Understanding AVX is a prerequisite to resolving the “your CPU supports instructions that this TensorFlow” error. Intel and AMD microprocessors’ Advanced Vector Extensions (also known as Sandy Bridge New Extensions) are referred to as AVX. These are x86 instruction set extensions. Features, instructions, and coding schemes are all updated in this version.
AVX2, also known as Haswell New Instructions, increases the bit size of most integer commands from 64 to 256. Intel introduced it for the first time with its Haswell processors. Many operations were sped up because to the AVX’s FMA, which performs a floating-point multiply-add operation in a single step.
Furthermore, AVX improves the speed and ease of use of algebra computations. CPUs that implement AVX and FMA may outperform older CPUs in terms of performance. AVX-incompatible CPUs may, nevertheless, display this warning.
Because of this Error Message “Your CPU Does Not Support the Instructions that are Required By This TensorFlow,” What may be Done?
“Your CPU supports instruction types that this TensorFlow binary was not compiled to use: FMA” indicates that the shared library of TensorFlow does not include instructions that your CPU is capable of using. AVX instructions may not be supported by some older CPU architectures following the release of TensorFlow 1.6 binaries.
Since the AVX instructions aren’t supported by earlier CPUs, you’ll have to compile TensorFlow from source on newer ones. Why can’t the AVX be used as a default option? Due to the fact that TensorFlow is produced without CPU extensions, this causes the problem.
The Way to Fix the Error “Your CPU Supports Instructions That This TensorFlow”
AVX and AVX2 instructions are not supported by this TensorFlow binary. How can I change this? TensorFlow was constructed from the source, which is why you received the warning notice.
These AVX support warnings can be ignored if you have a GPU installed in your machine. This error message can be disabled by adding the following text to your code. Importing the OS module and setting the mapping object is all that is required here.
Input the os
It is os.environ[‘TF CPP’] = ‘2;’
The export command in the bash shell can be used on a Unix system.
exported 2 is the minimum level of logging for TF CPP.
To use your CPU as much as possible, you must build TensorFlow from the source with AVX, AVX2, and FMA enabled if you don’t have a GPU.