本节书摘来自异步社区《TensorFlow技术解析与实战》一书中的第2章,第2.4节,作者李嘉璇,更多章节内容可以访问云栖社区“异步社区”公众号查看
从源代码编译安装,需要使用Bazel编译工具。我们先安装Bazel工具。在需要依赖的JDK 8配好之后,在Mac笔记本上直接执行下面命令,安装版本是0.4.4:
brew install bazel其他操作系统(如Ubuntu)的计算机对Bazel的安装,可以采用apt-get等方式。
先进入tensorflow-1.1.0的源代码目录,运行./configure脚本会出现所采用的Python路径、是否用HDFS、是否用Google Cloud Platform等选项,读者可以根据自己的需要进行配置,或者直接按“回车”采用默认配置。
下面我们演示使用CPU版本的编译。具体如下:
tensorflow-1.1.0 ./configure Please specify the location of python.[Default is /usr/local/bin/python]: Please specify optimization flags to use during compilation [Default is -march=native]: Do you wish to use jemalloc as the malloc implementation? (Linux only) [Y/n] jemalloc enabled on Linux Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] No Google Cloud Platform support will be enabled for TensorFlow Do you wish to build TensorFlow with Hadoop File System support? [y/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] No XLA support will be enabled for TensorFlow Found possible Python library paths: /usr/local/Cellar/python/2.7.12_2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages /Library/Python/2.7/site-packages Please input the desired Python library path to use. Default is [/usr/local/Cellar/ python/2.7.12_2/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages] Using python library path: /usr/local/Cellar/python/2.7.12_2/Frameworks/Python. framework/Versions/2.7/lib/python2.7/site-packages Do you wish to build TensorFlow with OpenCL support? [y/N] No OpenCL support will be enabled for TensorFlow Do you wish to build TensorFlow with CUDA support? [y/N] No CUDA support will be enabled for TensorFlow Configuration finished随后,我们执行bazel编译命令,因为编译时需要耗费大量的内存,加入--local_resources 2048,4,1.0来限制内存大小。具体如下:
bazel build --local_resources 2048,4,1.0 -c opt //tensorflow/tools/pip_package:build_ pip_package bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg然后进入/tmp/tensorflow_pkg,可以看到生成的文件tensorflow-1.1.0-cp27-cp27m-macosx_10_12_intel.whl,直接安装如下:
``pip install /tmp/tensorflow_pkg/tensorflow-1.1.0-cp27-cp27m-macosx_10_12_intel.whl``使用GPU版本的编译需要配置中选择使用CUDA,然后填写对应的CUDA SDK版本等,其他步骤均相同。
相关资源:敏捷开发V1.0.pptx