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This repository was archived by the owner on Aug 30, 2022. It is now read-only.
Currently I am working on a school project about federated learning and came across your framework during exploratory analysis. My project should utilize federated learning in this manner - I have an aggregation server (let's say in a cloud). I want this server to provide model to my 2 Raspberry PIs. These two RPIs would then train the model on a local data for x epochs and provide the trained models/gradients back to the global server. On this server, the results would be federated averaged and new model would be sent to the PIs. Is such a workflow possible with your framework? If so, could you provide me a hint?