第一步：安装cuda8.0（TensorFlow不支持cuda9.0版本，安装后会报错）
如果出现这种情况，可以从官方下载最新的显卡驱动，驱动安装后可以在C:\NVIDIA\DisplayDriver\385.41\Win10_64\International
找到ListDevices.txt与Display.Driver文件夹，选中并复制。重新运行cuda_8.0.61_win10.exe，并查看提取路径
C:\Users\zzx\AppData\Local\Temp\CUDA，当出现ListDevices.txt与Display.Driver文件夹时，将之前复制的
替换提取路径中的目标文件，然后检查系统时，会正常。安装时，选择自定义，全选，并安装。
第二步：安装cudnn6.0（cuda8.0与cudnn6.0搭配，cuda9.0和cudnn7.0搭配）
将cudnn中的bin，include，lib三个文件夹覆盖替换C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0中的bin，include，lib
添加环境变量：
添加后好像应该重启才能生效。
第三步：安装TensorFlow，默认是CPU版本的，如果想安装GPU版本，必须将旧的CPU版本下载
pip uninstall tensorflow
pip install tensorflow-gpu来安装
如果安装出现timeout 手动下载（地址：https://pypi.python.org/pypi/tensorflow）然后pip install 文件名
附件：cuda8.0+cudnn6.0下载链接http://download.csdn.net/download/hegongxu/10146459
最后测试程序：import tensorflow as tf #Creates a graph. a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a') b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b') c = tf.matmul(a, b) #Creates a session with log_device_placement set to True. sess = tf.Session(config=tf.ConfigProto(log_device_placement=True)) #Runs the op. print (sess.run(c))
成功结果：
2017-12-05 15:38:37.632186: 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 2017-12-05 15:38:38.586136: 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 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493 pciBusID: 0000:01:00.0 totalMemory: 2.00GiB freeMemory: 1.62GiB 2017-12-05 15:38:38.586528: 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 1050, pci bus id: 0000:01:00.0, compute capability: 6.1) Device mapping: /job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1 2017-12-05 15:38:38.661303: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\35\tensorflow\core\common_runtime\direct_session.cc:299] Device mapping: /job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1 MatMul: (MatMul): /job:localhost/replica:0/task:0/device:GPU:0 b: (Const): /job:localhost/replica:0/task:0/device:GPU:0 a: (Const): /job:localhost/replica:0/task:0/device:GPU:0 2017-12-05 15:38:38.665996: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\35\tensorflow\core\common_runtime\placer.cc:874] MatMul: (MatMul)/job:localhost/replica:0/task:0/device:GPU:0 2017-12-05 15:38:38.666324: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\35\tensorflow\core\common_runtime\placer.cc:874] b: (Const)/job:localhost/replica:0/task:0/device:GPU:0 2017-12-05 15:38:38.666690: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\35\tensorflow\core\common_runtime\placer.cc:874] a: (Const)/job:localhost/replica:0/task:0/device:GPU:0 [[ 22. 28.] [ 49. 64.]]