refactoring Mean into Sum

1 files changed, 8 insertions, 35 deletions

diff --git a/Mean.lua b/Mean.lua
index 14ad0d1..8087ac9 100644
--- a/Mean.lua
+++ b/Mean.lua
@@ -1,41 +1,14 @@
-local Mean, parent = torch.class('nn.Mean', 'nn.Module')
+local Mean, parent = torch.class('nn.Mean', 'nn.Sum')
 
-function Mean:__init(dimension, nInputDims)
-   parent.__init(self)
-   dimension = dimension or 1
-   self.dimension = dimension
-   -- do not assign default value to nInputDims or it will break backward compatibility
-   self.nInputDims = nInputDims
-   self._gradInput = torch.Tensor()
-end
+--[[
 
-function Mean:_getPositiveDimension(input)
-   local dimension = self.dimension
-   if dimension < 0 then
-      dimension = input:dim() + dimension + 1
-   elseif self.nInputDims and input:dim()==(self.nInputDims+1) then
-      dimension = dimension + 1
-   end
-   return dimension
-end
+This file is still here because of backward compatibility.
 
-function Mean:updateOutput(input)
-   local dimension = self:_getPositiveDimension(input)
-   self.output:mean(input, dimension)
-   if self.output:nDimension() > 1 then
-      self.output = self.output:select(dimension, 1)
-   end
-   return self.output
-end
+Please use instead "nn.Sum(dimension, nInputDims, sizeAverage)"
+
+]]--
 
-function Mean:updateGradInput(input, gradOutput)
-   local dimension = self:_getPositiveDimension(input)
-   self._gradInput:resizeAs(gradOutput):copy(gradOutput)
-   self._gradInput:mul(1/input:size(dimension))
 
-   if input:nDimension() > 1 then
-      self._gradInput = nn.utils.addSingletonDimension(self._gradInput, dimension)
-   end
-   self.gradInput = self._gradInput:expandAs(input)
-   return self.gradInput
+function Mean:__init(dimension, nInputDims)
+   parent.__init(self, dimension, nInputDims, true)
 end