我在GTX 1050TI上运行 Ubuntu20.04.我已经安装了 CUDA11.3.
nvidia-smi输出：
Wed Apr 6 18:27:23 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 465.19.01 Driver Version: 465.19.01 CUDA Version: 11.3 |
|-------------------------------+----------------------+----------------------+
| 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 GeForce ... Off | 00000000:01:00.0 Off | N/A |
| N/A 44C P8 N/A / N/A | 11MiB / 4040MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 3060 G /usr/lib/xorg/Xorg 4MiB |
| 0 N/A N/A 4270 G /usr/lib/xorg/Xorg 4MiB |
+-----------------------------------------------------------------------------+
nvcc --version输出：
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Sun_Mar_21_19:15:46_PDT_2021
Cuda compilation tools, release 11.3, V11.3.58
Build cuda_11.3.r11.3/compiler.29745058_0
Anaconda PyTorch 没有检测到 CUDA：
> import torch
> torch.cuda.is_available()
> False
有什么想法如何解决问题吗？
解决方案：
Conda在我的情况下安装了CPU构建。您可以通过运行torch.version.cuda轻松识别您的构建类型，如果您拥有CUDA构建，该应该返回一个字符串。如果您得到无，那么您正在运行CPU构建，它不会检测到CUDA
为了解决这个问题，我使用pip代替安装了火炬：
pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113