how to run the cpu version

[gaopeng-eugene]

/usr/local/lib/python3.6/site-packages/IPython/core/ultratb.py(1268)call()
-> self.handler((etype, evalue, etb))
(Pdb)

---

AssertionError Traceback (most recent call last)
/Users/gaopeng/Desktop/tensorflow/project/optnet/denoising/main.py in ()
229
230 if name=='main':
--> 231 main()
global main = <function main at 0x114ba7510>

/Users/gaopeng/Desktop/tensorflow/project/optnet/denoising/main.py in main()
109 elif args.model == 'optnet':
110 if args.learnD:
--> 111 model = models.OptNet_LearnD(nFeatures, args)
model = undefined
global models.OptNet_LearnD = <class 'models.OptNet_LearnD'>
nFeatures = 100
args = Namespace(Dpenalty=0.01, batchSz=150, cuda=False, eps=0.0001, learnD=True, model='optnet', nEpoch=50, no_cuda=False, save='work/optnet.eps=0.0001.learnD.0.01', testBatchSz=100, testPct=0.1, tvInit=False)
112 else:
113 model = models.OptNet(nFeatures, args)

/Users/gaopeng/Desktop/tensorflow/project/optnet/denoising/models.py in init(self=OptNet_LearnD (
), nFeatures=100, args=Namespace(Dpenalty=0.01, batchSz=150, cuda=False....01', testBatchSz=100, testPct=0.1, tvInit=False))
113
114 # self.fc1 = nn.Linear(nFeatures, nHidden)
--> 115 self.M = Variable(torch.tril(torch.ones(nHidden, nHidden)).cuda())
self.M = undefined
global Variable = <class 'torch.autograd.variable.Variable'>
global torch.tril =
global torch.ones =
nHidden = 199
nHidden.cuda = undefined
116
117 Q = 1e-8*torch.eye(nHidden)

/usr/local/lib/python3.6/site-packages/torch/utils.py in cuda(self=
1 0 0 ... 0 0 0
1... 1 1
[torch.FloatTensor of size 199x199]
, device=-1, async=False)
63 else:
64 new_type = getattr(torch.cuda, self.class.name)
---> 65 return new_type(self.size()).copy(self, async)
new_type = <class 'torch.cuda.FloatTensor'>
self.size.copy = undefined
self =
1 0 0 ... 0 0 0
1 1 0 ... 0 0 0
1 1 1 ... 0 0 0
... ⋱ ...
1 1 1 ... 1 0 0
1 1 1 ... 1 1 0
1 1 1 ... 1 1 1
[torch.FloatTensor of size 199x199]

    async = False
 66 
 67 

/usr/local/lib/python3.6/site-packages/torch/cuda/init.py in new(cls=<class 'torch.cuda.FloatTensor'>, *args=(torch.Size([199, 199]),), **kwargs={})
275
276 def new(cls, *args, **kwargs):
--> 277 _lazy_init()
global _lazy_init = <function _lazy_init at 0x110ab5378>
278 # We need this method only for lazy init, so we can remove it
279 del _CudaBase.new

/usr/local/lib/python3.6/site-packages/torch/cuda/init.py in _lazy_init()
87 raise RuntimeError(
88 "Cannot re-initialize CUDA in forked subprocess. " + msg)
---> 89 _check_driver()
global _check_driver = <function _check_driver at 0x110ab52f0>
90 assert torch._C._cuda_init()
91 assert torch._C._cuda_sparse_init()

/usr/local/lib/python3.6/site-packages/torch/cuda/init.py in _check_driver()
54 def _check_driver():
55 if not hasattr(torch._C, '_cuda_isDriverSufficient'):
---> 56 raise AssertionError("Torch not compiled with CUDA enabled")
global AssertionError = undefined
57 if not torch._C._cuda_isDriverSufficient():
58 if torch._C._cuda_getDriverVersion() == 0:

AssertionError: Torch not compiled with CUDA enabled

/usr/local/lib/python3.6/site-packages/IPython/core/ultratb.py(1269)call()
-> try:

[bamos]

Hi, it's great to hear you've been looking into our OptNet project and that you are exploring the code. I think I forgot to add some checks around some of the cuda() calls, like the one in the trace you sent. Please send in a PR if you add them!

-Brandon.