window10TensorFlow1.4安装

1. 第一步首先需要去下载一个Python。

用管理员身份打开cmd窗口&＃xff0c;输入命令conda create --name python35 python&＃61;3.5&＃xff0c;等待安装完成即可&＃xff1b;


注意:必须为3.5版本

激活&＃xff1a;

activate python35

释放

deactivate

#To activate this environment, use:

# > activate python35

#

# To deactivate an active environment, use:

# > deactivate






2. 各版本TensorFlow下载地址&＃xff1a;https://pypi.python.org/pypi/tensorflow-gpu/1.4.0



(python35) C:\Users\Administrator>pip install tensorflow_gpu-1.4.0-cp35-cp35m-win_amd64.whl

Processing c:\users\administrator\tensorflow_gpu-1.4.0-cp35-cp35m-win_amd64.whl

Collecting enum34>&＃61;1.1.6 (from tensorflow-gpu&＃61;&＃61;1.4.0)

  Using cached enum34-1.1.6-py3-none-any.whl

Collecting protobuf>&＃61;3.3.0 (from tensorflow-gpu&＃61;&＃61;1.4.0)

  Downloading protobuf-3.5.2-cp35-cp35m-win_amd64.whl (958kB)

    100% |████████████████████████████████| 962kB 46kB/s

Collecting numpy>&＃61;1.12.1 (from tensorflow-gpu&＃61;&＃61;1.4.0)

  Downloading numpy-1.14.2-cp35-none-win_amd64.whl (13.4MB)

    100% |████████████████████████████████| 13.4MB 1.0MB/s

Requirement already satisfied: wheel>&＃61;0.26 in c:\users\administrator\anaconda3\envs\python35\lib\site-packages (from tensorflow-gpu&＃61;&＃61;1.4.0)

Collecting tensorflow-tensorboard<0.5.0,>&＃61;0.4.0rc1 (from tensorflow-gpu&＃61;&＃61;1.4.0)

  Using cached tensorflow_tensorboard-0.4.0-py3-none-any.whl

Collecting six>&＃61;1.10.0 (from tensorflow-gpu&＃61;&＃61;1.4.0)

  Downloading six-1.11.0-py2.py3-none-any.whl

Requirement already satisfied: setuptools in c:\users\administrator\anaconda3\envs\python35\lib\site-packages (from protobuf>&＃61;3.3.0->tensorflow-gpu&＃61;&＃61;1.4.0)

Collecting bleach&＃61;&＃61;1.5.0 (from tensorflow-tensorboard<0.5.0,>&＃61;0.4.0rc1->tensorflow-gpu&＃61;&＃61;1.4.0)

  Using cached bleach-1.5.0-py2.py3-none-any.whl

Collecting markdown>&＃61;2.6.8 (from tensorflow-tensorboard<0.5.0,>&＃61;0.4.0rc1->tensorflow-gpu&＃61;&＃61;1.4.0)

  Using cached Markdown-2.6.11-py2.py3-none-any.whl

Collecting html5lib&＃61;&＃61;0.9999999 (from tensorflow-tensorboard<0.5.0,>&＃61;0.4.0rc1->tensorflow-gpu&＃61;&＃61;1.4.0)

  Using cached html5lib-0.9999999.tar.gz

Collecting werkzeug>&＃61;0.11.10 (from tensorflow-tensorboard<0.5.0,>&＃61;0.4.0rc1->tensorflow-gpu&＃61;&＃61;1.4.0)

  Downloading Werkzeug-0.14.1-py2.py3-none-any.whl (322kB)

    100% |████████████████████████████████| 327kB 1.7MB/s

Building wheels for collected packages: html5lib

  Running setup.py bdist_wheel for html5lib ... done

  Stored in directory: C:\Users\Administrator\AppData\Local\pip\Cache\wheels\6f\85\6c\56b8e1292c6214c4eb73b9dda50f53e8e977bf65989373c962

Successfully built html5lib

Installing collected packages: enum34, six, protobuf, numpy, html5lib, bleach, markdown, werkzeug, tensorflow-tensorboard, tensorflow-gpu

Successfully installed bleach-1.5.0 enum34-1.1.6 html5lib-0.9999999 markdown-2.6.11 numpy-1.14.2 protobuf-3.5.2 six-1.11.0 tensorflow-gpu-1.4.0 tensorflow-tensorboard-0.4.0 werkzeug-0.14.1






