macos下如何尝试编译tensorflow

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编译环境及其工具

编译工具:bazel (https://bazel.build/versions/master/docs/bazel-overview.html)

mac 操作系统版本：16.1.0 Darwin Kernel

tensorflow 版本：github 当前master分支

编译操作过程

git clone https://github.com/tensorflow/tensorflow
cd tensorflow
./configure  
配置过程没有使用GPU

bazel build -c opt //tensorflow/tools/pip_package:build_pip_package

bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg

sudo pip install /tmp/tensorflow_pkg/tensorflow-1.0.1-cp27-cp27m-macosx_10_12_intel.whl

hello world 案例

(dev-djdemo) ➜  dev-djdemo python
Python 2.7.10 (default, Jul 30 2016, 18:31:42)
[GCC 4.2.1 Compatible Apple LLVM 8.0.0 (clang-800.0.34)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
>>> print(sess.run(hello))
Hello, TensorFlow!

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