1 files changed, 5 insertions, 25 deletions
diff --git a/DistNLLCriterion.lua b/DistNLLCriterion.lua
index 01290c4..22204fc 100644
--- a/DistNLLCriterion.lua
+++ b/DistNLLCriterion.lua
@@ -17,7 +17,7 @@ end
 function DistNLLCriterion:normalize(input, target)
    -- normalize target
    if not self.targetIsProbability then
-      self.probTarget = self.targetSoftMax:forward(target)
+      self.probTarget = self.targetSoftMax:updateOutput(target)
    else
       self.probTarget = target
    end
@@ -31,7 +31,7 @@ function DistNLLCriterion:normalize(input, target)
 
    -- normalize input
    if not self.inputIsLogProbability and not self.inputIsProbability then
-      self.logProbInput = self.inputLogSoftMax:forward(self.input)
+      self.logProbInput = self.inputLogSoftMax:updateOutput(self.input)
    elseif not self.inputIsLogProbability then
       print('TODO: implement nn.Log()')
    else
@@ -42,7 +42,7 @@ end
 function DistNLLCriterion:denormalize()
    -- denormalize gradients
    if not self.inputIsLogProbability and not self.inputIsProbability then
-      self.gradInput = self.inputLogSoftMax:backward(self.input, self.gradLogInput)
+      self.gradInput = self.inputLogSoftMax:updateGradInput(self.input, self.gradLogInput)
    elseif not self.inputIsLogProbability then
       print('TODO: implement nn.Log()')
    else
@@ -55,7 +55,7 @@ function DistNLLCriterion:denormalize()
    end
 end
 
-function DistNLLCriterion:forward(input, target)
+function DistNLLCriterion:updateOutput(input, target)
    self:normalize(input, target)
    self.output = 0
    for i = 1,input:size(1) do
@@ -64,7 +64,7 @@ function DistNLLCriterion:forward(input, target)
    return self.output
 end
 
-function DistNLLCriterion:backward(input, target)
+function DistNLLCriterion:updateGradInput(input, target)
    self:normalize(input, target)
    self.gradLogInput:resizeAs(input)
    for i = 1,input:size(1) do
@@ -73,23 +73,3 @@ function DistNLLCriterion:backward(input, target)
    self:denormalize()
    return self.gradInput
 end
-
-function DistNLLCriterion:write(file)
-   parent.write(self, file)
-   file:writeBool(self.inputIsProbability)
-   file:writeBool(self.inputIsLogProbability)
-   file:writeBool(self.targetIsProbability)
-   file:writeObject(self.targetSoftMax)
-   file:writeObject(self.inputLogSoftMax)
-   file:writeObject(self.gradLogInput)
-end
-
-function DistNLLCriterion:read(file)
-   parent.read(self, file)
-   self.inputIsProbability = file:readBool()
-   self.inputIsLogProbability = file:readBool()
-   self.targetIsProbability = file:readBool()
-   self.targetSoftMax = file:readObject()
-   self.inputLogSoftMax = file:readObject()
-   self.gradLogInput = file:readObject()
-end