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use of Xaynet with Raspberry pi #961
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Hi @prathapkumarbaratam, yes that is possible. You can use our Python SDK to write your own client that fits your needs or you can also take a look into our examples in bindings/python/examples. Please note that the PET protocol requires at least three clients in order to function. Further, the selection of clients is random, which means that it will probably require more than three clients for the server to run several rounds. If you need any further assistance, please let me know. |
Thanks for quick response @Robert-Steiner . When Iam running rust examples. Iam getting error like this. can you help me in this? the first pic i have tried running coordinater and second pic I have tried running example with 4 participants and getting log like that. can you figure it out once Thanks and Regards |
This does not seems to be related with the project. Maybe you have a compilation that hanged some where and it is still keeping the lock or some inconsistency within the |
@prathapkumarbaratam I also recommend to use |
@Robert-Steiner can you tell me why iam getting this error after running Docker-compose for this case(I am bit new to docker). it is saying that app/configs not found. And also tell me step by step with commands how to run FL using xaynet framework. Thanks and Regards, |
The coordinator is running correctly. You can follow this example to create https://github.com/xaynetwork/xaynet/blob/master/bindings/python/examples/keras_house_prices/README.md your own client. |
@acrrd Iam getting following error after creating xaynet virtual environment. seems xaynet-sdk-python not supported? |
are you using python 3.6 or higher? I cannot reproduce this. |
iam using python 3.7.9 version @acrrd @Robert-Steiner |
hi @Robert-Steiner , Iam currently working on 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 a model for 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 a new model would be sent to the PIs. Is such a workflow possible with your framework? If so, could you provide me with a hint?any other examples using xaynet if possible?
Thank you,
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