If you are a developer working with TensorFlow, you might have encountered this error message: "Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2". This error message indicates that your CPU supports AVX and AVX2 instructions, but your TensorFlow binary was not compiled to use them. This can result in slower performance and reduced accuracy.
In this guide, we will provide you with step-by-step instructions on how to fix this error and improve the performance of your TensorFlow model.
What is AVX and AVX2?
AVX (Advanced Vector Extensions) and AVX2 are instruction set extensions developed by Intel Corporation. These extensions allow for faster and more efficient processing of data by enabling the CPU to perform multiple calculations on multiple data sets simultaneously.
Why is the AVX AVX2 error occurring?
The AVX AVX2 error occurs when you are using a TensorFlow binary that is not compiled to use the AVX and AVX2 instruction set extensions, even though your CPU supports them.
How to fix the AVX AVX2 error?
To fix the AVX AVX2 error, you will need to install TensorFlow from source and compile it with AVX and AVX2 support. Here are the steps:
Step 1: Install TensorFlow dependencies
Before you can install TensorFlow from source, you will need to install its dependencies. Open a terminal window and run the following command:
pip install -U --user pip six numpy wheel mock
Step 2: Clone the TensorFlow repository
Next, you will need to clone the TensorFlow repository from GitHub. To do this, run the following command:
git clone https://github.com/tensorflow/tensorflow.git
Step 3: Configure the TensorFlow build
Once you have cloned the TensorFlow repository, navigate to the tensorflow directory and run the following command to configure the TensorFlow build:
./configure
When prompted, select the following options:
- Please specify the location of python: /usr/bin/python3
- Do you wish to build TensorFlow with GPU support?: No
- Do you wish to use jemalloc as the malloc implementation?: No
- Do you wish to build TensorFlow with OpenCL support?: No
- Do you wish to build TensorFlow with ROCm support?: No
- Do you wish to build TensorFlow with CUDA support?: No
- Do you wish to build TensorFlow with MPI support?: No
- Please specify optimization flags to use during compilation: -march=native
Step 4: Compile TensorFlow with AVX and AVX2 support
Now that you have configured the TensorFlow build, run the following command to compile TensorFlow with AVX and AVX2 support:
bazel build --config=opt --copt=-march=native //tensorflow/tools/pip_package:build_pip_package
This command will take some time to complete. Once it is finished, run the following command to create a pip package of TensorFlow:
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
Step 5: Install TensorFlow with AVX and AVX2 support
Finally, install the TensorFlow pip package that you just created by running the following command:
pip install /tmp/tensorflow_pkg/tensorflow-<VERSION>-cp37-cp37m-linux_x86_64.whl
Replace <VERSION> with the version number of TensorFlow that you just compiled.
Frequently Asked Questions (FAQ)
Q: What is TensorFlow?
A: TensorFlow is an open-source machine learning framework developed by Google.
Q: What is AVX?
A: AVX (Advanced Vector Extensions) is an instruction set extension developed by Intel Corporation that allows for faster and more efficient processing of data.
Q: What is AVX2?
A: AVX2 is an extension of AVX that provides even faster and more efficient processing of data.
Q: Why is the AVX AVX2 error occurring?
A: The AVX AVX2 error occurs when you are using a TensorFlow binary that is not compiled to use the AVX and AVX2 instruction set extensions, even though your CPU supports them.
Q: How can I check if my CPU supports AVX and AVX2?
A: You can check if your CPU supports AVX and AVX2 by running the following command in a terminal window:
grep -o avx /proc/cpuinfo | wc -l
If the output is greater than 0, your CPU supports AVX. To check if your CPU supports AVX2, run the following command:
grep -o avx2 /proc/cpuinfo | wc -l
If the output is greater than 0, your CPU supports AVX2.