Windows下Anaconda环境安装Tensorflow

朴灿烈づ我的快乐病毒、 2022-06-09 05:37 353阅读 0赞

1. 安装好Anaconda后请确保以下几个路径已经添加到Window系统环境变量的path中

C:\\ProgramData\\Anaconda3      //C:\\ProgramData\\Anaconda3是我安装Anaconda的路径

C:\\ProgramData\\Anaconda3\\Scripts        //Anaconda路径的Scripts子文件夹

C:\\ProgramData\\Anaconda3\\Library\\bin

2. 如下步骤，conda会帮你安装好所有相关软件包，本方法适合网速较快的朋友，如果网速较慢，建议直接用另一种方法3

C:\\>conda create -n tensorflow  
  
C:\\>activate tensorflow  
  
(tensorflow) C:\\>python -m pip install --upgrade pip  
Requirement already up-to-date: pip in c:\\programdata\\anaconda3\\lib\\site-packages  
  
(tensorflow) C:\\>anaconda search -t conda tensorflow  
Using Anaconda API: https://api.anaconda.org  
Run 'anaconda show <USER/PACKAGE>' to get more details:  
Packages:  
     Name                      |  Version | Package Types   | Platforms  
     ------------------------- |   ------ | --------------- | ---------------  
     HCC/tensorflow            |    1.0.0 | conda           | linux-64  
     HCC/tensorflow-cpucompat  |    1.0.0 | conda           | linux-64  
     HCC/tensorflow-fma        |    1.0.0 | conda           | linux-64  
     SentientPrime/tensorflow  |    0.6.0 | conda           | osx-64  
                                          : TensorFlow helps the tensors flow  
     SmartAg/tensorflow\_gpu    |    1.0.1 | conda           | linux-aarch64  
     acellera/tensorflow-cuda  |   0.12.1 | conda           | linux-64  
     anaconda/tensorflow       |    1.2.1 | conda           | linux-ppc64le, linux-64, osx-64, win-64  
                                          : TensorFlow is a machine learning library  
     anaconda/tensorflow-gpu   |    1.2.1 | conda           | linux-ppc64le, linux-64, win-64  
                                          : TensorFlow is a machine learning library  
     conda-forge/r-tensorflow  |      0.7 | conda           | linux-64, osx-64, win-64  
     conda-forge/tensorflow    |    1.2.1 | conda           | linux-64, win-64, osx-64  
                                          : TensorFlow helps the tensors flow  
     creditx/tensorflow        |    0.9.0 | conda           | linux-64  
                                          : TensorFlow helps the tensors flow  
     derickl/tensorflow        |    1.2.1 | conda           | osx-64  
                                          : TensorFlow helps the tensors flow  
     dhirschfeld/tensorflow    |    1.2.0 | conda           | win-64  
                                          : Computation using data flow graphs for scalable machine learning  
     dseuss/tensorflow         |          | conda           | osx-64  
     guyanhua/tensorflow       |    1.0.0 | conda           | linux-64  
     ijstokes/tensorflow       | 2017.03.03.1349 | conda, ipynb    | linux-64  
     intel/tensorflow          |    1.2.1 | pypi, conda     | linux-64  
     jjh\_cio\_testing/tensorflow |    1.2.0 | conda           | linux-64  
                                          : TensorFlow is a machine learning library  
     jjh\_cio\_testing/tensorflow-gpu |    1.2.1 | conda           | linux-64  
                                          : TensorFlow is a machine learning library  
     jjh\_ppc64le/tensorflow    |    1.2.1 | conda           | linux-ppc64le  
                                          : TensorFlow is a machine learning library  
     jjh\_ppc64le/tensorflow-gpu |    1.2.1 | conda           | linux-ppc64le  
                                          : TensorFlow is a machine learning library  
     jjhelmus/tensorflow       | 0.12.0rc0 | conda, pypi     | linux-64, osx-64  
                                          : TensorFlow helps the tensors flow  
     jjhelmus/tensorflow-gpu   |    1.0.1 | conda           | linux-64  
     kevin-keraudren/tensorflow |    0.9.0 | conda           | linux-64  
     marta-sd/tensorflow       |    1.2.0 | conda           | linux-64  
     marta-sd/tensorflow-gpu   |    1.2.0 | conda           | linux-64  
     memex/tensorflow          |    0.5.0 | conda           | linux-64, osx-64  
                                          : TensorFlow helps the tensors flow  
     mhworth/tensorflow        |    0.7.1 | conda           | osx-64  
                                          : TensorFlow helps the tensors flow  
     miovision/tensorflow      | 0.10.0.gpu | conda           | linux-64, osx-64  
     msarahan/tensorflow       | 1.0.0rc2 | conda           | linux-64  
     mutirri/tensorflow        | 0.10.0rc0 | conda           | linux-64  
     mwojcikowski/tensorflow   |    1.0.1 | conda           | linux-64  
     nehaljwani/tensorflow     |    1.2.1 | conda           | osx-64, win-64  
                                          : TensorFlow is a machine learning library  
     nehaljwani/tensorflow-gpu |    1.1.0 | conda           | win-64  
                                          : TensorFlow is a machine learning library  
     r/r-tensorflow            |    0.8.2 | conda           | linux-64, win-32, win-64, linux-32, osx-64  
                                          : Interface to TensorFlow  
     rdonnelly/tensorflow      |    0.9.0 | conda           | linux-64  
     rdonnellyr/r-tensorflow   |    0.4.0 | conda           | linux-64  
     test\_org\_002/tensorflow   | 0.10.0rc0 | conda           |  
     thomasantony/tensorflow\_gpu |    1.0.1 | conda           | linux-aarch64  
Found 39 packages  
  
