOutput(
input:cdata(),
self.output:cdata(),
self.indices:cdata(),
self.otime, self.owidth, self.oheight,
self.dT, self.dW, self.dH,
self.padT, self.padW, self.padH
)
return self.output
end
function VolumetricMaxUnpooling:updateGradInput(input, gradOutput)
self:setParams()
input.THNN.VolumetricMaxUnpooling_updateGradInput(
input:cdata(),
gradOutput:cdata(),
self.gradInput:cdata(),
self.indices:cdata(),
self.otime, self.owidth, self.oheight,
self.dT, self.dW, self.dH,
self.padT, self.padW, self.padH
)
return self.gradInput
end
function VolumetricMaxUnpooling:empty()
self:clearState()
end
function VolumetricMaxUnpooling:__tostring__()
return 'nn.VolumetricMaxUnpooling associated to '..tostring(self.pooling)
end
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