1 files changed, 64 insertions, 0 deletions
diff --git a/Euclidean.lua b/Euclidean.lua
new file mode 100644
index 0000000..808b7ab
--- /dev/null
+++ b/Euclidean.lua
@@ -0,0 +1,64 @@
+local Euclidean, parent = torch.class('nn.Euclidean', 'nn.Module')
+
+function Euclidean:__init(inputSize,outputSize)
+   parent.__init(self)
+
+   self.weight = torch.Tensor(inputSize,outputSize)
+   self.gradWeight = torch.Tensor(inputSize,outputSize)
+
+   -- state
+   self.gradInput:resize(inputSize)
+   self.output:resize(outputSize)
+   self.temp = torch.Tensor(inputSize)
+
+   self:reset()
+end
+
+function Euclidean:reset(stdv)
+   if stdv then
+      stdv = stdv * math.sqrt(3)
+   else
+      stdv = 1./math.sqrt(self.weight:size(1))
+   end
+
+   for i=1,self.weight:size(2) do
+      self.weight:select(2, i):apply(function()
+                                        return torch.uniform(-stdv, stdv)
+                                     end)
+   end
+end
+
+function Euclidean:updateOutput(input)
+   self.output:zero()
+   for o = 1,self.weight:size(2) do
+      self.output[o] = input:dist(self.weight:select(2,o))
+   end
+   return self.output
+end
+
+function Euclidean:updateGradInput(input, gradOutput)
+   self:updateOutput(input)
+   if self.gradInput then
+      self.gradInput:zero()
+      for o = 1,self.weight:size(2) do
+         if self.output[o] ~= 0 then
+            self.temp:copy(input):add(-1,self.weight:select(2,o))
+            self.temp:mul(gradOutput[o]/self.output[o])
+            self.gradInput:add(self.temp)
+         end
+      end
+      return self.gradInput
+   end
+end
+
+function Euclidean:accGradParameters(input, gradOutput, scale)
+   self:updateOutput(input)
+   scale = scale or 1
+   for o = 1,self.weight:size(2) do
+      if self.output[o] ~= 0 then
+         self.temp:copy(self.weight:select(2,o)):add(-1,input)
+         self.temp:mul(gradOutput[o]/self.output[o])
+         self.gradWeight:select(2,o):add(self.temp)
+      end
+   end
+end