Reversed the dimensions of the output of SpatialMatching, and its arguments

Conflicts:
	SpatialMatching.lua

1 files changed, 7 insertions, 9 deletions

diff --git a/SpatialMatching.lua b/SpatialMatching.lua
index f74ed5e..17fbe0f 100644
--- a/SpatialMatching.lua
+++ b/SpatialMatching.lua
@@ -1,34 +1,32 @@
 local SpatialMatching, parent = torch.class('nn.SpatialMatching', 'nn.Module')
 
-function SpatialMatching:__init(maxw, maxh, full_output)
+function SpatialMatching:__init(maxh, maxw, full_output)
    -- If full_output is false, output is computed on elements of the first input
    -- for which all the possible corresponding elements exist in the second input
    -- In addition, if full_output is set to false, the pixel (1,1) of the first input
    -- is supposed to correspond to the pixel (maxh/2, maxw/2) of the second one
-   -- If align_inputs is set, input[2] is assumed to be large enough
-   -- (that is input[1]:size(1) <= inputs[1]:size(1) - maxh + 1, same for w)
-   -- TODO full_output == true and align_inputs == false is probably useless
    parent.__init(self)
    self.maxw = maxw or 11
    self.maxh = maxh or 11
    if full_output == nil then
       full_output = false
    end
-   if full_output then self.full_output = 1 else self.full_output = 0 end
+   self.full_output = full_output
+   self.gradInput1 = torch.Tensor()
+   self.gradInput2 = torch.Tensor()
 end
 
 function SpatialMatching:updateOutput(input)
    -- input is a table of 2 inputs, each one being KxHxW
    -- if not full_output, the 1st one is KxH1xW1 where H1 <= H-maxh+1, W1 <= W-maxw+1
-   self.output:resize(input[1]:size(2), input[1]:size(3), self.maxh, self.maxw)
+   self.output:resize(self.maxh, self.maxw, input[1]:size(2), input[1]:size(3))
    input[1].nn.SpatialMatching_updateOutput(self, input[1], input[2])
    return self.output
 end
 
 function SpatialMatching:updateGradInput(input, gradOutput)
-   -- TODO this is probably the wrong way
-   self.gradInput1 = torch.Tensor(input[1]:size()):zero()
-   self.gradInput2 = torch.Tensor(input[2]:size()):zero()
+   self.gradInput1:resize(input[1]:size()):zero()
+   self.gradInput2:resize(input[2]:size()):zero()
    input[1].nn.SpatialMatching_updateGradInput(self, input[1], input[2], gradOutput)
    self.gradInput = {self.gradInput1, self.gradInput2}
    return self.gradInput