torch/rnn won't use CUDA - torch

Question

I'm trying to use the torch/rnn toolkit to run RNNs on my nVidia graphics card. I've got an Ubuntu 16.04 VM with the nVidia driver, CUDA toolkit, Torch, and cuDNN working. I can run the mnistCUDNN example and nvidia-smi shows it using the graphics card. In Torch, I can require('cunn'); and it loads happily.
BUT when I dofile('./rnn/examples/recurrent-visual-attention.lua' ); inside Torch, I get
{
batchsize : 20
cuda : false
cutoff : -1
dataset : "Mnist"
device : 1
earlystop : 200
glimpseDepth : 1
glimpseHiddenSize : 128
glimpsePatchSize : 8
glimpseScale : 2
hiddenSize : 256
id : "ptb:brain:1508585440:1"
imageHiddenSize : 256
locatorHiddenSize : 128
locatorStd : 0.11
lstm : false
maxepoch : 2000
maxnormout : -1
minlr : 1e-05
momentum : 0.9
noTest : false
overwrite : false
progress : false
rewardScale : 1
saturate : 800
savepath : "/home/tom/save/rmva"
seqlen : 7
silent : false
startlr : 0.01
stochastic : false
trainsize : -1
transfer : "ReLU"
uniform : 0.1
unitPixels : 13
validsize : -1
version : 13
}
and since cuda:false, it runs using just the CPU.
Any ideas how to work out what I've missed? Thanks.

Answer 1

I'm an idiot. When I finally worked up the courage to read the source code, I discovered that it doesn't automatically try to use CUDA. There's a -cuda flag to ask it to.
In my defence, the examples are undocumented...