Make it easier to check with cuda.

diff --git a/test-dagnn.lua b/test-dagnn.lua
index e34ee02..cec37d2 100755 (executable)
--- a/test-dagnn.lua
+++ b/test-dagnn.lua
@@ -21,6 +21,9 @@
 
 require 'torch'
 require 'nn'
+
+-- require 'cunn'
+
 require 'dagnn'
 
 torch.setdefaulttensortype('torch.DoubleTensor')
@@ -57,7 +60,7 @@ function checkGrad(model, criterion, input, target, epsilon)
       local num = (loss1 - loss0) / (2 * epsilon)
 
       if num ~= ana then
-         err = math.max(err, math.abs(num - ana) / math.abs(num))
+         err = math.max(err, math.abs(num - ana) / math.max(epsilon, math.abs(num)))
       end
    end
 
@@ -111,10 +114,13 @@ model = nn.Sequential()
 
 criterion = nn.MSECriterion()
 
--- model:cuda()
--- criterion:cuda()
--- torch.setdefaulttensortype('torch.CudaTensor')
--- epsilon = 1e-4
+if cunn then
+   print("Using CUDA")
+   model:cuda()
+   criterion:cuda()
+   torch.setdefaulttensortype('torch.CudaTensor')
+   epsilon = 1e-3
+end
 
 local input = torch.Tensor(30, 50):uniform()
 local output = model:updateOutput(input):clone()