win安装cuda、cudnn检测是否安装成功

1、win+R cmd进入终端

激活创建的虚拟环境

conda activate PyTorch

(PyTorch) E:\Wan_ji_project\yolo3-pytorch-master>python
Python 3.8.13 (default, Mar 28 2022, 06:59:08) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc
. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()  # cuda是否可用
True
>>> print(torch.version.cuda)  # 查看pytorch 对应的cuda版本
11.3
>>> print(torch.__version__) # 查看pytorch版本
1.11.0
>>> torch.cuda.device_count()  # 返回gpu数量
1
>>> torch.cuda.get_device_name(0) # 返回gpu名字，设备索引默认从0开始；
'NVIDIA GeForce MX250'
>>> torch.cuda.current_device()  # 返回当前设备索引
0

通过nvcc -V和nvidia-smi分别查看cuda版本

(PyTorch) E:\Wan_ji_project\yolo3-pytorch-master>nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Tue_Mar__8_18:36:24_Pacific_Standard_Time_2022
Cuda compilation tools, release 11.6, V11.6.124
Build cuda_11.6.r11.6/compiler.31057947_0

(PyTorch) E:\Wan_ji_project\yolo3-pytorch-master>nvidia-smi
Thu Apr 28 11:16:49 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 511.65       Driver Version: 511.65       CUDA Version: 11.6     |
|-------------------------------+----------------------+----------------------+
| 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  | 00000000:02:00.0 Off |                  N/A |
| N/A   43C    P8    N/A /  N/A |      0MiB /  2048MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A       288      C   ...l\envs\PyTorch\python.exe    N/A      |
+-----------------------------------------------------------------------------+

检测cudnn可用性

(PyTorch) E:\Wan_ji_project\yolo3-pytorch-master>python
Python 3.8.13 (default, Mar 28 2022, 06:59:08) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.backends.cudnn.version())
8200
>>> a = torch.tensor(1.)
>>> a.cuda()
tensor(1., device='cuda:0')
>>> from torch.backends import cudnn # 若正常则静默
>>> cudnn.is_available() # 若正常返回True
True
>>> cudnn.is_acceptable(a.cuda()) # 若正常返回True
True
>>>