CPU instructions not compiled with TensorFlow

Question

MacBook Air: OSX El Capitan

When I run TensorFlow code in terminal (python 3 tfpractice.py), I get a longer than normal waiting time to get back output followed by these error messages:

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.

I have no clue how to fix this. I would like to get TensorFlow to just work on this pip3 install. So I followed the path to: tensorflow/core/platform/cpu_feature_guard

Do I need to edit the code here? Or is there an alternate way to get TensorFlow to compile with these instructions?

I installed TensorFlow using sudo pip3 install tensorflow.

Answer 1

NOTE : These are not error messages but mere warning messages.

The best way to maximise TF performance (apart from writing good code !!), is to compile it from the sources

When you do that, TF would ask you for a variety of options which will also involve options for these instructions.

In my own experience, compilation from the source is better in performance on an average.

If you are doing some intensive processing that could be done on a GPU then that might also explain your waiting time. For GPU support you would need to do pip3 install tensorflow-gpu