win7 + cuda + anaconda python + tensorflow-gpu + keras successful installation version match summary

 

win7 + cuda + anaconda python + tensorflow-gpu + keras successful installation version match summary

15:06:03 2019-09-20  wyx100  read the number 38 more

Category Column:  ML, development environment configuration

 

Disclaimer: This article is a blogger original article, follow the  CC 4.0 BY-SA  copyright agreement, reproduced, please attach the original source link and this statement.

This link: https://blog.csdn.net/wyx100/article/details/101061064

 

I met a lot of pit installation configuration process, in which the version compatibility between the software and the most relevant, here, lists the configuration software compatibility between different versions, easy to install configuration.

 

https://github.com/fo40225/tensorflow-windows-wheel

Path	Compiler	CUDA / cuDNN	SIMD	Notes
1.14.0\py37\CPU\sse2	VS2019 16.1	No	x86_64	Python 3.7
1.14.0\py37\CPU\avx2	VS2019 16.1	No	AVX2	Python 3.7
1.14.0\py37\GPU\cuda101cudnn76sse2	VS2019 16.1	10.1.168_425.25/7.6.0.64	x86_64	Python 3.7/Compute 3.0
1.14.0\py37\GPU\cuda101cudnn76avx2	VS2019 16.1	10.1.168_425.25/7.6.0.64	AVX2	Python 3.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0,7.5
1.13.1\py37\CPU\sse2	VS2017 15.9	No	x86_64	Python 3.7
1.13.1\py37\CPU\avx2	VS2017 15.9	No	AVX2	Python 3.7
1.13.1\py37\GPU\cuda101cudnn75sse2	VS2017 15.9	10.1.105_418.96/7.5.0.56	x86_64	Python 3.7/Compute 3.0
1.13.1\py37\GPU\cuda101cudnn75avx2	VS2017 15.9	10.1.105_418.96/7.5.0.56	AVX2	Python 3.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0,7.5
1.12.0\py36\CPU\sse2	VS2017 15.8	No	x86_64	Python 3.6
1.12.0\py36\CPU\avx2	VS2017 15.8	No	AVX2	Python 3.6
1.12.0\py36\GPU\cuda100cudnn73sse2	VS2017 15.8	10.0.130_411.31/7.3.1.20	x86_64	Python 3.6/Compute 3.0
1.12.0\py36\GPU\cuda100cudnn73avx2	VS2017 15.8	10.0.130_411.31/7.3.1.20	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0,7.5
1.12.0\py37\CPU\sse2	VS2017 15.8	No	x86_64	Python 3.7
1.12.0\py37\CPU\avx2	VS2017 15.8	No	AVX2	Python 3.7
1.12.0\py37\GPU\cuda100cudnn73sse2	VS2017 15.8	10.0.130_411.31/7.3.1.20	x86_64	Python 3.7/Compute 3.0
1.12.0\py37\GPU\cuda100cudnn73avx2	VS2017 15.8	10.0.130_411.31/7.3.1.20	AVX2	Python 3.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0,7.5
1.11.0\py36\CPU\sse2	VS2017 15.8	No	x86_64	Python 3.6
1.11.0\py36\CPU\avx2	VS2017 15.8	No	AVX2	Python 3.6
1.11.0\py36\GPU\cuda100cudnn73sse2	VS2017 15.8	10.0.130_411.31/7.3.0.29	x86_64	Python 3.6/Compute 3.0
1.11.0\py36\GPU\cuda100cudnn73avx2	VS2017 15.8	10.0.130_411.31/7.3.0.29	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0,7.5
1.11.0\py37\CPU\sse2	VS2017 15.8	No	x86_64	Python 3.7
1.11.0\py37\CPU\avx2	VS2017 15.8	No	AVX2	Python 3.7
