--- a
+++ b/util/ReverseSequence.lua
@@ -0,0 +1,55 @@
+------------------------------------------------------------------------
+-- Adapted from github.com/jcjohnson/torch-rnn/pull/66/commits/5e30c1d54dc9ed1d152e4a55e9c438775f623ef7
+
+--[[ ReverseSequence ]] --
+-- Reverses a sequence on a given dimension.
+-- Example: Given a tensor of torch.Tensor({{1,2,3,4,5}, {6,7,8,9,10})
+-- nn.ReverseSequence(1):forward(tensor) would give: torch.Tensor({{6,7,8,9,10},{1,2,3,4,5}})
+------------------------------------------------------------------------
+local ReverseSequence, parent = torch.class("nn.ReverseSequence", "nn.Module")
+
+function ReverseSequence:__init(dim,gpu)
+    parent.__init(self)
+    self.output = torch.Tensor()
+    self.gradInput = torch.Tensor()
+    self.outputIndices = torch.LongTensor()
+    self.gradIndices = torch.LongTensor()
+    self.typ = 'torch.CudaTensor'
+    if gpu and (gpu < 1) then
+      self.typ = 'torch.LongTensor'
+    end
+end
+
+function ReverseSequence:reverseOutput(input)
+  self.output:resizeAs(input)
+  self.outputIndices:resize(input:size())
+  local T = input:size(1)
+  for x = 1, T do
+      self.outputIndices:narrow(1, x, 1):fill(T - x + 1)
+  end
+  self.output:gather(input, 1, self.outputIndices:type(self.typ))
+end
+
+function ReverseSequence:updateOutput(input)
+  input = input:transpose(1, 2)
+  self:reverseOutput(input)
+  self.output = self.output:transpose(1, 2)
+  return self.output
+end
+
+function ReverseSequence:reverseGradOutput(gradOutput)
+    self.gradInput:resizeAs(gradOutput)
+    self.gradIndices:resize(gradOutput:size())
+    local T = gradOutput:size(1)
+    for x = 1, T do
+        self.gradIndices:narrow(1, x, 1):fill(T - x + 1)
+    end
+    self.gradInput:gather(gradOutput, 1, self.gradIndices:type(self.typ))
+end
+
+function ReverseSequence:updateGradInput(inputTable, gradOutput)
+  gradOutput = gradOutput:transpose(1, 2)
+  self:reverseGradOutput(gradOutput)
+  self.gradInput = self.gradInput:transpose(1, 2)
+  return self.gradInput
+end