您必须下载/更新Cuda
如果您正在寻找CUDA工具包10.2下载使用此链接：https://developer.nvidia.com/cuda-10.2-download-archive
然后激活虚拟环境并设置LD_LIBRARY_PATH，例如：无法加载动态库'libcudart.so.10.0（在Ubuntu 18.04上）

**如果您安装了ubuntu 18.04，请运行这些命令。**或按照here的说明操作

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin

sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600

sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub

sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"

sudo apt-get update

sudo apt-get -y install cuda

这对我很有效：
sudo apt-get安装库10.1

确保您安装了兼容GPU/CPU版本的tensorflow。我在Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz 2.59 GHz计算机上的Pipenv虚拟环境中安装tensorflow。我使用pip install tensorflow时收到了相同的消息。以下是执行笔记本单元或包含import tensorflow as tf的代码后的输出消息。

2023-02-27 14:53:16.590721: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-27 14:53:16.957000: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-27 14:53:16.957019: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-27 14:53:18.213523: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-27 14:53:18.213591: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-27 14:53:18.213597: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.

当我将安装命令更改为pip install tensorflow-cpu时，错误消失了。这是执行相同的笔记本单元格或包含import tensorflow as tf的代码后的新输出消息。

023-02-28 10:01:35.003241: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

pip install tensorflow-gpu可以解决这个问题。请参见here了解有关tensorflow-gpu的详细信息。但是，请仔细检查这个官方pip库，似乎从2022年12月起，建议安装tensorflow而不是tensorflow-gpu。

在Ubuntu 20.04上，您可以简单地安装NVIDIAs cuda toolkitcuda：

sudo apt-get update
sudo apt install nvidia-cuda-toolkit

还有install advices for Windows。
该软件包大约是1GB，它花了一段时间来安装...几分钟后，您需要export PATH变量，以便可以找到它：
1.查找共享对象

sudo find / -name 'libcudart.so*'

/usr/lib/x86_64-linux-gnu/libcudart.so.10.1
/usr/lib/x86_64-linux-gnu/libcudart.so

1.将文件夹添加到path，以便python能够找到它

export PATH=/usr/lib/x86_64-linux-gnu${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

1.权限

sudo chmod a+r /usr/lib/x86_64-linux-gnu/libcuda*

Helped me

这通常发生在使用不兼容的CUDA版本运行Tensorflow时。看起来以前有人问过这个问题（无法评论）。请参考this问题。

今天我遇到了这个问题。我去了CUDA toolkit website，选择了选项，然后显示了一些如下的说明：

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
wget https://developer.download.nvidia.com/compute/cuda/11.6.2/local_installers/cuda-repo-ubuntu2004-11-6-local_11.6.2-510.47.03-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2004-11-6-local_11.6.2-510.47.03-1_amd64.deb
sudo apt-key add /var/cuda-repo-ubuntu2004-11-6-local/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda         # I have broken packages, so could not invoke this command

因此，说明将根据您的规格而变化，请勿从此处/其他堆栈溢出答案复制。

我无法调用最后一个命令，但经过一些试验和错误之后，我调用了：

sudo apt install libcudart.so.11.0   # this worked for me!

这对我很有效！