1.11.0\py37\GPU\cuda100cudnn73sse2	VS2017 15.8	10.0.130_411.31/7.3.0.29	x86_64	Python 3.7/Compute 3.0
1.11.0\py37\GPU\cuda100cudnn73avx2	VS2017 15.8	10.0.130_411.31/7.3.0.29	AVX2	Python 3.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0,7.5
1.10.0\py36\CPU\sse2	VS2017 15.8	No	x86_64	Python 3.6
1.10.0\py36\CPU\avx2	VS2017 15.8	No	AVX2	Python 3.6
1.10.0\py36\GPU\cuda92cudnn72sse2	VS2017 15.8	9.2.148.1/7.2.1.38	x86_64	Python 3.6/Compute 3.0
1.10.0\py36\GPU\cuda92cudnn72avx2	VS2017 15.8	9.2.148.1/7.2.1.38	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.10.0\py27\CPU\sse2	VS2017 15.8	No	x86_64	Python 2.7
1.10.0\py27\CPU\avx2	VS2017 15.8	No	AVX2	Python 2.7
1.10.0\py27\GPU\cuda92cudnn72sse2	VS2017 15.8	9.2.148.1/7.2.1.38	x86_64	Python 2.7/Compute 3.0
1.10.0\py27\GPU\cuda92cudnn72avx2	VS2017 15.8	9.2.148.1/7.2.1.38	AVX2	Python 2.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.9.0\py36\CPU\sse2	VS2017 15.7	No	x86_64	Python 3.6
1.9.0\py36\CPU\avx2	VS2017 15.7	No	AVX2	Python 3.6
1.9.0\py36\GPU\cuda92cudnn71sse2	VS2017 15.7	9.2.148/7.1.4	x86_64	Python 3.6/Compute 3.0
1.9.0\py36\GPU\cuda92cudnn71avx2	VS2017 15.7	9.2.148/7.1.4	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.9.0\py27\CPU\sse2	VS2017 15.7	No	x86_64	Python 2.7
1.9.0\py27\CPU\avx2	VS2017 15.7	No	AVX2	Python 2.7
1.9.0\py27\GPU\cuda92cudnn71sse2	VS2017 15.7	9.2.148/7.1.4	x86_64	Python 2.7/Compute 3.0
1.9.0\py27\GPU\cuda92cudnn71avx2	VS2017 15.7	9.2.148/7.1.4	AVX2	Python 2.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.8.0\py36\CPU\sse2	VS2017 15.4	No	x86_64	Python 3.6
1.8.0\py36\CPU\avx2	VS2017 15.4	No	AVX2	Python 3.6
1.8.0\py36\GPU\cuda91cudnn71sse2	VS2017 15.4	9.1.85.3/7.1.3	x86_64	Python 3.6/Compute 3.0
1.8.0\py36\GPU\cuda91cudnn71avx2	VS2017 15.4	9.1.85.3/7.1.3	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.8.0\py27\CPU\sse2	VS2017 15.4	No	x86_64	Python 2.7
1.8.0\py27\CPU\avx2	VS2017 15.4	No	AVX2	Python 2.7
1.8.0\py27\GPU\cuda91cudnn71sse2	VS2017 15.4	9.1.85.3/7.1.3	x86_64	Python 2.7/Compute 3.0
1.8.0\py27\GPU\cuda91cudnn71avx2	VS2017 15.4	9.1.85.3/7.1.3	AVX2	Python 2.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.7.0\py36\CPU\sse2	VS2017 15.4	No	x86_64	Python 3.6
1.7.0\py36\CPU\avx2	VS2017 15.4	No	AVX2	Python 3.6
1.7.0\py36\GPU\cuda91cudnn71sse2	VS2017 15.4	9.1.85.3/7.1.2	x86_64	Python 3.6/Compute 3.0
1.7.0\py36\GPU\cuda91cudnn71avx2	VS2017 15.4	9.1.85.3/7.1.2	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.7.0\py27\CPU\sse2	VS2017 15.4	No	x86_64	Python 2.7
1.7.0\py27\CPU\avx2	VS2017 15.4	No	AVX2	Python 2.7
1.7.0\py27\GPU\cuda91cudnn71sse2	VS2017 15.4	9.1.85.3/7.1.2	x86_64	Python 2.7/Compute 3.0
