參考博客：http://blog.csdn.net/zhaoyu106/article/details/52793183/，
http://blog.csdn.net/u010900574/article/details/52201808
由於我之前已經配置過cuda8.0和cudnn5.1.10所以不用安裝了
1、安裝bazel
點擊鏈接： installer for your system，跳轉到Bazel的下載頁面：
下載bazel-0.7.0-installer-linux-x86_64.sh到桌面，下載最新版的，不用和我的一致，然后在terminal中輸入以下命令
cd /home/***(自己的用戶名)/Desktop/###(這個命令意思是找到剛剛我們用U盤傳過來的文件) chmod +x PATH_TO_INSTALL.SH #對.sh文件授權 ./PATH_TO_INSTALL.SH --user #運行.sh文件
2、安裝第三方庫
在terminal中輸入以下命令
sudo apt-get install python-numpy swig python-dev python-wheel #安裝第三方庫 sudo apt-get install git git clone git://github.com/numpy/numpy.git numpy
3、安裝tensorflow
在terminal中輸入以下命令
git clone https://github.com/tensorflow/tensorflow
在terminal中輸入以下命令：
cd ~/tensorflow #切換到tensorflow文件夾 ./configure #執行configure文件
Do you wish to use jemalloc as the malloc implementation? [Y/n] y jemalloc enabled Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] n No Google Cloud Platform support will be enabled for TensorFlow Do you wish to build TensorFlow with Hadoop File System support? [y/N] n No Hadoop File System support will be enabled for TensorFlow Do you wish to build TensorFlow with the XLA just-in-time compiler (experimental)? [y/N] n No XLA JIT support will be enabled for TensorFlow Found possible Python library paths: /usr/lib/python2.7/site-packages /usr/lib64/python2.7/site-packages Please input the desired Python library path to use. Default is [/usr/lib/python2.7/site-packages] Using python library path: /usr/lib/python2.7/site-packages Do you wish to build TensorFlow with OpenCL support? [y/N] n No OpenCL support will be enabled for TensorFlow Do you wish to build TensorFlow with CUDA support? [y/N] y CUDA support will be enabled for TensorFlow Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]: Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: 8.0 Please specify the location where CUDA 8.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-8.0
4、創建pip
在tensorflow的根目錄下，在terminal中輸入以下命令：
bazel build -c opt //tensorflow/tools/pip_package:build_pip_package bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg sudo pip install /home/***（你自己的用戶名）/Desktop/tensorflow-0.10.0-cp2-none-any.whl
tensorflow-0.10.0-cp2-none-any.whl要根據你下載的文件名有所更改。
5、設置tensorflow環境
bazel build -c opt //tensorflow/tools/pip_package:build_pip_package # To build with GPU support: bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package mkdir _python_build cd _python_build ln -s ../bazel-bin/tensorflow/tools/pip_package/build_pip_package.runfiles/org_tensorflow/* . ln -s ../tensorflow/tools/pip_package/* . python setup.py develop
6、tensorflow測試
$ python
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> print sess.run(hello)
Hello, TensorFlow!
>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> print sess.run(a+b)
42
>>>
大功告成
出現的錯誤
操作
bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
報錯
ERROR: /home/yaroslavvb/tensorflow.git/tensorflow/tensorflow/core/kernels/BUILD:1080:1: undeclared inclusion(s) in rule '//tensorflow/core/kernels:cwise_op_gpu': this is missing dependency dependency for following files included by 'tensorflow/core/kernels/cwise_op_gpu_floor.cu.cc': '/usr/local/cuda-8.0/include/cuda_runtime.h' '/usr/local/cuda-8.0/include/host_config.h' '/usr/local/cuda-8.0/include/builtin_types.h' '/usr/local/cuda-8.0/include/device_types.h' '/usr/local/cuda-8.0/include/host_defines.h' '/usr/local/cuda-8.0/include/driver_types.h' '/usr/local/cuda-8.0/include/surface_types.h' '/usr/local/cuda-8.0/include/texture_types.h'
可以進入tensorflow/third_party/gpus/crosstool/目錄，打開CROSSTOOL文件，搜索cxx_builtin_include_directory，應該有三行，在下面添加行如下
cxx_builtin_include_directory: "/usr/local/cuda-8.0/include"
如果出現的錯誤是類似的，只要將cxx_builtin_include_directory: "/usr/local/cuda-8.0/include"的文件路徑改一下就可以了，親測有效
再次運行上一步的命令，應該就沒問題了。