Move make contiguous code from lua to C.

Exceptions are:
1) SparseLinear
requires additional parameters to be passed in (e.g. nbatches),
so it's not clear it's worth moving to C since it won't really simplify the binding
code logic.

2) BatchNormalization
requires "makeBatch", which isn't a trivial translation to C.

3) LookupTable
requires "view" in C, which is already a TODO

4) SpatialUpSamplingBilinear
requires "view" in C, which is already TODO

1 files changed, 0 insertions, 19 deletions

diff --git a/VolumetricFullConvolution.lua b/VolumetricFullConvolution.lua
index 3c86a14..58eaa1d 100644
--- a/VolumetricFullConvolution.lua
+++ b/VolumetricFullConvolution.lua
@@ -57,22 +57,6 @@ function VolumetricFullConvolution:reset(stdv)
    self.bias:uniform(-stdv, stdv)
 end
 
-local function makeContiguous(self, input, gradOutput)
-   if not input:isContiguous() then
-      self._input = self._input or input.new()
-      self._input:resizeAs(input):copy(input)
-      input = self._input
-   end
-   if gradOutput then
-      if not gradOutput:isContiguous() then
-         self._gradOutput = self._gradOutput or gradOutput.new()
-         self._gradOutput:resizeAs(gradOutput):copy(gradOutput)
-         gradOutput = self._gradOutput
-     end
-   end
-   return input, gradOutput
-end
-
 local function calculateAdj(targetSize, ker, pad, stride)
   return (targetSize + 2 * pad - ker) % stride
 end
@@ -113,7 +97,6 @@ function VolumetricFullConvolution:updateOutput(input)
     adjH = calculateAdj(tH, self.kH, self.padH, self.dH)
   end
 
-   inputTensor = makeContiguous(self, inputTensor)
    inputTensor.THNN.VolumetricFullConvolution_updateOutput(
       inputTensor:cdata(),
       self.output:cdata(),
@@ -153,7 +136,6 @@ function VolumetricFullConvolution:updateGradInput(input, gradOutput)
       end
     end
 
-   inputTensor, gradOutput = makeContiguous(self, inputTensor, gradOutput)
    inputTensor.THNN.VolumetricFullConvolution_updateGradInput(
       inputTensor:cdata(),
       gradOutput:cdata(),
@@ -199,7 +181,6 @@ function VolumetricFullConvolution:accGradParameters(input, gradOutput, scale)
     adjH = calculateAdj(tH, self.kH, self.padH, self.dH)
   end
 
-   inputTensor, gradOutput = makeContiguous(self, inputTensor, gradOutput)
    inputTensor.THNN.VolumetricFullConvolution_accGradParameters(
       inputTensor:cdata(),
       gradOutput:cdata(),