Add ShakeShakeTable

lib/ShakeShakeTable.lua

@@ -0,0 +1,42 @@
+local ShakeShakeTable, parent = torch.class('w2nn.ShakeShakeTable','nn.Module')
+
+function ShakeShakeTable:__init()
+   parent.__init(self)
+   self.alpha = torch.Tensor()
+   self.beta = torch.Tensor()
+   self.first = torch.Tensor()
+   self.second = torch.Tensor()
+   self.train = true
+end
+function ShakeShakeTable:updateOutput(input)
+   local batch_size = input[1]:size(1)
+   if self.train then
+      self.alpha:resize(batch_size):uniform()
+      self.beta:resize(batch_size):uniform()
+      self.second:resizeAs(input[1]):copy(input[2])
+      for i = 1, batch_size do
+	 self.second[i]:mul(self.alpha[i])
+      end
+      self.output:resizeAs(input[1]):copy(input[1])
+      for i = 1, batch_size do
+	 self.output[i]:mul(1.0 - self.alpha[i])
+      end
+      self.output:add(self.second):mul(2)
+   else
+      self.output:resizeAs(input[1]):copy(input[1]):add(input[2])
+   end
+   return self.output
+end
+function ShakeShakeTable:updateGradInput(input, gradOutput)
+   local batch_size = input[1]:size(1)
+   self.first:resizeAs(gradOutput):copy(gradOutput)
+   for i = 1, batch_size do
+      self.first[i]:mul(self.beta[i])
+   end
+   self.second:resizeAs(gradOutput):copy(gradOutput)
+   for i = 1, batch_size do
+      self.second[i]:mul(1.0 - self.beta[i])
+   end
+   self.gradOutput = {self.first, self.second}
+   return self.gradOutput
+end

lib/w2nn.lua

@@ -74,5 +74,6 @@ else
    require 'SSIMCriterion'
    require 'InplaceClip01'
    require 'L1Criterion'
+   require 'ShakeShakeTable'
    return w2nn
 end