CUDA与PyTorch版本匹配但torch.cuda.is_available()返回False求助

我在搭载NVIDIA A100-SXM4-40GB GPU的集群上运行深度学习模型，所有版本看起来均匹配，但torch.cuda.is_available()仍返回False，恳请帮忙解决该问题，非常感谢！

环境版本信息 #

PyTorch与CUDA版本 #

>>> print(torch.__version__)
2.0.1+cu117
>>> print(torch.version.cuda)
11.7

nvcc版本输出 #

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Tue_May__3_18:49:52_PDT_2022
Cuda compilation tools, release 11.7, V11.7.64
Build cuda_11.7.r11.7/compiler.31294372_0

nvidia-smi输出 #

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.48.07    Driver Version: 515.48.07    CUDA Version: 11.7     |
|-------------------------------+----------------------+----------------------+| 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  NVIDIA A100-SXM...  On   | 00000000:07:00.0 Off |                   On || N/A   28C    P0    41W / 400W |     45MiB / 40960MiB |     N/A      Default ||                               |                      |              Enabled |+-------------------------------+----------------------+----------------------+

torch环境收集结果 #

PyTorch version: 2.0.1+cu117
Is debug build: False
CUDA used to build PyTorch: 11.7
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.1 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.27.7
Libc version: glibc-2.31

Python version: 3.8.18 (default, Sep 11 2023, 13:40:15)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.4.0-121-generic-x86_64-with-glibc2.17
Is CUDA available: False
CUDA runtime version: 11.7.64
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: GPU 0: NVIDIA A100-SXM4-40GB
Nvidia driver version: 515.48.07
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.4.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.4.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

内容的提问来源于stack exchange，提问作者Harry556