dag:connect(c, d)
dag:connect(c, e)
+dag:setLabel(a, 'first module')
+
dag:setInput(a)
dag:setOutput({ d, e })
torch.save('/tmp/test.t7', model)
local otherModel = torch.load('/tmp/test.t7')
print('Gradient estimate error ' .. checkGrad(otherModel, criterion, input, output, epsilon))
+
+dag:print()