How to run with cpu? Actually CUDA is needed anyway? about ganomaly

[zszzlmt]

it seems that even though i added the option "--gpu_ids -1", the self.device still have value cuda:0

self.device = torch.device("cuda:0" if self.opt.gpu_ids!=-1 else "cpu")

why
qaq

[zszzlmt]

And I skipped this line, force self.device to be "cpu", but the problem is still there

THCudaCheck FAIL file=/opt/conda/conda-bld/pytorch_1535491974311/work/aten/src/THC/THCGeneral.cpp line=74 error=35 : CUDA driver version is insufficient for CUDA runtime version
Traceback (most recent call last):
File "/home/foo/ganomaly/train.py", line 43, in
model.train()
File "/home/foo/ganomaly/lib/model.py", line 285, in train
self.train_epoch()
File "/home/foo/ganomaly/lib/model.py", line 255, in train_epoch
self.optimize()
File "/home/foo/ganomaly/lib/model.py", line 187, in optimize
self.update_netd()
File "/home/foo/ganomaly/lib/model.py", line 146, in update_netd
self.fake, self.latent_i, self.latent_o = self.netg(self.input)
File "/home/foo/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/foo/ganomaly/lib/networks.py", line 173, in forward
latent_i = self.encoder1(x)
File "/home/foo/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/foo/ganomaly/lib/networks.py", line 72, in forward
if isinstance(input.data, torch.cuda.FloatTensor) and self.ngpu > 1:
RuntimeError: cuda runtime error (35) : CUDA driver version is insufficient for CUDA runtime version at /opt/conda/conda-bld/pytorch_1535491974311/work/aten/src/THC/THCGeneral.cpp:74

[samet-akcay]

I've updated the repo now. You could run the code on CPU via the following command: python train.py --device cpu. However, this is not recommended since training on CPU takes much more time than training on GPU.