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Win10 CUDA CUDNN 安装配置(torch paddlepaddle)
2022-07-31 03:51:00 【狸不凡】
前言
终于,这次把CUDA CUDNN的配置给搞定了,我的显卡是Geforece Nvidia 930MX。
这次记录下配置过程。cuda10.2版本对torch,paddle有良好的支持,所以本次我们安装cuda10.2
一:查看支持cuda10.2的驱动程序
https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html
cuda 10.2 的驱动程序版本大于等于441.22
二:获取支持自己GPU的驱动程序
https://www.nvidia.cn/geforce/drivers/
根据第一步,我们需要下载的驱动程序大于等于441.22
输入本机型号
搜索查看满足的驱动
下载安装
下载 cuda10.2 和 cudnn
可以在下面官网获取,也可以直接从百度网盘获取
链接:https://pan.baidu.com/s/1W5IjQWDrT0kpmI1fMoapmQ?pwd=if33
提取码:if33
cuda 10.2下载地址
https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal
cudnn 各版本下载地址
https://developer.nvidia.com/rdp/cudnn-archive
解压安装cuda10.2
Update.Core 安装可能报错,直接删除就行
安装时选择自定义安装,然后自行选择安装路径,当然最好直接默认
解压添加cudnn
将解压的cudnn对应文件夹的文件,移动到我们安装的cuda对应的文件夹里面
添加环境变量
三 测试安装
nvcc -V
torch 历史版本
https://pytorch.org/get-started/previous-versions/
torch paddle tensorflow测试是否安装成功
import tensorflow as tf
print(tf.test.is_gpu_available())
print(tf.config.list_physical_devices('GPU'))
import torch
print(torch.cuda.is_available())
print(torch.Tensor(5, 3).cuda())
import paddle
paddle.fluid.install_check.run_check()
paddle.fluid.is_compiled_with_cuda()
结语
到此就基本完成了。
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