can’t connect to the NVIDIA driver after restarting the server. At this point, TensorFlow is still running, but only on the CPU. When installing the GPU version of TensorFlow, it also shows that it is installed.
first enter at the terminal nvidia-smi
appears nvidia-smi has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.
1 input in the terminal nvcc-v
driver is also
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Tue_Jan_10_13:22:03_CST_2017
Cuda compilation tools, release 8.0, V8.0.61
solution takes only two steps, without restarting
step1:sudo apt-get install dkms
step2: sudo dkms install -m nvidia -v 410.73
enter nvidia-smi
again, return to normal.
where 410.73 in step2 is the version number of NVIDIA. When you do not know the version number, enter the directory /usr/ SRC, you can see that there is a folder of NVIDIA inside, the suffix is its version number
cd /usr/src
another: how to check whether TensorFlow is gpu version or CPU version
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
https://blog.csdn.net/hangzuxi8764/article/details/86572093 p>
Read More:
- Tensorflow 2.1.0 error resolution: failed call to cuinit: CUDA_ ERROR_ NO_ DEVICE: no CUDA-capable device is detected
- Tensorflow error in Windows: failed call to cuinit: CUDA_ ERROR_ UNKNOWN
- failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error
- linux/tensorflow: failed call to cuDevicePrimaryCtxRetain: CUDA_ERROR_INVALID_DEVICE
- RuntimeError: cuda runtime error (100) : no CUDA-capable device is detected at /opt/conda/conda-bld/
- [MMCV]RuntimeError: CUDA error: no kernel image is available for execution on the device
- The apple mobile device service failed to start. Error 1053 is resolved
- FCOS No CUDA runtime is found, using CUDA_HOME=’/usr/local/cuda-10.0′
- CUDA Error: no kernel image is available for execution on device
- Error: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
- Ubuntu cannot access USB device, failed to create a proxy device for the USB device
- CUDA error: device-side assert triggered
- Failed to add /run/systemd/ask-password to directory watch: No space left on device?
- device no response, device descriptor read/64, error -71
- pycuda._driver.Error:cuInit failed:unknown error
- Failed to mount / cache (no such device)
- /sbin/mount.vboxsf: mounting failed with the error: No such device
- docker:Failed to add /run/systemd/ask-password to directory watch: No space left on device
- RuntimeError: CUDA error: device-side assert triggered
- QInotifyFileSystemWatcherEngine::addPaths: inotify_add_Watch failed: there is no space on the device