Anaconda中的Python包不同于命令行到jupyterhub (linux)

Question

这里有奇怪的问题。我正在开发Ubuntu20.04，使用Anaconda来设置一些python环境。具体来说，我试图设置tensorflow使用我的GPU，但这只是一个细节。问题是，当我打开一个终端并执行以下命令(对于称为tf的环境)时，所有操作都是正确的：

conda activate tf
python

然后在python提示符中运行

import tensorflow as tf
tf.config.list_physical_devices()

输出很好，它表明我有一个GPU：

PhysicalDevice(名称=‘/物理_设备:CPU:0，设备类型=’CPU‘)，PhysicalDevice(名称=’/物理_设备:GPU:0‘，设备_PhysicalDevice=’GPU‘)

于是我启动了木星实验室，我为它添加了一个叫做tf的环境，我运行了相同的命令，它说它找不到一些包，只显示CPU作为物理设备。这就是问题所在。这是输出：

2022-02-16 09:20:03.656417: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:936] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-16 09:20:03.656737: W tensorflow/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
2022-02-16 09:20:03.656836: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcublas.so.11'; dlerror: libcublas.so.11: cannot open shared object file: No such file or directory
2022-02-16 09:20:03.656927: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcublasLt.so.11'; dlerror: libcublasLt.so.11: cannot open shared object file: No such file or directory
2022-02-16 09:20:03.658936: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcusolver.so.11'; dlerror: libcusolver.so.11: cannot open shared object file: No such file or directory
2022-02-16 09:20:03.659034: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcusparse.so.11'; dlerror: libcusparse.so.11: cannot open shared object file: No such file or directory
2022-02-16 09:20:03.659198: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1850] 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...
[PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU')]

如果使用此环境打开控制台，也会发生同样的情况。但是在jupyter中，如果我打开一个普通的终端和activate tf，那么它就能正常工作。

为什么这里的行为不同？这是我第一次看到这种事发生。有人知道如何让jupyter的行为与命令行的行为相同吗？

谢谢。

UPDATE我认为问题可能是$PATH变量，但我在jupyter中强制执行路径，使其与终端会话中显示的相同，但仍然会得到相同的错误。

Answer 1

运行木星笔记本的环境有一个错误的LD_LIBRARY_PATH，然后它找不到使用GPU所需的CUDA或cudnn库。