当前位置:网站首页>Win10 CUDA CUDNN installation configuration (torch paddlepaddle)
Win10 CUDA CUDNN installation configuration (torch paddlepaddle)
2022-07-31 04:02:00 【raccoon extraordinary】
Foreword
Finally, the configuration of CUDA CUDNN is done this time. My graphics card is Geforece Nvidia 930MX.
This time record the configuration process.The cuda10.2 version has good support for torch and paddle, so this time we install cuda10.2
One: Check the driver that supports cuda10.2
https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html
cuda 10.2 driver version greater than or equal to 441.22
Two: Get a driver that supports your own GPU
https://www.nvidia.cn/geforce/drivers/
According to the first step, the driver we need to download is greater than or equal to 441.22
Enter the model number
Search for the driver that meets the requirements
Download and install
download cuda10.2 and cudnn
You can get it on the official website below, or you can get it directly from Baidu Netdisk
Link: https://pan.baidu.com/s/1W5IjQWDrT0kpmI1fMoapmQ?pwd=if33
Extraction code: if33
cuda 10.2 download address
https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal
cudnn version download address
https://developer.nvidia.com/rdp/cudnn-archive
Unzip and install cuda10.2
Update.Core installation may report errors, just delete it
Select custom installation during installation, and then choose the installation path by yourself, of course, it is best to default directly
Unzip and add cudnn
Move the files in the folder corresponding to the unzipped cudnn to the folder corresponding to the cuda we installed
Add environment variables
Third test installation
nvcc -V
torch history
https://pytorch.org/get-started/previous-versions/
torch paddle tensorflow test whether the installation is successful
import tensorflow as tfprint(tf.test.is_gpu_available())print(tf.config.list_physical_devices('GPU'))import torchprint(torch.cuda.is_available())print(torch.Tensor(5, 3).cuda())import paddlepaddle.fluid.install_check.run_check()paddle.fluid.is_compiled_with_cuda()
Concluding remarks
This is almost done.
边栏推荐
- 安全20220715
- interprocess communication
- C language from entry to such as soil, the data store
- 【AUTOSAR-RTE】-4-Port和Interface以及Data Type
- Detailed explanation of TCP and UDP
- 进程间通信
- The BP neural network
- SIP Protocol Standard and Implementation Mechanism
- MATLAB/Simulink & & STM32CubeMX tool chain completes model-based design development (MBD) (three)
- Detailed explanation of TCP (2)
猜你喜欢
IDEA comment report red solution
立足本土,链接全球 | 施耐德电气“工业SI同盟”携手伙伴共赴未来工业
(五)final、抽象类、接口、内部类
从滴滴罚款后数据治理思考
Learning DAVID Database (1)
已解决(最新版selenium框架元素定位报错)NameError: name ‘By‘ is not defined
【小土堆补充】Pytorch学习笔记_Anaconda虚拟环境使用
【C语言进阶】文件操作(一)
(4) Recursion, variable parameters, access modifiers, understanding main method, code block
[Swift]自定义点击APP图标弹出的快捷方式
随机推荐
Implementation of a sequence table
Learning DAVID Database (1)
Summary of Huawei Distributed Storage FusionStorage Knowledge Points [Interview]
els block to the left to move the conditional judgment
Mysql 45 study notes (23) How does MYSQL ensure that data is not lost
Win10 CUDA CUDNN 安装配置(torch paddlepaddle)
安全20220712
(8) Math class, Arrays class, System class, Biglnteger and BigDecimal classes, date class
qlib架构
beforeDestroy与destroyed的使用
高等数学---第九章二重积分
LocalDate加减操作及比较大小
Based on the local, linking the world | Schneider Electric "Industrial SI Alliance" joins hands with partners to go to the future industry
[AUTOSAR-RTE]-5-Explicit (explicit) and Implicit (implicit) Sender-Receiver communication
mysql基础知识(二)
从滴滴罚款后数据治理思考
Difference between unallocated blocks and unused blocks in database files
$parent/$children and ref
问题7:列表的拼接
[C language] General method of expression evaluation