Hello Everyone
I am trying to create a Decentralized federated learning scenario in TensorFlow, where the clients communicate among themselves and update their parameters; there is no central server or an aggregator like in the case of centralized federated learning.
- Is it possible to create this scenario in TensorFlow
- Is it possible to use lambda functions as a ping to do the parameter updates among the client network
- I have my custom pre-trained models in PyTorch can I transfer them to TensorFlow and use them here, if so how can I export my models to TensorFlow
If there are any other suggestions that would help me build this scenario please let me know