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Federated learning via stochastic gradient descent
I 'm doing my research on federated meta-learning, and I decide to follow the type of MAML by using the two step gradient decent trick on the client side. However, when I tried to modify the client code in the repository from the original one to the meta-learning one, I got really low testing accuracy on the server. The accuracy can only raise up to about 20% at most. I 'm wondering why, and I have no idea. Could anyone offer some advice? My client code is pasted as follows.
client.zip
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