1 files changed, 36 insertions, 0 deletions
diff --git a/contrib/lua-torch/nn/Constant.lua b/contrib/lua-torch/nn/Constant.lua
new file mode 100644
index 000000000..07773feb2
--- /dev/null
+++ b/contrib/lua-torch/nn/Constant.lua
@@ -0,0 +1,36 @@
+------------------------------------------------------------------------
+--[[ Constant ]]--
+-- Outputs a constant value given an input.
+-- If nInputDim is specified, uses the input to determine the size of
+-- the batch. The value is then replicated over the batch.
+-- You can use this with nn.ConcatTable() to append constant inputs to
+-- an input : nn.ConcatTable():add(nn.Constant(v)):add(nn.Identity()) .
+------------------------------------------------------------------------
+local Constant, parent = torch.class("nn.Constant", "nn.Module")
+
+function Constant:__init(value, nInputDim)
+   self.value = value
+   if torch.type(self.value) == 'number' then
+      self.value = torch.Tensor{self.value}
+   end
+   assert(torch.isTensor(self.value), "Expecting number or tensor at arg 1")
+   self.nInputDim = nInputDim
+   parent.__init(self)
+end
+
+function Constant:updateOutput(input)
+   if self.nInputDim and input:dim() > self.nInputDim then
+      local vsize = self.value:size():totable()
+      self.output:resize(input:size(1), table.unpack(vsize))
+      local value = self.value:view(1, table.unpack(vsize))
+      self.output:copy(value:expand(self.output:size()))
+   else
+      self.output:resize(self.value:size()):copy(self.value)
+   end
+   return self.output
+end
+
+function Constant:updateGradInput(input, gradOutput)
+   self.gradInput:resizeAs(input):zero()
+   return self.gradInput
+end