Parallel optimization. ParallelTable inherits Container. unit tests

1 files changed, 34 insertions, 0 deletions

diff --git a/test.lua b/test.lua
index 3cf6a58..eb2f3ea 100644
--- a/test.lua
+++ b/test.lua
@@ -2452,6 +2452,40 @@ function nntest.SpatialUpSamplingNearest()
   end
 end
 
+function nntest.Parallel()
+   local input = torch.randn(3, 4, 5)
+   local m = nn.Parallel(1,3)
+   m:add(nn.View(4,5,1))
+   m:add(nn.View(4,5,1))
+   m:add(nn.View(4,5,1))
+   
+   local output = m:forward(input)
+   local output2 = input:transpose(1,3):transpose(1,2)
+   mytester:assertTensorEq(output2, output, 0.000001, 'Parallel forward err')
+   
+   local gradInput = m:backward(input, output2)
+   mytester:assertTensorEq(gradInput, input, 0.000001, 'Parallel backward err')
+end
+
+function nntest.ParallelTable()
+   local input = torch.randn(3, 4, 5)
+   local p = nn.ParallelTable()
+   p:add(nn.View(4,5,1))
+   p:add(nn.View(4,5,1))
+   p:add(nn.View(4,5,1))
+   m = nn.Sequential()
+   m:add(nn.SplitTable(1))
+   m:add(p)
+   m:add(nn.JoinTable(3))
+   
+   local output = m:forward(input)
+   local output2 = input:transpose(1,3):transpose(1,2)
+   mytester:assertTensorEq(output2, output, 0.000001, 'ParallelTable forward err')
+   
+   local gradInput = m:backward(input, output2)
+   mytester:assertTensorEq(gradInput, input, 0.000001, 'ParallelTable backward err')
+end
+
 function nntest.ConcatTable()
    -- Test tensor input
    local input = torch.rand(5, 5, 5)