Comments (3)
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
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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
from ganomaly.
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.
from ganomaly.
Related Issues (20)
- how can i balance the model HOT 7
- how can i see the result of test?? HOT 1
- How to distinguish a mnist_pic is normal or anomaly? HOT 17
- Sudden increase of err_d HOT 1
- Changes for Windows10
- Some qutestions about testing
- can it display where is the anomaly when inference? HOT 1
- what is the difference between fixed_fakes_*.png and fakes.png
- Is the testing function missing self.netg.eval? HOT 5
- AttributeError: module 'torch._C' has no attribute '_cuda_setDevice' HOT 4
- What's the performance of the model in terms of custom dataset?
- Can this code be used on sequence data? HOT 1
- How to use ganomaly neural network for single-channel data training
- Program stucks when the input image size is 224x224 HOT 2
- Experiment(To replicate the results in the paper for MNIST and CIFAR10 datasets)
- Testing
- Possible mode collapse HOT 1
- Test problem HOT 2
- Missing net.eval() in the testing code HOT 1
- ROC is changed every time
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