  
(tensorflow) C:\\>anaconda show  anaconda/tensorflow-gpu  
Using Anaconda API: https://api.anaconda.org  
Name:    tensorflow-gpu  
Summary: TensorFlow is a machine learning library  
Access:  public  
Package Types:  conda  
Versions:  
   + 1.0.1  
   + 1.1.0  
   + 1.2.1  
  
  
To install this package with conda run:  
     conda install --channel https://conda.anaconda.org/anaconda tensorflow-gpu  
  
  
//选择安装最新GPU版本，你也可以选择安装CPU版， 国内连接这个网站比较慢，也可以用清华大学镜像网站

/\*

//可以配置清华大学镜像网址

(tensorflow) C:\\>conda config --addchannels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/

(tensorflow) C:\\>conda config --setshow\_channel\_urls yes

(tensorflow) C:\\>conda install --channel hhttps://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/  tensorflow-gpu

\*/

//用anaconda主机下载，可能比较慢  
(tensorflow) C:\\>conda install --channel https://conda.anaconda.org/anaconda tensorflow-gpu  
Fetching package metadata .............  
Solving package specifications: .  
  
  
The following NEW packages will be INSTALLED:  
  
  
    cudatoolkit:    8.0-1             anaconda  
    cudnn:          6.0-0             anaconda  
    libprotobuf:    3.2.0-vc14\_0      anaconda \[vc14\]  
    mkl:            2017.0.3-0        anaconda  
    numpy:          1.12.1-py36\_0     anaconda  
    pip:            9.0.1-py36\_1      anaconda  
    protobuf:       3.2.0-py36\_0      anaconda  
    python:         3.6.2-0           anaconda  
    setuptools:     27.2.0-py36\_1     anaconda  
    six:            1.10.0-py36\_0     anaconda  
    tensorflow-gpu: 1.1.0-np112py36\_0 anaconda  
    vs2015\_runtime: 14.0.25420-0      anaconda  
    werkzeug:       0.12.2-py36\_0     anaconda  
    wheel:          0.29.0-py36\_0     anaconda  
    zlib:           1.2.11-vc14\_0     anaconda \[vc14\]  
  
  
Proceed (\[y\]/n)? y  
  
等待.................................

另一种方法：

3  安装CPU版本请跳过3.1 3.2 3.3

下载 3.1 3.2

3.1

CUDA® Toolkit 8.0. For details, see [NVIDIA's documentation][NVIDIA_s documentation]

3.2   需要用邮箱注册成Nvdia开发者下载，最好用国外邮箱，国内有些邮箱可能收不到激活邮件。

注意现在tensorflow还不支持最新的cuDNN7.0， 一定要下载cuDNN V6.0 for cuda8.0

cuDNN v6 or v6.1. For details, see [NVIDIA's documentation][NVIDIA_s documentation 1]

3.3

安装完3.1后，确认cuda toolkit的路径已经在系统环境变量path中，不在请手动添加 toolkit的安装路径 如C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v8.0到系统环境变量

将3.2文件解压后的三个文件夹拷贝到C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v8.0

3.4

cmd指令窗口运行

C:\\>conda create -n tensorflow  
C:\\>activate tensorflow

//安装CPU版本用这个指令

(tensorflow) C:\\>pip install --ignore-installed --upgrade tensorflow

//如果安装GPU版本用这个指令

(tensorflow) C:\\pip install --ignore-installed --upgrade tensorflow-gpu

4 确认tensorflow正确安装

C:\\>python

输入如下代码

>>> import tensorflow as tf >>> hello = tf.constant('Hello, TensorFlow!') >>> sess = tf.Session() >>> print(sess.run(hello))

当看到如下打印，即正确安装了

b'Hello, TensorFlow!'  
>>>

No module pip\* 解决方法

(tensorflow) C:\\WINDOWS\\system32>python -m ensurepip

(tensorflow) C:\\WINDOWS\\system32>easy\_install pip==18.1

[NVIDIA_s documentation]: http://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/
[NVIDIA_s documentation 1]: https://developer.nvidia.com/cudnn