参考博客:http://blog.csdn.net/zhaoyu106/article/details/52793183/,
http://blog.csdn.net/u010900574/article/details/52201808
由于我之前已经配置过cuda8.0和cudnn5.1.10所以不用安装了
1、安装bazel
点击链接: installer for your system,跳转到Bazel的下载页面:
下载bazel-0.7.0-installer-linux-x86_64.sh到桌面,下载最新版的,不用和我的一致,然后在terminal中输入以下命令
cd /home/***(自己的用户名)/Desktop/###(这个命令意思是找到刚刚我们用U盘传过来的文件) chmod +x PATH_TO_INSTALL.SH #对.sh文件授权 ./PATH_TO_INSTALL.SH --user #运行.sh文件
2、安装第三方库
在terminal中输入以下命令
sudo apt-get install python-numpy swig python-dev python-wheel #安装第三方库 sudo apt-get install git git clone git://github.com/numpy/numpy.git numpy
3、安装tensorflow
在terminal中输入以下命令
git clone https://github.com/tensorflow/tensorflow
在terminal中输入以下命令:
cd ~/tensorflow #切换到tensorflow文件夹 ./configure #执行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、创建pip
在tensorflow的根目录下,在terminal中输入以下命令:
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/***(你自己的用户名)/Desktop/tensorflow-0.10.0-cp2-none-any.whl
tensorflow-0.10.0-cp2-none-any.whl要根据你下载的文件名有所更改。
5、设置tensorflow环境
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测试
$ 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
出现的错误
操作
bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
报错
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'
可以进入tensorflow/third_party/gpus/crosstool/目录,打开CROSSTOOL文件,搜索cxx_builtin_include_directory,应该有三行,在下面添加行如下
cxx_builtin_include_directory: "/usr/local/cuda-8.0/include"
如果出现的错误是类似的,只要将cxx_builtin_include_directory: "/usr/local/cuda-8.0/include"
的文件路径改一下就可以了,亲测有效
再次运行上一步的命令,应该就没问题了。