1.7.0\py27\GPU\cuda91cudnn71avx2	VS2017 15.4	9.1.85.3/7.1.2	AVX2	Python 2.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.6.0\py36\CPU\sse2	VS2017 15.4	No	x86_64	Python 3.6
1.6.0\py36\CPU\avx2	VS2017 15.4	No	AVX2	Python 3.6
1.6.0\py36\GPU\cuda91cudnn71sse2	VS2017 15.4	9.1.85.3/7.1.1	x86_64	Python 3.6/Compute 3.0
1.6.0\py36\GPU\cuda91cudnn71avx2	VS2017 15.4	9.1.85.3/7.1.1	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.6.0\py27\CPU\sse2	VS2017 15.4	No	x86_64	Python 2.7
1.6.0\py27\CPU\avx2	VS2017 15.4	No	AVX2	Python 2.7
1.6.0\py27\GPU\cuda91cudnn71sse2	VS2017 15.4	9.1.85.2/7.1.1	x86_64	Python 2.7/Compute 3.0
1.6.0\py27\GPU\cuda91cudnn71avx2	VS2017 15.4	9.1.85.2/7.1.1	AVX2	Python 2.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.5.0\py36\CPU\avx	VS2017 15.4	No	AVX	Python 3.6
1.5.0\py36\CPU\avx2	VS2017 15.4	No	AVX2	Python 3.6
1.5.0\py36\GPU\cuda91cudnn7avx2	VS2017 15.4	9.1.85/7.0.5	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.5.0\py27\CPU\sse2	VS2017 15.4	No	x86_64	Python 2.7
1.5.0\py27\CPU\avx	VS2017 15.4	No	AVX	Python 2.7
1.5.0\py27\CPU\avx2	VS2017 15.4	No	AVX2	Python 2.7
1.5.0\py27\GPU\cuda91cudnn7sse2	VS2017 15.4	9.1.85/7.0.5	x86_64	Python 2.7/Compute 3.0
1.5.0\py27\GPU\cuda91cudnn7avx2	VS2017 15.4	9.1.85/7.0.5	AVX2	Python 2.7/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.4.0\py36\CPU\avx	VS2017 15.4	No	AVX	Python 3.6
1.4.0\py36\CPU\avx2	VS2017 15.4	No	AVX2	Python 3.6
1.4.0\py36\GPU\cuda91cudnn7avx2	VS2017 15.4	9.1.85/7.0.5	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1,7.0
1.3.0\py36\CPU\avx	VS2015 Update 3	No	AVX	Python 3.6
1.3.0\py36\CPU\avx2	VS2015 Update 3	No	AVX2	Python 3.6
1.3.0\py36\GPU\cuda8cudnn6avx2	VS2015 Update 3	8.0.61.2/6.0.21	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1
1.2.1\py36\CPU\avx	VS2015 Update 3	No	AVX	Python 3.6
1.2.1\py36\CPU\avx2	VS2015 Update 3	No	AVX2	Python 3.6
1.2.1\py36\GPU\cuda8cudnn6avx2	VS2015 Update 3	8.0.61.2/6.0.21	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1
1.1.0\py36\CPU\avx	VS2015 Update 3	No	AVX	Python 3.6
1.1.0\py36\CPU\avx2	VS2015 Update 3	No	AVX2	Python 3.6
1.1.0\py36\GPU\cuda8cudnn6avx2	VS2015 Update 3	8.0.61.2/6.0.21	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1
1.0.0\py36\CPU\sse2	VS2015 Update 3	No	x86_64	Python 3.6
1.0.0\py36\CPU\avx	VS2015 Update 3	No	AVX	Python 3.6
1.0.0\py36\CPU\avx2	VS2015 Update 3	No	AVX2	Python 3.6
1.0.0\py36\GPU\cuda8cudnn51sse2	VS2015 Update 3	8.0.61.2/5.1.10	x86_64	Python 3.6/Compute 3.0
1.0.0\py36\GPU\cuda8cudnn51avx2	VS2015 Update 3	8.0.61.2/5.1.10	AVX2	Python 3.6/Compute 3.0,3.5,5.0,5.2,6.1
0.12.0\py35\CPU\avx	VS2015 Update 3	No	AVX	Python 3.5
0.12.0\py35\CPU\avx2	VS2015 Update 3	No	AVX2	Python 3.5
0.12.0\py35\GPU\cuda8cudnn51avx2	VS2015 Update 3	8.0.61.2/5.1.10	AVX2	Python 3.5/Compute 3.0,3.5,5.0,5.2,6.1

