
Install TensorFlow Addons on Raspberry 64 OS
64-OS TensorFlow 2.4.1
Introduction.
TensorFlow Addons give you additional functionality not yet included in the core of TensorFlow. If it has proven useful, a particular Addon merged into the TensorFlow package. Other algorithms remain in the Addons herd, only appreciated by a select few of the TF-community.
Due to the experimental nature of the package, versions have a short lifespan. Fourteen versions have been released in 2020 alone.
We hope to keep up with the pace. If not, please let us know, and we will try to provide the missing version on our GitHub page.
Because the Addons work entirely in conjuction with TensorFlow, we discuss only the 64-bit version. Installing a 32-bit version of TensorFlow on a Raspberry Pi is a nightmare, with disappointing performances. Better use the new and much snappier 64-bit operating system on your RPi.
Version check.
Please check your operating system before installing the TensorFlow Addons on your Raspberry 64-bit OS. Run the command uname -a and verify your version with the screen dump below.

You also need to check your C++ compiler version with the command gcc -v. It must also be an aarch64-linux-gnu version, as shown in the screenshot. If you have a 64-bit operating system, but your gcc version is different from the one given above, reinstall the whole operating system with the latest version. The guide is found here: Install 64 bit OS on Raspberry Pi 4. You must have a 64-bit C ++ compiler as we are going to build libraries. Even if you use Python wheels, gcc is called behind the curtains.
Also, note the zram swap size of more than 3 Gbyte after installation according to our instructions.
Tensorflow.
As said, the Addons work with the TensorFlow framework, so you need to have a working TensorFlow version on your system. If required, you can install a recent TensorFlow version according to one of our guides. You can check your TensorFlow version with the different Addons version here.
The wheel.
Once you have TensorFlow up and running, you can install the Addons. The easiest way to install the TensorFlow-Addons is by using the wheel we have placed on our GitHub page. It's the outcome of the time-consuming installation from scratch by Bazel, given in the next paragraph. Please follow the instructions.