DepthConcat

1 files changed, 32 insertions, 4 deletions

diff --git a/test/test.lua b/test/test.lua
index 593e659..b035928 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -1,8 +1,6 @@
-require 'torch'
-
 -- you can easily test specific units like this: 
--- luajit -lnn -e "nn.test{'LookupTable'}"
--- luajit -lnn -e "nn.test{'LookupTable', 'Add'}"
+-- th -lnn -e "nn.test{'LookupTable'}"
+-- th -lnn -e "nn.test{'LookupTable', 'Add'}"
 
 local mytester = torch.Tester()
 local jac
@@ -2311,6 +2309,36 @@ function nntest.L1Penalty()
    -- during BPROP is not included in the FPROP output)
 end
 
+function nntest.DepthConcat()
+   local outputSize = torch.IntTensor{5,6,7,8}
+   local input = torch.randn(2,3,12,12)
+   local gradOutput = torch.randn(2, outputSize:sum(), 12, 12)
+   local concat = nn.DepthConcat(2)
+   concat:add(nn.SpatialConvolutionMM(3, outputSize[1], 1, 1, 1, 1)) --> 2, 5, 12, 12
+   concat:add(nn.SpatialConvolutionMM(3, outputSize[2], 3, 3, 1, 1)) --> 2, 6, 10, 10
+   concat:add(nn.SpatialConvolutionMM(3, outputSize[3], 4, 4, 1, 1)) --> 2, 7, 9, 9
+   concat:add(nn.SpatialConvolutionMM(3, outputSize[4], 5, 5, 1, 1)) --> 2, 8, 8, 8
+   concat:zeroGradParameters()
+   -- forward/backward
+   local outputConcat = concat:forward(input)
+   local gradInputConcat = concat:backward(input, gradOutput)
+   -- the spatial dims are the largest, the nFilters is the sum
+   local output = torch.Tensor(2, outputSize:sum(), 12, 12):zero() -- zero for padding
+   local narrows = { {{},{1,5},{},{}}, {{},{6,11},{2,11},{2,11}}, {{},{12,18},{2,10},{2,10}}, {{},{19,26},{3,10},{3,10}} }
+   local gradInput = input:clone():zero()
+   local gradWeights = {}
+   for i=1,4 do
+      local conv = concat:get(i)
+      local gradWeight = conv.gradWeight:clone()
+      conv:zeroGradParameters()
+      output[narrows[i]]:copy(conv:forward(input))
+      gradInput:add(conv:backward(input, gradOutput[narrows[i]]))
+      mytester:assertTensorEq(gradWeight, conv.gradWeight, 0.000001, "Error in SpatialConcat:accGradParameters for conv "..i)
+   end
+   mytester:assertTensorEq(output, outputConcat, 0.000001, "Error in SpatialConcat:updateOutput")
+   mytester:assertTensorEq(gradInput, gradInputConcat, 0.000001, "Error in SpatialConcat:updateGradInput")
+end
+
 mytester:add(nntest)
 
 if not nn then