X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=dagnn.git;a=blobdiff_plain;f=test-dagnn.lua;h=b390a29a5b7b412c6ff019e44f51ef5ef5e2a6de;hp=2db93c67adc784e8afd497279486eb46873b7aee;hb=d88688ee3e40d6087c8b0b271d257730c7ac76ca;hpb=a7a25093ee35439427cc2a085d63d0d22122e93c

diff --git a/test-dagnn.lua b/test-dagnn.lua
index 2db93c6..b390a29 100755
--- a/test-dagnn.lua
+++ b/test-dagnn.lua
@@ -104,9 +104,12 @@ dag:setLabel(a, 'first module')
 dag:setInput(a)
 dag:setOutput({ d, e })
 
--- Check the output of the dot file
-print('Writing /tmp/graph.dot')
-dag:saveDot('/tmp/graph.dot')
+-- Check the output of the dot file. Generate a pdf with:
+--
+-- dot ./graph.dot -Lg -T pdf -o ./graph.pdf
+--
+print('Writing ./graph.dot')
+dag:saveDot('./graph.dot')
 
 -- Let's make a model where the dag is inside another nn.Container.
 model = nn.Sequential()
@@ -133,8 +136,8 @@ print('Gradient estimate error ' .. checkGrad(model, criterion, input, output, e
 
 -- Check that we can save and reload the model
 model:clearState()
-torch.save('/tmp/test.t7', model)
-local otherModel = torch.load('/tmp/test.t7')
+torch.save('./test.t7', model)
+local otherModel = torch.load('./test.t7')
 print('Gradient estimate error ' .. checkGrad(otherModel, criterion, input, output, epsilon))
 
 dag:print()