运行NVIDIA-SMI给出,
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 528.33 Driver Version: 528.33 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... WDDM | 00000000:01:00.0 On | N/A |
| N/A 49C P8 N/A / N/A | 244MiB / 4096MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
运行conda list pytorch
给出,
# Name Version Build Channel
pytorch 1.13.1 py3.9_cpu_0 pytorch
pytorch-cuda 11.7 h67b0de4_1 pytorch
pytorch-mutex 1.0 cpu pytorch
运行nvcc --version
得到,
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Jun__8_16:59:34_Pacific_Daylight_Time_2022
Cuda compilation tools, release 11.7, V11.7.99
Build cuda_11.7.r11.7/compiler.31442593_0
作为参考,我有一个GeForce GTX 1050ti
我已经试过用conda和pip卸载pytorch,然后用,
conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
1条答案
按热度按时间dgiusagp1#
所以我删除了所有与torch和cuda相关的内容(使用conda list torch和conda list cuda时发现的),然后使用重新安装
康达安装pytorch Torch 视觉 Torch 音频pytorch-cuda = 11.7-c pytorch-c英伟达
以及
conda安装-c水蟒cudatoolkit
而且现在起作用了