tensorflow CUDA cudnn 版本对应关系

https://blog.csdn.net/yuejisuo1948/article/details/81043962

linux下：

windows下：

上面两张图是在这里找到的：https://tensorflow.google.cn/install/source  （右上角language选English）

 

 

tensorflow和keras版本搭配

https://docs.floydhub.com/guides/environments/

 

 

anaconda python 版本对应关系

https://blog.csdn.net/yuejisuo1948/article/details/81043823

本文链接：https://blog.csdn.net/yuejisuo1948/article/details/81043823

 

首先解释一下上表。 anaconda在每次发布新版本的时候都会给python3和python2都发布一个包，版本号是一样的。

表格中，python版本号下方的离它最近的anaconda包就是包含它的版本。

举个例子，假设你想安装python2.7.14，在表格中找到它，它下方的三个anaconda包（anaconda2-5.0.1、5.1.0、5.2.0）都包含python2.7.14；

假设你想安装python3.6.5，在表格中找到它，它下方的anaconda3-5.2.0就是你需要下载的包；

假设你想安装python3.7.0，在表格中找到它，它下方的anaconda3-5.3.0或5.3.1就是你需要下载的包；

镜像下载地址：清华镜像源

官方下载地址：https://repo.anaconda.com/archive/
 

 

https://blog.csdn.net/stephen_2018/article/details/80392545

win7 vs2015 cuda9.0 安装 Tensorflow-gpu 1.8

cuda_9.0.176_windows.exe

cudnn-9.0-windows7-x64-v7.zip

python-3.5.4-amd64.exe

 

https://blog.csdn.net/ei1990/article/details/84800151

WIN7系统安装 tensorflow1.6.0 + CUDA9.0 + cudnn7 版本

Anaconda3   5.2.0

CUDA9.0 + cudnn7 (9.1版本不支持tensorflow)

tensorflow-gpu 1.6.0

https://blog.csdn.net/Zqinstarking/article/details/80713338

防坑 centos7 安装 CUDA9.0 + cudnn7.1 +TensorFlow GPU版1.6.0/1.8.0

简单来说：tf1.5及以上用只能是cuda9.0，其他的tf1.4及以下版本就是cuda8.0等，最好自己去查查！可恶的是tf官方和nVidia都没有版本对应的说明！！！

https://blog.csdn.net/wukongabc_123/article/details/80379882

Windows 7下安装TensorFlow1.6（cuda9.0+cuDNN 7.0+python3.5+pip9）

https://blog.csdn.net/duoker/article/details/79483434

win7 x64 安装 TensorFlow1.6 CUDA 9.1+cuDNN7.1( 7.0.5)+python3.6 (python 3.5.2)

https://blog.csdn.net/wukongabc_123/article/details/80379882

win7+anaconda3+cuda9.0+CuDNN7+tensorflow-gpu+pycharm配置

https://blog.csdn.net/u011440696/article/details/79381375

tensorflow 安装GPU版本，个人总结，步骤比较详细

https://blog.csdn.net/gangeqian2/article/details/79358543

TensorFlow 安装GPU版本

https://blog.csdn.net/AAlonso/article/details/81504036

python+tensorflow+tensorflow-gpu+CUDA+cuDNN+pycharm全套环境配置教程 推荐

https://blog.csdn.net/kele52he/article/details/82986900

 

深度学习环境搭建-CUDA9.0、cudnn7.3、tensorflow_gpu1.10的安装

https://blog.csdn.net/xiaosa_kun/article/details/84868347

 

win7 vs2015 cuda9.0 安装 Tensorflow-gpu 1.8

https://blog.csdn.net/stephen_2018/article/details/80392545

 

WIN7系统安装 tensorflow1.6.0 + CUDA9.0 + cudnn7 版本

https://blog.csdn.net/ei1990/article/details/84800151

https://blog.csdn.net/weixin_42071277/article/details/88851868

Windows 7下安装TensorFlow1.6（cuda9.0+cuDNN 7.0+python3.5+pip9）

https://blog.csdn.net/duoker/article/details/79483434

 

匹配tensorflow-gpu和keras：

     tensorflow 1.5 和keras 2.1.3、keras 2.1.4、keras 2.3.0（运行代码会报错）

     tensorflow 1.4和keras 2.1.3

     tensorflow 1.3和keras 2.1.2

     tensorflow  1.2和keras 2.1.1