I am trying to get tensorflow installed on a raspberry pi 4 which is running manjaro. It is to use the open source BNN library Larq, which recommended manjaro as an OS because it was 64bit as opposed to Raspbian. I have tried to install using yay from Archlinux user repository but got a couple different errors, like: "tensorflow/workspace.bzl: patch does not apply" and a failure to download. Any suggestions, I am very new to manjaro.
As a side note, I am not particularly stuck to Manjaro is anyone has experience using Larq and the larq compute engine on a RPi4 with a different OS any insight there would be helpful as well.
Thank you!
I cannot help you with Manjaro. However, I used Ubuntu 20.04 (64 bits) on my RPI4. I suppose you need the RPI4 to deploy and run your BNNs. If I am correct, I give you the following advice.
Please, note that the RPI4 is needed only to run LCE models (*.tflite). To this end, you don't need to install Tensorflow on your RPI4. For everything else (see below) you can use a regular Linux box.
To check if everything is fine with your runtime environment (i.e. the RPI4), You can use your main Larq+LCE installation to convert one of your models into an LCE model and test it with the benchmark tool available here. For the RPI4+Ubuntu you should use lce_benchmark_model_aarch64.
If you need to compile your own BNN-based applications for your RPI4, you can follow the build guide on the LCE website. I did it once a long time ago. I used the LCE Docker to have a working environment. Then, from the inside of the docker, I followed the ARM guide: "Cross-compiling with Make" version.
I hope this helps.