Since I completely removed CUDA from my system this shouldn’t be the problem, but I think somehow it may be related. I searched a bit, and found this pytorch thread. I restarted, removed all irrelevant environment variables which may have caused issues (LD_LIBRARY_PATH), removed conda, reinstalled, tried cuda 9.2, but nothing works. Have an NVIDIA GPU and installed a driver from I get the following error message Traceback (most recent call last):įile "/home/rana/anaconda3/envs/p圓6torch12cu10/lib/python3.6/site-packages/torch/cuda/_init_.py", line 178, in _lazy_initįile "/home/rana/anaconda3/envs/p圓6torch12cu10/lib/python3.6/site-packages/torch/cuda/_init_.py", line 99, in _check_driverįound no NVIDIA driver on your system. When I run: print(_count()) # -> 0īut using cuda fails. You might also want to find other CUDA verion on the Legacy Releases. Note that the latest CUDA version supported by MXNet is 9.2. Since I wanted conda to manage my CUDA version, I installed the cudatoolkit through conda env (python 3.6):Ĭonda install pytorch torchvision cudatoolkit=10.0 -c pytorchĪgain, everything installs perfectly. If you already had CUDA, then installed VS2017, you should reinstall CUDA now so that you get the CUDA toolkit components for VS2017 integration. The output of cat /proc/driver/nvidia/version NVRM version: NVIDIA UNIX x86_64 Kernel Module 410.78 Sat Nov 10 22:09: Once the extraction process finishes, the wizard will start. The progress bar appears to show the files are being saved to the selected location. Select a location on your hard drive and click OK. uest-channel-token=13099850080781834209 110MiB | Run the executable file you downloaded from NVIDIA’s website. | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. | NVIDIA-SMI 410.78 Driver Version: 410.78 CUDA Version: N/A | The output of nvidia-smi: Fri Aug 23 22:29:48 2019 Then I updated my Nvidia drivers to 4.10 via PPA (Ubuntu 16.04): sudo add-apt-repository ppa:graphics-drivers/ppaĮverything worked smoothly. I removed / purge all CUDA through: sudo apt-get -purge remove cudaĭpkg -list |grep "^rc" | cut -d " " -f 3 | xargs sudo dpkg -purge Previously, I was using Pytorch with CUDA 8.0, and wanted to upgrade. However, I am not able to use cuda in pytorch (even though it installed successfully). I have successfully installed NVIDIA driver & cudatoolkit via conda.
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