Hello All,
I am trying to implement federated learning for my research. However, the tutorials or code snippets that I found (on MNIST) distribute a collected MNIST dataset over n number of clients.
To make this simple, suppose I have just 2 clients with different data as inputs(for eg. client A has data 1-5 and client B has data 6-10). I want to train the model separately on Client A and Client B with their respective data (not distributing the combined dataset). Is this possible to do so? can you please give me an example to proceed further?
To clarify on my current setup, I am using Windows 10 with pytorch 1.0.0 and do not know if additional libraries like pysyft works for my version. I just want to make it work using pytorch.
I would really appreciate anybody’s help on this.