tensorflow cuda nivdia

https://www.w3cschool.cn/tensorflow_python/tensorflow_python/

NVIDIA 驱动程序下载

https://www.nvidia.cn/Download/index.aspx?lang=cn

驱动确定cuda tookit版本 https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html

cuda tookit 版本确定cuDNN版本

CUDA Toolkit	Linux x86_64 Driver Version	Windows x86_64 Driver Version
CUDA 10.1.105	>= 418.39	>= 418.96
CUDA 10.0.130	>= 410.48	>= 411.31
CUDA 9.2 (9.2.148 Update 1)	>= 396.37	>= 398.26
CUDA 9.2 (9.2.88)	>= 396.26	>= 397.44
CUDA 9.1 (9.1.85)	>= 390.46	>= 391.29
CUDA 9.0 (9.0.76)	>= 384.81	>= 385.54
CUDA 8.0 (8.0.61 GA2)	>= 375.26	>= 376.51
CUDA 8.0 (8.0.44)	>= 367.48	>= 369.30
CUDA 7.5 (7.5.16)	>= 352.31	>= 353.66
CUDA 7.0 (7.0.28)	>= 346.46	>= 347.62

 

CUDA Toolkit Download

https://developer.nvidia.com/cuda-toolkit-archive

 

Ubuntu 18.10（nvdia 418.56->cuda toolkit 10.1->cuDNN 7.5.0)

(nvidoa 390->cuda8.0->cuDNN6.0)

cuDNN Archive

https://developer.nvidia.com/rdp/cudnn-archive#a-collapse750-101

 

 

rope for spyder3

https://pypi.org/project/rope/#files

 

tensorflow与cuda cuDNN版本对应关系（在网页最下部）

https://tensorflow.google.cn/install/source tf-gpu

cuda9=>1.5~1.12(XLA)

cuda8=>1.0~1.4

1.13.1=>cuda10.0=>cuDNN7.5

版本	Python 版本	编译器	编译工具	cuDNN	CUDA
tensorflow_gpu-1.13.0	2.7、3.3-3.6	GCC 4.8	Bazel 0.19.2	7.4	10.0

tf1.4-gpu=>cuda8.0=>cuDNN6

tensorflow_gpu-1.4.0

2.7、3.3-3.6

GCC 4.8

Bazel 0.5.4

6

8

tensorflow-gpu 1.4.0

https://pypi.org/project/tensorflow-gpu/1.4.0/#files

 

配置cuda toolkit环境变量

(a)vim ~/.bashrc

(b)添加如下行，用于添加cuda bin的路径到环境变量PATH

export PATH=$PATH:/usr/local/cuda/bin

(c)添加如下行，用于添加cuda/lib和cuda/lib64路径到环境变量LD_LIBRARY_PATH

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib:/usr/local/cuda/lib64

(d)使配置生效

source ~/.bashrc

转载于:https://www.cnblogs.com/yanzisoft/p/10800778.html