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- local Copy, parent = torch.class('nn.Copy', 'nn.Module')
-
- function Copy:__init(intype, outtype, forceCopy, dontCast)
- intype = intype or torch.Tensor.__typename
- outtype = outtype or torch.Tensor.__typename
-
- self.dontCast = dontCast
-
- parent.__init(self)
- self.gradInput = torch.getmetatable(intype).new()
- self.output = torch.getmetatable(outtype).new()
-
- if (not forceCopy) and intype == outtype then
-
- self.updateOutput = function(self, input)
- self.output:set(input)
- return input
- end
-
- self.updateGradInput = function(self, input, gradOutput)
- self.gradInput:set(gradOutput)
- return gradOutput
- end
- end
- end
-
- function Copy:updateOutput(input)
- self.output:resize(input:size()):copy(input)
- return self.output
- end
-
- function Copy:updateGradInput(input, gradOutput)
- self.gradInput:resize(gradOutput:size()):copy(gradOutput)
- return self.gradInput
- end
-
- function Copy:type(type, tensorCache)
- if type and self.dontCast then
- return self
- end
- return parent.type(self, type, tensorCache)
- end
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