From 3ce35f0bac29d4a9645ba71ee9a6cde6d93091d2 Mon Sep 17 00:00:00 2001
From: Jonathan Tompson <tompson@cims.nyu.edu>
Date: Mon, 21 Oct 2013 14:12:18 -0400
Subject: going back on Clement's suggestion.  It was a good idea, but we're
 needlessly loosing performance in the 1D case with the input clone.

---
 PairwiseDistance.lua | 78 ++++++++++++++++++++++++++--------------------------
 1 file changed, 39 insertions(+), 39 deletions(-)

diff --git a/PairwiseDistance.lua b/PairwiseDistance.lua
index f9f77f2..79569c9 100644
--- a/PairwiseDistance.lua
+++ b/PairwiseDistance.lua
@@ -11,26 +11,27 @@ function PairwiseDistance:__init(p)
 end 
   
 function PairwiseDistance:updateOutput(input)
-   if input[1]:dim() > 2 then
-      error('input must be vector or matrix')
-   end
    if input[1]:dim() == 1 then
-     -- Reshape the input so it always looks like a batch (avoids multiple
-     -- code-paths).  (Clement's good suggestion)
-     input[1]:resize(1,input[1]:size(1))
-     input[2]:resize(1,input[2]:size(1))
-   end
- 
-   self.diff:resizeAs(input[1])
-   self.diff:zero()
-   self.diff:add(input[1], -1, input[2])
-   self.diff:abs()
+      self.output[1]=input[1]:dist(input[2],self.norm)
+   elseif input[1]:dim() == 2 then
+      self.diff = self.diff or input[1].new()
+      self.diff:resizeAs(input[1])
 
-   self.output:resize(input[1]:size(1))
-   self.output:zero()
-   self.output:add(self.diff:pow(self.norm):sum(2))
-   self.output:pow(1./self.norm)
+      local diff = self.diff:zero()
+      diff:add(input[1], -1, input[2])
+      diff:abs()
 
+      self.output:resize(input[1]:size(1))
+      self.output:zero()
+      self.output:add(diff:pow(self.norm):sum(2))
+      self.output:pow(1./self.norm)
+   else
+      error('input must be vector or matrix')
+   end
+   if input[1]:dim() > 2 then
+      error('input must be vector or matrix')
+   end  
+ 
    return self.output
 end
 
@@ -44,13 +45,6 @@ function PairwiseDistance:updateGradInput(input, gradOutput)
       error('input must be vector or matrix')
    end
 
-   if input[1]:dim() == 1 then
-     -- Reshape the input so it always looks like a batch (avoids multiple
-     -- code-paths).  (Clement's good suggestion)
-     input[1]:resize(1,input[1]:size(1))
-     input[2]:resize(1,input[2]:size(1))
-   end
-
    self.gradInput[1]:resize(input[1]:size()) 
    self.gradInput[2]:resize(input[2]:size()) 
    self.gradInput[1]:copy(input[1])
@@ -65,24 +59,30 @@ function PairwiseDistance:updateGradInput(input, gradOutput)
         self.gradInput[1]:cmul(self.gradInput[1]:clone():abs():pow(self.norm-2))
      end
 
-     self.outExpand = self.outExpand or self.output.new()
-     self.outExpand:resize(self.output:size(1), 1)
-     self.outExpand:copy(self.output)
-     self.outExpand:add(1.0e-6)  -- Prevent divide by zero errors
-     self.outExpand:pow(-(self.norm-1))
-     self.gradInput[1]:cmul(self.outExpand:expand(self.gradInput[1]:size(1),
-        self.gradInput[1]:size(2)))
+     if (input[1]:dim() > 1) then
+        self.outExpand = self.outExpand or self.output.new()
+        self.outExpand:resize(self.output:size(1), 1)
+        self.outExpand:copy(self.output)
+        self.outExpand:add(1.0e-6)  -- Prevent divide by zero errors
+        self.outExpand:pow(-(self.norm-1))
+        self.gradInput[1]:cmul(self.outExpand:expand(self.gradInput[1]:size(1),
+           self.gradInput[1]:size(2)))
+     else
+        self.gradInput[1]:mul(math.pow(self.output[1] + 1e-6, -(self.norm-1)))
+     end
    end
-   
-   self.grad = self.grad or gradOutput.new()
-   self.ones = self.ones or gradOutput.new()
+   if input[1]:dim() == 1 then
+      self.gradInput[1]:mul(gradOutput[1])
+   else
+      self.grad = self.grad or gradOutput.new()
+      self.ones = self.ones or gradOutput.new()
 
-   self.grad:resizeAs(input[1]):zero()
-   self.ones:resize(input[1]:size(2)):fill(1)
+      self.grad:resizeAs(input[1]):zero()
+      self.ones:resize(input[1]:size(2)):fill(1)
 
-   self.grad:addr(gradOutput, self.ones)
-   self.gradInput[1]:cmul(self.grad)
-   
+      self.grad:addr(gradOutput, self.ones)
+      self.gradInput[1]:cmul(self.grad)
+   end
    self.gradInput[2]:zero():add(-1, self.gradInput[1])
    return self.gradInput
 end
-- 
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