TensorFlow AVX/AVX2 Warning: How to Leverage CPU Instructions for Better Performance?

Your CPU Supports AVX and AVX2: What to Do When TensorFlow Complains

You may have encountered this warning message while using TensorFlow:

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

Understanding the Warning

Modern CPUs offer performance-enhancing instructions known as extensions, such as AVX (Advanced Vector Extensions). AVX includes FMA (fused multiply-accumulate) operations that significantly speed up linear algebra operations common in machine learning. The warning signifies that your CPU does support AVX, but TensorFlow is not configured to utilize it.

Why Isn't AVX Used by Default?

TensorFlow's default distribution is built without support for these extensions to ensure compatibility with a wide range of CPUs. Additionally, GPUs typically outperform CPUs for machine learning training, so the default builds focus on GPU compatibility.

Addressing the Issue

With a GPU:

If you have a GPU, TensorFlow will automatically prioritize it for compute-intensive operations, making the AVX support of your CPU less relevant. To suppress the warning, set:

import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

Without a GPU:

To utilize your CPU's full potential, consider building TensorFlow from the source with AVX, AVX2, and FMA enabled if your CPU supports them. While the build process is complex (involving the bazel build system), it should eliminate the warning and enhance TensorFlow's performance on your CPU.

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