注意：有很多类似的问题，但是针对不同版本的 ubuntu 和有些不同的特定库。我一直无法弄清楚符号链接、其他环境变量的组合，例如LD_LIBRARY_PATH会工作
这是我的nvidia配置
$ nvidia-smi
Tue Apr 6 11:35:54 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.80.02 Driver Version: 450.80.02 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce RTX 2070 Off | 00000000:01:00.0 Off | N/A |
| 18% 25C P8 9W / 175W | 25MiB / 7982MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 1081 G /usr/lib/xorg/Xorg 20MiB |
| 0 N/A N/A 1465 G /usr/bin/gnome-shell 3MiB |
+-----------------------------------------------------------------------------+
运行 TF 程序时发生以下情况：
2021-04-06 14:35:01.589906: W tensorflow/stream_executor/platform/default/dso_loader.cc:60]
Could not load dynamic library 'libcudnn.so.8'; dlerror:
libcudnn.so.8: cannot open shared object file: No such file or directory
2021-04-06 14:35:01.589914: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757]
Cannot dlopen some GPU libraries. Please make sure the missing
libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at
https://www.tensorflow.org/install/gpu for how to download
and setup the required libraries for your platform.
Skipping registering GPU devices...
有人见过这种特殊的组合吗？你是如何解决它的？
以下是尝试的附加修复之一，但没有任何更改：
conda install cudatoolkit=11.0
所以我有同样的问题。正如评论所说，这是因为你需要安装CUDNN。为此，有一个指南here https://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html.
但据我所知，您的发行版（Ubuntu 20.04）我已经可以给您命令行了：
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
export last_public_key=3bf863cc # SEE NOTE BELOW
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/${last_public_key}.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /"
sudo apt-get update
sudo apt-get install libcudnn8
sudo apt-get install libcudnn8-dev
where ${last_public_key}是最后一个公钥（文件为.pub扩展名）发布于https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/。 （2023 年 3 月 8 日编辑这篇文章时，它是3bf863cc).
如果你想安装特定版本，最后 2 个命令将替换为
sudo apt-get install libcudnn8=${cudnn_version}-1+${cuda_version}
sudo apt-get install libcudnn8-dev=${cudnn_version}-1+${cuda_version}
where
${cudnn_version}例如8.2.4.* and ${cuda_version}例如cuda11.0（据我所知，命令上有 11.0nvidia-smi，虽然我没有测试过它，因为我的是 11.4，但我想它应该可以正常工作）
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