adding SoftMax and SpatialSoftMax bindings

1 files changed, 43 insertions, 6 deletions

diff --git a/test/test.lua b/test/test.lua
index 78a4fdc..6965219 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -130,11 +130,11 @@ function cudnntest.ReLU()
    local input = torch.randn(bs,from,inj,ini):cuda()
    local gradOutput = torch.randn(bs,from,outj,outi):cuda()
 
-   local sconv = nn.ReLU(ki,kj,si,sj):cuda()
+   local sconv = nn.ReLU():cuda()
    local groundtruth = sconv:forward(input)
    local groundgrad = sconv:backward(input, gradOutput)
    cutorch.synchronize()
-   local gconv = cudnn.ReLU(ki,kj,si,sj):cuda()
+   local gconv = cudnn.ReLU():cuda()
    local rescuda = gconv:forward(input)
 
    -- serialize and deserialize
@@ -164,11 +164,11 @@ function cudnntest.Tanh()
    local input = torch.randn(bs,from,inj,ini):cuda()
    local gradOutput = torch.randn(bs,from,outj,outi):cuda()
 
-   local sconv = nn.Tanh(ki,kj,si,sj):cuda()
+   local sconv = nn.Tanh():cuda()
    local groundtruth = sconv:forward(input)
    local groundgrad = sconv:backward(input, gradOutput)
    cutorch.synchronize()
-   local gconv = cudnn.Tanh(ki,kj,si,sj):cuda()
+   local gconv = cudnn.Tanh():cuda()
    local rescuda = gconv:forward(input)
 
    -- serialize and deserialize
@@ -198,11 +198,11 @@ function cudnntest.Sigmoid()
    local input = torch.randn(bs,from,inj,ini):cuda()
    local gradOutput = torch.randn(bs,from,outj,outi):cuda()
 
-   local sconv = nn.Tanh(ki,kj,si,sj):cuda()
+   local sconv = nn.Sigmoid():cuda()
    local groundtruth = sconv:forward(input)
    local groundgrad = sconv:backward(input, gradOutput)
    cutorch.synchronize()
-   local gconv = cudnn.Tanh(ki,kj,si,sj):cuda()
+   local gconv = cudnn.Sigmoid():cuda()
    local rescuda = gconv:forward(input)
 
    -- serialize and deserialize
@@ -218,6 +218,43 @@ function cudnntest.Sigmoid()
    mytester:assertlt(error:abs():max(), precision_backward, 'error on state (backward) ')
 end
 
+function cudnntest.SoftMax()
+   local bs = math.random(1,32)
+   local from = math.random(1,32)
+   local ki = math.random(2,4)
+   local kj = math.random(2,4)
+   local si = ki
+   local sj = kj
+   local outi = math.random(1,64)
+   local outj = math.random(1,64)
+   local ini = outi
+   local inj = outj
+   local input = torch.randn(bs,from,inj,ini):cuda()
+   local gradOutput = torch.randn(bs,from,outj,outi):cuda()
+
+   local sconv = nn.SoftMax():cuda()
+   local groundtruth = sconv:forward(input:view(bs,-1))
+   local groundgrad = sconv:backward(input, gradOutput)
+   cutorch.synchronize()
+   local gconv = cudnn.SoftMax():cuda()
+   local rescuda = gconv:forward(input)
+
+   -- serialize and deserialize
+   torch.save('modelTemp.t7', gconv)
+   gconv = torch.load('modelTemp.t7')
+
+   local rescuda = gconv:forward(input)
+   local resgrad = gconv:backward(input, gradOutput)
+   cutorch.synchronize()
+   local error = rescuda:float() - groundtruth:float()
+   mytester:assertlt(error:abs():max(),
+                     precision_forward, 'error on state (forward) ')
+   error = resgrad:float() - groundgrad:float()
+   mytester:assertlt(error:abs():max(),
+                     precision_backward, 'error on state (backward) ')
+end
+
+
 
 torch.setdefaulttensortype('torch.FloatTensor')
 math.randomseed(os.time())