How to try to compile tensorflow under mac os
This article is to share with you about how to try to compile tensorflow under mac os, the editor thinks it is very practical, so I share it with you to learn. I hope you can get something after reading this article.
Compilation environment and its tools
Compilation tool: bazel (https://bazel.build/versions/master/docs/bazel-overview.html)
Mac operating system version: 16.1.0 Darwin Kernel
Tensorflow version: github current master branch
Compilation operation process
Git clone https://github.com/tensorflow/tensorflow
Cd tensorflow
. / configure
GPU is not used in the configuration process
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 case
(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, TensorFlowers')
> > 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! The above is how to try to compile tensorflow under mac os. The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.
