It seems that the number of joining clients (not the num of computing clients) is fixed in fedml_api/data_preprocessing/**/data_loader and cannot be changed except CIFAR10 datasets.

Here I mean that it seems the total clients is decided by the datasets, rather the input from run_fedavg_distributed_pytorch.sh.

https://github.com/FedML-AI/FedML/blob/3d9fda8d149c95f25ec4898e31df76f035a33b5d/fed

Description

Previously we had the issue that tensorflow==2.3.0 could not be properly installed with poetry. As we updated tensorflow to 2.3.1 we should reevaluate this and accordingly adjust all workarounds in which we install tensorflow with pip.

ToDo

• Check if the project setup works correctly if tensorflow is not installed using pip but rather using poetry like every

Is your feature request related to a problem? Please describe.
Currently ambianic-edge is packaged with its source directly in a docker container.

Describe the solution you'd like
For better modularity and portability, we should package as a python wheel as we already do with peerjs-python.

Additional context
There will be some tricky parts with declaring optional or on-deman