3. &＃xff08;1&＃xff09;安装CUDA 参考网站&＃xff1a;http://blog.sina.com.cn/s/blog_14935c5880102wu86.html

下载并按照CUDA&＃xff1a;进入此网站(https://developer.nvidia.com/cuda-downloads)&＃xff0c;点击Windows





 &＃xff08;2&＃xff09;安装cudnn 参考网站&＃xff1a;http://blog.csdn.net/sb19931201/article/details/53648615

cuDNN下载网站(https://developer.nvidia.com/rdp/form/cudnn-download-survey)&＃xff0c;





 
&＃xff08;3&＃xff09;安装提示&＃xff1a;
下载这个安装包需要注册并且填一堆问卷&＃xff0c;下下来以后把相关包不用安装&＃xff0c;直接拷到cuda路径对应的文件夹下面就行;
将这三个文件夹下的文件拷到CUDA对应的文件夹下面即可



cuda安装完成后默认的环境变量配置不对&＃xff0c;CUDA_PATH是C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0,

但是这样不能直接访问到bin和lib\x64下的程序包&＃xff0c;在path中加上这两个路径即可。


C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin\lib\x64

(4)
下载并安装Anaconda&＃xff1a;进入
下载网站(
https://www.continuum.io/downloads
)&＃xff0c;点击Windows图标




4. 测试

1、进入cmd激活python35环境&＃xff0c;键入python进入python shell&＃xff1b;

2、输入import tensorflow as tf导入tensorflow库&＃xff0c;无报错即成功安装TensorFlow&＃xff1b;

3、键入代码

   hello &＃61; tf.constant(&＃39;Hello, TensorFlow!&＃39;)   

   sess &＃61; tf.Session()





>>> hello&＃61;tf.constant(&＃39;hello,tensorflow!&＃39;)

>>> sess&＃61;tf.Session()

2018-03-16 11:47:17.431306: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\35\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

2018-03-16 11:47:18.130259: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\35\tensorflow\core\common_runtime\gpu\gpu_device.cc:1030] Found device 0 with properties:

name: GeForce GTX 1060 6GB major: 6 minor: 1 memoryClockRate(GHz): 1.7085

pciBusID: 0000:01:00.0

totalMemory: 6.00GiB freeMemory: 5.01GiB

2018-03-16 11:47:18.130433: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\35\tensorflow\core\common_runtime\gpu\gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1060 6GB, pci bus id: 0000:01:00.0, compute capability: 6.1)

>>>





>>> tf.__version__

&＃39;1.4.0&＃39;



>>> a&＃61;tf.random_normal((100,100))

>>> b&＃61;tf.random_normal((100,500))

>>> c&＃61;tf.matmul(a,b)

>>> sess &＃61; tf.InteractiveSession()

2018-03-16 11:52:38.934649: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\35\tensorflow\core\common_runtime\gpu\gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1060 6GB, pci bus id: 0000:01:00.0, compute capability: 6.1)

>>> sess.run(c)

array([[ 2.38107853e&＃43;01, -2.83940554e&＃43;00,  3.25224590e&＃43;00, ...,

         1.48687639e&＃43;01,  1.14226675e&＃43;01, -2.92734909e&＃43;01],

       [-1.78896534e&＃43;00,  1.63350086e&＃43;01, -2.12260437e&＃43;01, ...,

        -9.29720116e&＃43;00,  1.34245167e&＃43;01,  6.11474180e&＃43;00],

       [-1.08380480e&＃43;01, -1.27219784e&＃43;00,  7.25827408e&＃43;00, ...,

        -9.24288750e&＃43;00,  7.42250681e&＃43;00,  8.72167200e-02],

       ...,

       [ 1.50586033e&＃43;00, -1.09648788e-02, -6.79777718e&＃43;00, ...,

         4.91322136e&＃43;00, -7.05123472e&＃43;00, -3.51647973e&＃43;00],

       [-5.51862574e&＃43;00,  4.30281878e&＃43;00, -5.66631556e&＃43;00, ...,

        -4.48143864e&＃43;00,  9.17361164e&＃43;00, -6.72823429e&＃43;00],

       [ 1.17639284e&＃43;01, -1.05234756e&＃43;01, -1.81000245e&＃43;00, ...,

         3.35602999e&＃43;00,  7.88399172e&＃43;00,  9.59712029e&＃43;00]], dtype&＃61;float32)